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geeeeeeeeeeeeeeeeeeeez

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Political consultancy Cambridge Analytica, the firm at the centre of the Facebook data-sharing scandal, is shutting down, it says.

The firm was accused of improperly using data on behalf of political clients.

The Facebook data of up to 87 million people was improperly shared with the political consultancy.

The social network and advertising giant declined to comment.

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Political consultancy Cambridge Analytica, the firm at the centre of the Facebook data-sharing scandal, is shutting down, it says. The firm was accused of improperly using data on behalf of political clients. The Facebook data of up to 87 million people was improperly shared with the political consultancy.

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SAN FRANCISCO (Analysis) - Google - the advertising and search engine monolith that once touted its official commitment, "Don't be evil" - has thrown its full weight behind the U.S. military-industrial complex's fast-advancing unmanned drone program - and more than three thousand of its employees will have none of it.
Watch | Project Maven: The Pentagon's New Artificial Intelligence

This plan will irreparably damage Google's brand and its ability to compete for talent. Amid growing fears of biased and weaponized AI, Google is already struggling to keep the public's trust. By entering into this contract, Google will join the ranks of companies like , Raytheon, and General Dynamics. The argument that other firms, like Microsoft and Amazon, are also participating doesn't make this any less risky for Google. Google's unique history, its motto Don't Be Evil, and its direct reach into the lives of billions of users set it apart."

However, journalist and author Yasha Levine has explained in his new book Surveillance Valley: The Secret Military History of the Internet that Google long been a leading Silicon Valley vendor to the U.S. repressive state:

Over the years, [Google] supplied mapping technology used by the U.S. Army in Iraq, hosted data for the Central Intelligence Agency, indexed the National Security Agency's vast intelligence databases, built military robots, co-launched a spy satellite with the Pentagon, and leased its cloud computing platform to help police departments predict crime. And Google is not alone. From Amazon to eBay to Facebook ... Some parts of these companies are so thoroughly intertwined with America's security services that it is hard to tell where they end and the U.S. government begins.

The grim calculus of remote-controlled warfare

Reports have shown that the use of drones in such locales as Afghanistan, Iraq, Libya, Pakistan, Syria, Yemen and other theaters of operations have claimed a vast number of civilian lives - in 2017, according to surveys. According to New York Times Magazine , which surveyed 150 Coalition drone strikes carried out in Iraq over an 18-month period, one out of every five strikes kills civilians.
Watch | Suffering in Silence: a documentary about the war on terror in Pakistan

A program of targeted killing far from any battlefield, without charge or trial ... violates international law, under which lethal force may be used outside armed conflict zones only as a last resort to prevent imminent threats, when non-lethal means are not available.

There is very little information available to the public about the U.S. targeting of people far from any battlefield, so we don't know when, where and against whom targeted killing can be authorized ... The secrecy and lack of standards for sentencing people to death, resulting in a startling lack of oversight and safeguards, is one of our prime concerns with this program."

Google defends its public image (and low-profile military ties)

Claiming that it values the input of its employees as an "important part" of its company culture, Google has promised to address the AI-drone issue without making specific comments on the employees' demands. In a statement Tuesday, the company said:

Any military use of machine learning naturally raises valid concerns. We're actively engaged across the company in a comprehensive discussion of this important topic and also with outside experts, as we continue to develop our policies around the development and use of our machine learning technologies."

Google has also defended its participation in the Pentagon program with the claim that its usage is specifically for non-offensive purposes and uses open-source object-recognition software based on non-classified data that's freely available to any users of the Google Cloud, and could in fact save lives while saving labor through the use of AI.
Read more by Elliot Gabriel
Google itself has long been interested in developing its own line of drone products, including private delivery drones .
Watch | Eric Schmidt at the Artificial Intelligence and Global Security Summit
"It comes from a, it's essentially related to the history of the Vietnam War and the founding of the tech industry," Schmidt added.

That Google helps the military build more efficient systems of surveillance and death shouldn't be surprising. The company has spent the last 15 years selling souped-up versions of its information technology to mil and intel agencies. https://t.co/8UfdiGVeqc

- Yasha Levine (@yashalevine) March 16, 2018

Indeed, Levine argues:

In the 1960s, America was a global power overseeing an increasingly volatile world: conflicts and regional insurgencies against U.S.-allied governments from South America to Southeast Asia and the Middle East. These were not traditional wars that involved big armies but guerrilla campaigns and local rebellions, frequently fought in regions where Americans had little previous experience. Who were these people? Why were they rebelling? What could be done to stop them? In military circles, it was believed that these questions were of vital importance to America's pacification efforts, and some argued that the only effective way to answer them was to develop and leverage computer-aided information technology."

Surveillance capitalism's military-industrial roots

In a 2014 essay for Monthly Review magazine titled " Surveillance Capitalism: Monopoly-Finance Capital, the Military-Industrial Complex, and the Digital Age ," authors John Bellamy Foster and Robert W. McChesney coined the phrase surveillance capitalism , tracing its origins to the inception of a post-World War II "new Pentagon capitalism" that came to be known as the military-industrial complex.

Under the model - revolutionized by then-Army Chief of Staff and later President Dwight D. Eisenhower - the U.S. technological, scientific research and industrial capacity were to become "organic parts of our military structure" in conditions of national emergency, effectively giving the civilian economy a dual-use purpose. In a 1946 memorandum, Eisenhower noted:

The future security of the nation ... demands that all those civilian resources which by conversion or redirection constitute our main support in time of emergency be associated closely with the activities of the Army in time of peace."

The model became a permanent feature of the U.S. economy, giving birth to a sprawling military-civilian economic base Eisenhower famously criticized in his 1961 farewell address to the nation. Civilian industry, science, and academia were used alongside an exorbitant and perpetually-expanding war budget to underwrite the Defense Department's never-ending state of conflict with Cold War enemies and unruly populations, making the world safe for the unchallenged reign of U.S. monopoly capitalism (imperialism ) and "pump-priming" the economy whenever an additional surge of " military Keynesian " government spending was required.
Watch | Richard Wolff On Trump's Defence Spending
Levine posits that a primary purpose of conceiving the "information superhighway" was the need for a computerized counterinsurgency tool that could predict and check the "perceived global spread of communism" and provide real-time surveillance of potential threat groups:

The Internet came out of this effort: an attempt to build computer systems that could collect and share intelligence, watch the world in real time, and study and analyze people and political movements with the ultimate goal of predicting and preventing social upheaval. Some even dreamed of creating a sort of early warning radar for human societies: a networked computer system that watched for social and political threats and intercepted them in much the same way that traditional radar did for hostile aircraft. In other words, the Internet was hardwired to be a surveillance tool from the start. No matter what we use the network for today - dating, directions, encrypted chat, email, or just reading the news - it always had a dual-use nature rooted in intelligence gathering and war."

The Arpanet system formed the backbone of U.S. military communications from 1969 until 1989, when the World Wide Web was introduced to civilian consumers. The unveiling of the World Wide Web opened the floodgates to the use of the internet by users across the globe, as well as its subsequent commercialization and the resulting dot com boom of the mid-to-late 1990s, when Google was founded.
Watch | Yasha Levine on why we lost our fear of computers as tools of social control
Vast strides in biometrics, analytics research, AI, and deep-learning technology - perfected not only by Google but by academic researchers and technology firms across the globe - have vastly boosted the state's ability to surveil and control populations and police dissent across the globe. Many of the technologies developed by global arms, surveillance, and data-analysis firms are supplied to countries requiring tailor-made solutions to unrest such as , , , Saudi Arabia , , , and Azerbaijan .

The extent of Silicon Valley's integration with the U.S. government was laid bare to the public in 2013, when Edward Snowden provided evidence proving that the U.S. National Security Agency (NSA) and Federal Bureau of Investigation (FBI) had direct access to the internal servers of nine major tech firms - AOL, Apple, Facebook, Google, Microsoft, PalTalk, Skype, YouTube, and Yahoo - each of which provided direct access through major internet service providers to the NSA through its secret projects like Boundless Informant and Prism.

Foster and McChesney explained:

These monopolistic corporate entities readily cooperate with the repressive arm of the state in the form of its military, intelligence, and police functions. The result is to enhance enormously the secret national security state, relative to the government as a whole.

Edward Snowden's revelations of the NSA's Prism program, together with other leaks, have shown a pattern of a tight interweaving of the military with giant computer-Internet corporations, creating what has been called a 'military-digital complex.' Indeed, Beatrice Edwards, the executive director of the Government Accountability Project, that what has emerged is a 'government-corporate surveillance complex."

Information superiority and the modern battlefield

As a matter of survival, however, all modern militaries - both regular and irregular, large and small - are being forced to adapt to the digitization of warfare. , , and even non-state actors like Lebanese resistance group are fast making technological advances to keep pace in the informationized battlefield.

The weaponized nature of digital technology is a pandora's box that may prove impossible to close. Be that as it may, Google's employees are livid about their participation in these developments:

We cannot outsource the moral responsibility of our technologies to third parties ... Building this technology to assist the U.S. Government in military surveillance - and potentially lethal outcomes - is not acceptable."

While the tech conglomerate workers' attempt to decouple Google from the Pentagon may be in vain, one can only applaud their efforts to protest the tech conglomerate's complicity in the bloodshed wrought by U.S. imperialism through its array of increasingly high-tech implements of death.

Top Photo | An RQ-4 Global Hawk gets all pre-flight checks accomplished from maintenance technicians before a mission while deployed at an air base in Southwest Asia. The (U.S. Air Force photo)
Elliott Gabriel is a former staff writer for teleSUR English and a MintPress News contributor based in Quito, Ecuador. He has taken extensive part in advocacy and organizing in the pro-labor, migrant justice and police accountability movements of Southern California and the state's Central Coast.
Stories published in our Daily Digests section are chosen based on the interest of our readers. They are republished from a number of sources, and are not produced by MintPress News. The views expressed in these articles are the author's own and do not necessarily reflect MintPress News editorial policy.

Republish our stories! MintPress News is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License.

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Google's Drone War Project Shows Big Data's Military Roots

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SAN FRANCISCO (Analysis) - Google - the advertising and search engine monolith that once touted its official commitment, "Don't be evil" - has thrown its full weight behind the U.S. military-industrial complex's fast-advancing unmanned drone program - and more than three thousand of its employees will have none of it.

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By 2020, China plans to give all of its 1.4 billion citizens a personal score, based on how they behave. To create those scores, which could affect whether someone is allowed to fly or own property, China is using facial recognition, artificial intelligence, smart glasses and other technologies to monitor, rate and sometimes shame its citizens.

China's plan is to give each citizen a social credit score, which goes far beyond the traditional credit score based on finances. The score can fluctuate based on a range of behaviors, like whether you jaywalk or buy Chinese-made goods or buy too many video games. If your score gets too low, you can be banned from buying a plane ticket, renting a house, accessing high-speed internet or getting a loan.

CBS News

Sensetime, one of China's most successful artificial intelligence companies, has created smart cameras for the government that can help catch criminals but also track average citizens. As people, bikes, cars and buses pass in front of the cameras, identifiers pop up.

"It can recognize more than 4,000 vehicles," CEO Xu Li explains. "We can tell whether it is an adult, a child, male or female."

With China's millions of surveillance cameras, the government can record jaywalkers at city intersections, zero in on their faces and then shame them on public video screens.

Police in Beijing have been seen wearing glasses that resemble Google Glass and can recognize faces linked to the government's national database.

AFP/Getty

The fear is that the government will use this social credit scoring system to punish people who aren't sufficiently loyal to the Communist party. Trying to clear your name or fight your score is nearly impossible, since there is no real due process.

Special Reports: CNET's in-depth features in one place.

CNET Magazine: Check out a sample of the stories in CNET's newsstand edition.

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China turns to tech to monitor, shame and rate citizens

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By 2020, China plans to give all of its 1.4 billion citizens a personal score, based on how they behave. To create those scores, which could affect whether someone is allowed to fly or own property, China is using facial recognition, artificial intelligence, smart glasses and other technologies to monitor, rate and sometimes shame its citizens.

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A report published Wednesday by the Senate Commerce Committee says that data brokers are targeting poor consumers by grouping them based on their financial vulnerability.

According to the report, marketers who purchase this data then use the information to sell risky financial products to the people who can least afford them.

Though marketers often argue that consumer data is necessary to make advertising relevant to customers' interests and preferences, the Committee report said the nine data collection companies it reviewed sort people into less benign categories like "Rural and Barely Making It," "Ethnic Second-City Strugglers," and "Credit Crunched: City Families."

Here's a list of the less-than-favorable descriptions data brokers are using to define subsets of poor consumers, according to the Senate Commerce Committee's report:

The Committee staff compiled its report using information it requested from nine data sellers about where they get their information and how they use it. The respondents were: Acxiom, Experian, Epsilon, Reed Elsevier, Equifax, TransUnion, Rapleaf, Spokeo, and Datalogix.

The report said that while some data brokers have policies that prohibit their customers from using their information to sell debt-related products, the lack of industry oversight allows data brokers wiggle room when it comes to enforcing the terms of these contracts.

It highlighted the "Hard Times" product offered by Experian as an example of how brokers define financially vulnerable consumers. Experian told the Committee that it describes the people whose contact information is included in its bundle as follows:

"This is the bottom of the socioeconomic ladder, the poorest lifestyle segment in the nation. Hard Times are older singles in poor city neighborhoods. Nearly three-quarters of the adults are between the ages of 50 and 75; this is an underclass of the working poor and destitute seniors without family support....One-quarter of the households have at least one resident who is retired."

Marketing materials for another Experian product explicitly advertise its ability to help marketers identify "under-banked consumers" who have procured payday loans, through which a person borrows a small amount of money at a high interest rate with the expectation that the money will be paid back when the borrower receives his or her next payday.

According to The Pew Charitable Trusts, these loans are either expressly prohibited or made illegal by other lending laws in 14 states and the District of Columbia.

"The products companies described to the Committee include consumer profiles characterizing consumers based on degree of financial vulnerability and propensity to use payday loans and other non-traditional financial products," the report said. "The names, descriptions and characterizations in such products likely appeal to companies that sell high-cost loans and other financially risky products to populations more likely to need quick cash, and the sale and use of these consumer profiles merits close review."

Though the Senate Commerce Committee report did not investigate whether the companies it surveyed gave consumer information to marketers who used it in predatory fashion, the report cited several past incidents as evidence of how such fraud does, in fact, occur.

In one particularly egregious case, a telemarketer stole from a 92-year-old Army veteran's bank account after receiving information from the data broker InfoUSA, which advertised lists like "Oldies But Goodies" to reach people described as "gullible . . . [who] want to believe their luck can change."

The report further chastised three of its respondents - Acxiom, Experian and Epsilon - for not giving up certain information about where their data comes from.

"This is serious stuff," Senate Commerce Committee Chairman Jay Rockefeller said at a hearing the day the report was released. "We have the feeling people are getting scammed or screwed. ... It's up to you to talk us out of that."

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How Marketers Use Big Data To Prey On The Poor

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A report published Wednesday by the Senate Commerce Committee says that data brokers are targeting poor consumers by grouping them based on their financial vulnerability. According to the report, marketers who purchase this data then use the information to sell risky financial products to the people who can least afford them.

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An automatic bathroom soap dispenser has sparked outrage online after it was filmed failing to detect the hand of a dark-skinned person.

Chukwuemeka Afigbo, Facebook's head of platform partnerships in the Middle East and Africa, posted a video of a white man waving his hand under the dispenser and getting soap on the first try. However, when a darker-skinned man does the same, no soap is released.

A white paper towel is then waved under the dispenser, which works.

Afigbo tweeted: "If you have ever had a problem grasping the importance of diversity in tech and its impact on society, watch this video."

Some Twitter users blamed the lack of diversity in tech industries for the problem:

But others said it was nothing to do with race, blaming a technological error and labelling the backlash "crazy":

Soap dispensers like this one tend to work by measuring infrared light radiating from nearby objects. Body heat emits infrared radiation.

The dispenser sends out an invisible light from an infrared LED bulb and activates when a hand reflects light back to the sensor.

But darker colours absorb light rather than bounce it back, preventing the soap from being released.

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This soap dispenser has been accused of racism

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An automatic bathroom soap dispenser has sparked outrage online after it was filmed failing to detect the hand of a dark-skinned person. Chukwuemeka Afigbo, Facebook's head of platform partnerships in the Middle East and Africa, posted a video of a white man waving his hand under the dispenser and getting soap on the first try.

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There's this great Andy Warhol quote you've probably seen before: "I think everybody should like everybody." You can buy posters and plates with pictures of Warhol, looking like the cover of a Belle & Sebastian album, with that phrase plastered across his face in Helvetica. But the full quote, taken from a 1963 interview in Art News, is a great description of how we interact on social media today.

Warhol: Someone said that Brecht wanted everybody to think alike. I want everybody to think alike. But Brecht wanted to do it through Communism, in a way. Russia is doing it under government. It's happening here all by itself without being under a strict government; so if it's working without trying, why can't it work without being Communist? Everybody looks alike and acts alike, and we're getting more and more that way.
I think everybody should be a machine. I think everybody should like everybody.
Art News: Is that what Pop Art is all about?
Warhol: Yes. It's liking things.
Art News: And liking things is like being a machine?
Warhol: Yes, because you do the same thing every time. You do it over and over again.

The like and the favorite are the new metrics of success-very literally. Not only are they ego-feeders for the stuff we put online as individuals, but advertisers track their campaigns on Facebook by how often they are liked. A recent New York Times story on a krill oil ad campaign lays bare how much the like matters to advertisers. Liking is an economic act.

I like everything. Or at least I did, for 48 hours. Literally everything Facebook sent my way, I liked-even if I hated it. I decided to embark on a campaign of conscious liking, to see how it would affect what Facebook showed me. I know this sounds like a stunt (and it was) but it was also genuinely just an open-ended experiment. I wasn't sure how long I'd keep it up (48 hours was all I could stand) or what I'd learn (possibly nothing.)

See, Facebook uses algorithms to decide what shows up in your feed. It isn't just a parade of sequential updates from your friends and the things you've expressed an interest in. In 2014 the News Feed is a highly-curated presentation, delivered to you by a complicated formula based on the actions you take on the site, and across the web. I wanted to see how my Facebook experience would change if I constantly rewarded the robots making these decisions for me, if I continually said, "good job, robot, I like this." I also decided I'd only do this on Facebook itself-trying to hit every Like button I came across on the open web would just be too daunting. But even when I kept the experiment to the site itself, the results were dramatic.

>There is a very specific form of Facebook messaging, designed to get you to interact. And if you take the bait, you'll be shown it ad nauseam.

The first thing I liked was Living Social-my friend Jay had liked it before me and it was sitting at the top of my feed. I liked two more updates from friends. So far, so good. But the fourth thing I encountered was something I didn't really like. I mean, I don't truly like Living Social either, whatever the hell that is, but who cares. But this fourth thing was something I sort of actively disliked. A bad joke-or at least a dumb one. Oh well. I liked it anyway.

One thing I had to decide right away was what to do about the related items that appear after you've liked something. Let's say you like a story about cows that you see on Modern Farmer. Facebook will immediately present you with four more options to like things below that cow story, "relateds" in Facebook parlance. Probably more stories about cows or agriculture.

Relateds quickly became a problem, because as soon as you like one, Facebook replaces it with another. So as soon as I liked the four relateds below a story, it immediately gave me four more. And then four more. And then four more. And then four more. I quickly realized I'd be stuck in a related loop for eternity if I kept this up. So I settled on a new rule: I would like the first four relateds Facebook shows me, but no more.

Sometimes, liking is counterintuitive. My friend Hillary posted a picture of her toddler Pearl, with bruises on her face. It was titled "Pearl vs. the concrete." I didn't like it at all! It was sad. Normally, it would be the kind of News Feed item that would compel me to leave a comment, instead of hitting the little thumbs up button. Oh well. Like. The only time I declined to like something was when a friend posted about the death of a relative. I just had a death in my family last week. It was a bridge I wasn't going to cross.

But there was still plenty more to like. I liked one of my cousin's updates, which he had re-shared from Joe Kennedy, and was subsequently beseiged with Kennedys to like (plus a Clinton and a Shriver). I liked Hootsuite. I liked The New York Times, I liked Coupon Clipinista. I liked something from a friend I haven't spoken to in 20 years-something about her kid, camp and a snake. I liked Amazon. I liked fucking Kohl's. I liked Kohl's for you.

My News Feed took on an entirely new character in a surprisingly short amount of time. After checking in and liking a bunch of stuff over the course of an hour, there were no human beings in my feed anymore. It became about brands and messaging, rather than humans with messages.

Likewise, content mills rose to the top. Nearly my entire feed was given over to Upworthy and the Huffington Post. As I went to bed that first night and scrolled through my News Feed, the updates I saw were (in order): Huffington Post, Upworthy, Huffington Post, Upworthy, a Levi's ad, Space.com, Huffington Post, Upworthy, The Verge, Huffington Post, Space.com, Upworthy, Space.com.

Also, as I went to bed, I remember thinking "Ah, crap. I have to like something about Gaza," as I hit the Like button on a post with a pro-Israel message.

By the next morning, the items in my News Feed had moved very, very far to the right. I'm offered the chance to like the 2nd Amendment and some sort of anti-immigrant page. I like them both. I like Ted Cruz. I like Rick Perry. The Conservative Tribune comes up again, and again, and again in my News Feed. I get to learn its very particular syntax. Usually it went something like this:

A sentence recounting some controversial news. Good!

A sentence explaining why this is good.

A call to action, often ending with a question?

Once I see this pattern, I start noticing it everywhere. SF Gate, the San Francisco Chronicle's web presence, uses a similar tactic. It is a very specific form of Facebook messaging, designed to get you to interact. And if you take the bait, you'll be shown it ad nauseam.

I was also struck by how different my feeds were on mobile and the desktop, even when viewed at the same time. By the end of day one, I noticed that on mobile, my feed was almost completely devoid of human content. I was only presented with the chance to like stories from various websites, and various other ads. Yet on the desktop-while it's still mostly branded content-I continue to see things from my friends. On that little bitty screen, where real-estate is so valuable, Facebook's robots decided that the way to keep my attention is by hiding the people and only showing me the stuff that other machines have pumped out. Weird.

As day one rolled into day two, I began dreading going to Facebook. It had become a temple of provocation. Just as my News Feed had drifted further and further right, so too did it drift further and further left. Rachel Maddow, Raw Story, Mother Jones, Daily Kos and all sort of other leftie stuff was interspersed with items that are so far to the right I'm nearly afraid to like them for fear of ending up on some sort of watch list.

>Stop what you're doing and look at this baby that looks exactly like Jay-Z.

This is a problem much bigger than Facebook. It reminded me of what can go wrong in society, and why we now often talk at each other instead of to each other. We set up our political and social filter bubbles and they reinforce themselves-the things we read and watch have become hyper-niche and cater to our specific interests. We go down rabbit holes of special interests until we're lost in the queen's garden, cursing everyone above ground.

But maybe worse than the fractious political tones my feed took on was how deeply stupid it became. I'm given the chance to like a Buzzfeed post of some guy dancing, and another that asks Which Titanic Character Are You? A third Buzzfeed post informs me that "Katy Perry's Backup Dancer is the Mancandy You Deserve." According to New York magazine, I am "officially old" because Malia Obama went to Lollapalooza (like!) and CNN tells me "Husband Explores His Man-ternal Instincts" alongside a photo of a shirtless man cupping his nipples. A cloud that looks like a penis. Stop what you're doing and look at this baby that looks exactly like Jay-Z. My feed was showing almost only the worst kind of tripe that all of us in the media are complicit in churning out yet should also be deeply ashamed of. Sensational garbage. I liked it all.

While I expected that what I saw might change, what I never expected was the impact my behavior would have on my friends' feeds. I kept thinking Facebook would rate-limit me, but instead it grew increasingly ravenous. My feed become a cavalcade of brands and politics and as I interacted with them, Facebook dutifully reported this to all my friends and followers.

That first night, a small little circle with a dog's head popped up in the corner of my phone. A chat head, from Facebook's Messenger software! The dog turned out to be my old WIRED editor, John Bradley. "Have you been hacked," he wanted to know. The next morning, my friend Helena sent me a message. "My fb feed is literally full of articles you like, it's kind of funny," she says. "No friend stuff, just Honan likes." I replied with a thumbs up. This continued throughout the experiment. When I posted a status update to Facebook just saying "I like you," I heard from numerous people that my weirdo activity had been overrunning their feeds. "My newsfeed is 70 percent things Mat has liked," noted my pal Heather. Eventually, I would hear from someone who worked at Facebook, who had noticed my activity and wanted to connect me with the company's PR department.

But I'd already put a stop to it by then anyway, because it was just too awful. I tried counting how much stuff I'd liked by looking in my activity log, but it was too overwhelming. I'd added more than a thousand things to my Likes page-most of which were loathsome or at best banal. By liking everything, I turned Facebook into a place where there was nothing I liked. To be honest, I really didn't like it. I didn't like what I had done.

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I Liked Everything I Saw on Facebook for Two Days. Here's What It Did to Me

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There's this great Andy Warhol quote you've probably seen before: "I think everybody should like everybody." You can buy posters and plates with pictures of Warhol, looking like the cover of a Belle & Sebastian album, with that phrase plastered across his face in Helvetica.

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Here's some good news for Facebook, which hasn't had much to cheer about the past two months given it's Cambridge Analytica fiasco: Business is booming.

Facebook reported Q1 earnings Wednesday and everything was rosy. The company reported profit of $1.69 per share on revenue of $11.97 billion for the quarter, both better than Wall Street estimates. The revenue jump in particular was a 49 percent increase over the same quarter one year ago - and it seems as though the revenue growth slowdown that Facebook warned was coming almost two years ago is still somewhere off in the future.

Facebook user growth was also solid. The company added 49 million daily users, and now 1.45 billion people use the service every day. It added a million users in the U.S. and Canada, reversing a small but troubling dip last quarter when that group of users shrank for the first time.

The stock is up more than 4 percent in early after-hours trading.

The glaringly obvious takeaway here: No, Facebook's business was not decimated by its recent Cambridge Analytica privacy debacle.

We already knew that, of course. CEO Mark Zuckerberg told everyone earlier this month the scandal wasn't hurting usage or revenue. But even if you don't want to take his word for it, the Cambridge Analytica scandal didn't crop up until the last two weeks of March, which were also the last two weeks of the quarter. If user or advertiser backlash does have any impact, it will appear in Facebook's Q2 earnings, which we won't find out about until July.

Analysts expected Facebook to report profits of $1.36 per share on revenue of $11.4 billion for the quarter. That represented growth of 42 percent year over year, the lowest since Q3 2015 (though Facebook is comparing to much larger revenue totals now than it was then).

Facebook will talk about these numbers and take analyst questions at 5 pm ET today - we'll be listening in and will update here or post others at Recode as we learn more.

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Facebook finally has a good day: Business is booming

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Here's some good news for Facebook, which hasn't had much to cheer about the past two months given it's Cambridge Analytica fiasco: Business is booming. Facebook reported Q1 earnings Wednesday and everything was rosy. The company reported profit of $1.69 per share on revenue of $11.97 billion for the quarter, both better than Wall Street estimates.

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THIS IS A TERRIFYING SERVICE: IT KNOWS WHERE I HAVE BEEN LITERALLY SINCE 2014; WE CONSENT TO THIS; INCREDIBLY IRONIC PHRASING WHEN YOU TRY ACCESSING

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wow the clearest example of surveillance capitalism manifesting! companies using cookies to increase pricing!

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Even rocket scientists, I would wager, are befuddled by airline pricing. One minute, a flight you're looking at costs £400; 30 seconds later it has increased by £100. Panic sets in; you buy a ticket before it ascends out of your price range.

I experienced this fluctuation frustration recently while trying to buy a ticket home to London from New York for Christmas. After about a gazillion visits to British Airways' website, I decided finally to book something. Immediately, the price went up. That's OK, I thought, trying to console myself. I read on Twitter that London has gone all Islamic anyway and Christmas has been banned. Probably nothing to go home to any more, just ritual stonings and sharia. Then I remembered a rumour that clearing your browser cookies could get you a cheaper flight. I gave it a go and, voila, the flight reverted to its earlier, cheaper price.

The thinking behind the cookies trick is that airlines can tell from your browser history when you're particularly interested in a flight - and thus willing to pay a higher price - and take advantage of this. Whether this is true is known only to a few (when the Guardian asked BA about this in 2010, it said it didn't use cookies in this way). What is clear, however, is that airlines - and many other companies - are increasingly moving towards "personalised pricing". Sometimes called "differential pricing" or "price discrimination", this means charging customers different prices for the same product based on how much they think people are willing to pay.

Price discrimination, to be clear, is not the same as "dynamic pricing". Airlines have practised dynamic pricing for a long time: there are a set number of prices available, and you get a different fare based on factors including when you book and the availability of seats on the flight. Prices, however, are starting to get more personal. In 2014, a US regulator approved an industry-wide system, the implementation of which started only recently, that allows airlines and travel agencies to collect personal data - information such as marital status, address and travel history - and use that data to offer you "more agile pricing and more personalised offerings". So, if an airline can see that you live in a fancy neighbourhood and regularly fly business-class, it may offer you a higher fare than it would someone whom it believes is more price-sensitive. As technology grows more sophisticated, companies may be able to serve you higher prices based on factors such as your emotional state.

Businesses are already using customised pricing online based on information they can glean about you. It is hard to know how widespread the practice is; companies keep their pricing strategies closely guarded and are wary of the bad PR price discrimination could pose. However, it is clear that a number of large retailers are experimenting with it. Staples, for example, has offered discounted prices based on whether rival stores are within 20 miles of its customers' location. Office Depot has admitted to using its customers' browsing history and location to vary its range of offers and products. A 2014 study from Northeastern University found evidence of "steering" or differential pricing at four out of 10 general merchandise websites and five out of five travel websites. (Steering is when a company doesn't give you a customised price, but points you towards more expensive options if it thinks you will pay more.) The online travel company Orbitz raised headlines in 2012 when it emerged that the firm was pointing Mac users towards higher-priced hotel rooms than PC users.

Price discrimination doesn't happen only online. Supermarkets have used personalised pricing based on information gleaned from loyalty cards and shopping habits. Broadly speaking, economists tend to think of price discrimination as a good thing for businesses and customers. Essentially, it is algorithms robbing from the rich to subsidise the poor, all while growing a company's market.

There is the potential for this to go further still and for customised pricing to help reduce some of the inequities in society. In Finland, speeding tickets are linked to income, a system known as progressive punishment. Could we not have progressive pricing, a system where the cost of necessities such as bread and milk is linked to your ability to pay for them?

However, it seems more likely that companies will exploit the increasing amounts of data they have about us to our detriment. Take Uber, for example. Its much-hated "surge pricing" is an example of dynamic pricing: prices change according to supply and demand. They don't change according to how desperate you, as an individual, are to get a cab, but this may not be the case for long. Uber knows a hell of a lot about you - including, for example, how low the battery is on your phone. It also has data that shows people are more likely to pay surge pricing when their phone battery is low. "We absolutely don't use that ... but it's an interesting kind of psychological fact of human behaviour," a behavioural economist at Uber said earlier this year. This may be true, but why do you think Uber employs behavioural economists? It is not simply to marvel at the psychology of human behaviour.

As airlines become more adept at gathering and exploiting data, I shudder to think what "interesting facts" of human behaviour they will start to factor into their pricing strategies. Fares will stop being linked to variables such as seats already sold and start fluctuating according to how many times your mum has texted you to ask if you've bought your ticket yet, and how guilty you feel that you haven't. Good luck trying to clear your cookies to fix that.
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Cookie monsters: why your browsing history could mean rip-off prices | Arwa Mahdawi

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Even rocket scientists, I would wager, are befuddled by airline pricing. One minute, a flight you're looking at costs £400; 30 seconds later it has increased by £100. Panic sets in; you buy a ticket before it ascends out of your price range.

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I'VE BEEN PWNED

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this is MESSED UP??? france is developing a whatsapp rival BECAUSE whatsapp encrypts its messages so it cant spy on officials/the public? WHAT

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The French government is building its own encrypted messenger service to ease fears that foreign entities could spy on private conversations between top officials, the digital ministry said on Monday.

None of the world's major encrypted messaging apps, including Facebook's WhatsApp and Telegram - a favourite of President Emmanuel Macron - are based in France, raising the risk of data breaches at servers outside the country.

About 20 officials and top civil servants are testing the new app which a state-employed developer has designed, a ministry spokewoman said, with the aim that its use will become mandatory for the whole government by the summer.

"We need to find a way to have an encrypted messaging service that is not encrypted by the United States or Russia," the spokeswoman said. "You start thinking about the potential breaches that could happen, as we saw with Facebook, so we should take the lead."

The US social network, which bought WhatsApp in 2014, has drawn heavy criticism since it acknowledged that information about many millions of users wrongly ended up in the hands of political consultancy Cambridge Analytica.

The French government's encrypted app has been developed on the basis of free-to-use code found on the Internet and could be eventually made available to all citizens, the spokeswoman said. She declined to give the names of either the codes or the messaging service.

Fond of Telegram
Macron's inner circle - now government advisers or ministers - have grown fond of the Telegram app, which they used to plot his rise to power and his presidential election campaign last year.

Macron, an economy minister in the previous Socialist administration, wanted at the time to use an encrypted messaging service that even his rivals in the last government could not crack, a close adviser to Macron told Reuters.

Since then, most of his lawmakers have joined the app and the president himself can often be seen online on Telegram, sometimes in the early hours of the morning.

But privacy concerns started growing earlier this year, and security tools from French security firm Thales installed on officials' work smartphones prevented the use of either WhatsApp or Telegram.

Telegram was set up by a Russian entrepreneur who has come into conflict with the authorities. Russia's state telecommunications regulator said on Monday it had begun blocking access to Telegram after the company refused to comply with an order to give state security access to its users' secret messages.

Both WhatsApp and Telegram promote themselves as ultra-secure because all their data is encrypted from start to finish. WhatsApp relies on open industry standards created by the developers behind Signal, a rival messaging app, while Telegram relies on its own, home-grown encryption techniques.
© Thomson Reuters 2018

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france whatsapp rival app telegram not encrypted by the united states or russia apps

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France Is Building a WhatsApp Rival Due to Surveillance Risk

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The French government is building its own encrypted messenger service to ease fears that foreign entities could spy on private conversations between top officials, the digital ministry said on Monday. None of the world's major encrypted messaging apps, including Facebook's WhatsApp and Telegram - a favourite of President Emmanuel Macron - are based in France, raising the risk of data breaches at servers outside the country.

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Despite the fact that for the most of their lives smartphones have been an extension of their very selves, Generation Z, like their older millennial cousins, love stores and cherish experiences - they even use bank branches more often than Baby Boomers. This sounds like a throw-back, an affinity for the vintage. So how many younger consumers are likely to pay with digital wallets?

Probably more than most retailers are prepared for.

"Do I think cash is dead? No," said Peter Caparso, Checkout.com's president of North America. "Do I think it'll be greatly diminished? Yes. Until 2007, after the invention of the phone in 1876, you were tethered to a five-foot semi-circle to talk. Now this younger generation, they're used to the convenience and the portability of the phone, and that's translating to the retail arena."

Mobile payments have had a bumpy road to adoption, in part thanks to misconceptions about how they would evolve. A few years ago, for example, Apple Pay seemed poised to take the crown in what was deemed a winner-takes-all race to become a "universal wallet." That helped fuel an ill-conceived effort by a worried group of retailers, (led by Walmart but joined by several of its rivals), to block Apple Pay and come up with their own digital wallet. That attempt, CurrentC, went down in flames before it ever got off the ground.

But even Apple Pay has lagged behind predictions. As digital payment adoption failed to follow a certain upward trajectory, it began to seem that a critical mass of consumers just really prefer plastic cards. That has been a misunderstanding of how payment methods develop​ and has interfered with retailers' need to invest, said Ralph Dangelmaier, CEO of BlueSnap.

"It takes five to seven years for something to take hold, no matter what it is," he told Retail Dive in an interview. "Everyone is too bullish in the beginning and too bearish in the middle. The Gen Z's want to bank on Apple, Venmo and the rest. Four years from now, or maybe three, half of payments will be on [big players like] PayPal, Apple Pay, mobile Visa Checkout and now this new one, W3. The browser will be a wallet. The 'buy now' button, that's going to be smoking hot, I think."

A few years into the digital payment evolution, things are finally picking up speed, according to Bluesnap data. From the fourth quarter last year to the first quarter of 2018, wallet payment spend rose 114%, the number of transactions has increased 38% and average ticket size is up 55%. That's evidence of four important factors, Dangelmaier said: there's greater acceptance, shoppers are more comfortable, they're having a better checkout experience, and there are more repeat purchases.

​Smooth, smart and secure

When it comes to the ease and expectation of mobile payments, it's not so much that younger consumers, both millennials and Gen Z, have an easier time adapting to new tech and payment methods. It's more that the phone is simply their portal to the world​. There's just no reason to have paper dollars or even plastic cards taking up space in a (physical) wallet when it's all on their phone.

Credit cards, and even checks, were earlier replacements for cold hard cash, but they can't compare to the zippy, app-based money transactions possible on mobile and the web. That doesn't mean, however, that spending for younger consumers is notional. For Gen Z, who are still under the age of 21 and even in some cases in preschool, that means paying for things like sharing a pizza with friends. Meanwhile millennials, some of whom have entered their 40s, are looking at purchases like cars and homes.

But even with the recession well in the rear view, the economy chugging along and, for many, their earning potential realized, millennials remain loathe to over-spend, Caparso said. More younger consumers are also opting for longer-term financing and rejecting the stiffer terms of most traditional credit cards.

"Millennials are more likely to use the credit card in order to build up their credit rating and not for day to day living," he said. "Growing up during the Great Recession, has given them, definitely it seems to me, a reluctance."

And while some adults think of Gen Z as unable to get off their phones, their digital nativism actually leads them to feel very much in control of their devices, according to Jane Cheung, global leader for consumer products for the IBM Institute for Business Value and leader of an IBM study on Gen Z for the National Retail Federation.

"They don't think about 'on or 'off,'" she explained in an interview with Retail Dive last year. "But according to our data, this generation is very smart. Their top three criteria in order to feel comfortable giving personal information is they need to know the data is protected, they want to know the terms and conditions and they want to know how retailers are collecting the information."

What retailers should do

Almost 2.1 billion consumers worldwide are expected to use mobile wallets for payments or money transfers by next year, representing growth of almost 30% over the 1.6 billion consumers who used mobile wallets last year, according to Juniper Research. Yet too many retailers aren't ready for the wallet-based payments that their customers will increasingly want to use.

It's not a world where the kind of exclusivity pursued by CurrentC will fly or even the more accepted practice of taking some charge cards but not others. The good news is, digital wallets don't come with the kind of transaction fees that retailers now face from banks, according to Dangelmaier. In fact, while it's "a huge benefit to the shopper, what the retailers don't get is that it doesn't cost more, despite what most people think," he said, noting that fees are paid by the issuer, not the merchant.

It's not that there won't be winners and losers, but retailers needn't have a dog in that fight, Caparso says. "There are a ton of wallet methods out there - it's like alphabet soup," he said. "If you're working with a provider that has the full portfolio - you're allowing yourself to maximize all the potential deals. I do think with the younger generation, some wallet methods will win out over others. You want to be able to have the flexibility to accommodate this younger demographic."

Dangelmaier agrees, adding that retailers do have some say in how well they'll fare as cash fades and the digital wallet rises. "The Z's and the millennials, no brainer. The X's and the Baby Boomers are in. The banks are going to do well. The loser is the guy printing money - check printing companies, ATM machines," he said. "And merchants that don't get on board because they're reading that it's not really a trend yet, they're just wrong, and they'll lose sales."

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Despite the fact that for the most of their lives smartphones have been an extension of their very selves, Generation Z, like their older millennial cousins, love stores and cherish experiences - they even use bank branches more often than Baby Boomers. This sounds like a throw-back, an affinity for the vintage.

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Opinion | Chinese Tech Companies' Dirty Secret

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"Finding a job = finding a woman." Chinese tech companies use female employees as bait to recruit male applicants.

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"If I’m not paying for Facebook, am I the product?

No. Our product is social media"

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By Rob Goldman, Vice President, Ads
To build a product that connects people across continents and cultures, we need to make sure everyone can afford it. Advertising lets us keep Facebook free. But we aren't blind to the challenges this model poses. It requires a steadfast commitment to privacy.

So our promise is this: we do not tell advertisers who you are or sell your information to anyone. That has always been true. We think relevant advertising and privacy aren't in conflict, and we're committed to doing both well.

We know that many of you have questions about how we use your information in advertising - and what control you have over it. I'll address some of the most frequent questions we get, but first I'll lay out the basic mechanics of Facebook advertising.

There are a few ways that advertisers can reach you with ads on Facebook:

1. Information from your use of Facebook. When you use Facebook, you can choose to share things about yourself like your age, gender, hometown, or friends. You can also click or like posts, Pages, or articles. We use this information to understand what you might be interested in and hopefully show you ads that are relevant. If a bike shop comes to Facebook wanting to reach female cyclists in Atlanta, we can show their ad to women in Atlanta who liked a Page about bikes. But here's what's key: these businesses don't know who you are. We provide advertisers with reports about the kinds of people seeing their ads and how their ads are performing, but we don't share information that personally identifies you. You can always see the 'interests' assigned to you in your ad preferences, and if you want, remove them.

2. Information that an advertiser shares with us. In this case, advertisers bring us the customer information so they can reach those people on Facebook. These advertisers might have your email address from a purchase you made, or from some other data source. We find Facebook accounts that match that data, but we don't tell the advertiser who matched. In ad preferences you can see which advertisers with your contact information are currently running campaigns - and you can click the top right corner of any ad to hide all ads from that business.

3. Information that websites and apps send to Facebook.Some of the websites and apps you visit may use Facebook tools to make their content and ads more relevant and better understand the results of their ad campaigns. For example, if an online retailer is using Facebook Pixel, they can ask Facebook to show ads to people who looked at a certain style of shoe or put a pair of shoes into their shopping cart. If you don't want this data used to show you ads, you can turn it off in ad preferences. My colleague David Baser shared more detail about how we, and others in the industry, use this information in a post earlier this week.

Now for some of the questions we hear most frequently around our advertising practices:
If I'm not paying for Facebook, am I the product?
No. Our product is social media - the ability to connect with the people that matter to you, wherever they are in the world. It's the same with a free search engine, website or newspaper. The core product is reading the news or finding information - and the ads exist to fund that experience.
If you're not selling advertisers my data, what are you giving them?
We sell advertisers space on Facebook - much like TV or radio or newspapers do. We don't sell your information. When an advertiser runs a campaign on Facebook, we share reports about the performance of their ad campaign. We could, for example, tell an advertiser that more men than women responded to their ad, and that most people clicked on the ad from their phone.
Why does Facebook need all this data?

As people use Facebook, they share information and content - whether it's liking a post, sharing a photo or updating their profile. We use this information to give you a better service. For example, we can show you photos from your closest friends at the top of your News Feed, or show you articles about issues that matter most to you, or suggest groups that you might want to join.

Data also helps us show you better and more relevant ads. And it lets advertisers reach the right people, including millions of small businesses and non-profits who rely on Facebook every day to reach people that might be interested in their product or cause. Data lets a local coffee shop survive and grow amid larger competitors by showing ads to customers in its area. And it lets a non-profit promote a diabetes fundraiser to those interested in the cause.
What if I don't want my data used to show me ads?
You can't opt out of ads altogether because ads are what keep Facebook free, but you do have different options to control how your data can and can't be used to show you ads. They're all found in ad preferences.

You can decide which of your profile fields you want used for ad targeting in the Information section under "About You." You can remove yourself from interests under "Interests" and categories under "Your Categories." You can turn off ads that use data from apps or websites that you visit in the Ads Settings section under "Ads based on use of websites and apps."

-

Digital advertising is relatively new and has radically changed since the early days of banner ads on the top of a website. But the promise of digital advertising is that it can show you ads for products, services, and causes that may actually be of interest to you. And for small businesses, it levels the playing field and lets them reach an audience that they never could have before. You get better ads, advertisers get a tailored audience and everyone on Facebook gets our firm commitment to privacy.
Downloads: Infographic: Make Facebook Your Facebook

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Hard Questions: What Information Do Facebook Advertisers Know About Me?

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By Rob Goldman, Vice President, Ads To build a product that connects people across continents and cultures, we need to make sure everyone can afford it. Advertising lets us keep Facebook free. But we aren't blind to the challenges this model poses. It requires a steadfast commitment to privacy.

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Facebook's CEO spent five hours on Tuesday alternately answering and deflecting questions about user privacy and how the social network handles your data.

Hear, hear: Zuckerberg's testimony before a joint hearing of the Senate Commerce, Science, and Transportation and Senate Judiciary committees was sparked by the revelation weeks ago that Facebook is at the center massive data scandal.

The background: It was revealed in March that millions of its users' information was shared with Cambridge Analytica-a firm that provided data to President Trump's election campaign in 2016. Facebook now estimates that many as 87 million users were affected.

This is just the latest in a string of data privacy-related issues the world's largest social network is dealing with.

What happened in Washington: In a room packed with politicians, reporters, photographers, and some sign-wielding protesters, Zuckerberg first read from prepared testimony, noting several of the things Facebook is doing to address data privacy problems and prevent abuses like Cambridge Analytica's from happening again, such as further limiting developers' access to users' information.

He then spent hours answering senators' questions, including one from Kamala Harris of California about why Facebook didn't let users know about issues related to Cambridge Analytica back in 2015 (which is when it originally learned that the company had bought data from a researcher and demanded it be deleted-though it's now clear that's not what ended up happening). Zuckerberg wouldn't say whether Facebook made a clear decision not to inform users but said that, looking back, the company screwed up in how it handled the situation. (See also " Facebook may stop the data leaks, but it's too late: Cambridge Analytica's models live on.")

In response to many of the questions, rather than offering immediate answers Zuckerberg said he'd have his "team" get back to senators with details.

A few interesting points: in a response to a question by Vermont senator Patrick Leahy, Zuckerberg said Facebook is cooperating with special counsel Robert Mueller's investigation into Russian interference in the 2016 US presidential election.

He also said that while Facebook is beefing up its use of AI to spot and remove offensive content, it will be five to 10 years before the company will have tools to do this automatically.

Many senators seemed unsure about how Facebook works-for instance, Zuckerberg had to say several times that Facebook doesn't share or sell user data to advertisers (rather, it allows advertisers to tell it what kinds of users they want to target on Facebook). This lack of understanding points to a broader problem the company has long struggled to address: many of its users are simply not as tech-savvy (or Facebook-savvy) as those behind the social network.

What's next: This was the first of two hearings on Zuckerberg's schedule. On Wednesday, he will speak before the House Energy and Commerce Committee; you can watch at the committee's website.

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Well-rehearsed, evasive Mark Zuckerberg tries to explain Facebook user privacy to Congress

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Facebook's CEO spent five hours on Tuesday alternately answering and deflecting questions about user privacy and how the social network handles your data. Hear, hear: Zuckerberg's testimony before a joint hearing of the Senate Commerce, Science, and Transportation and Senate Judiciary committees was sparked by the revelation weeks ago that Facebook is at the center massive data scandal.

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Committee Chairman

The Chairman of the Committee, Lord Clement-Jones, said:

"The UK has a unique opportunity to shape AI positively for the public's benefit and to lead the international community in AI's ethical development, rather than passively accept its consequences.

"The UK contains leading AI companies, a dynamic academic research culture, and a vigorous start-up ecosystem as well as a host of legal, ethical, financial and linguistic strengths. We should make the most of this environment, but it is essential that ethics take centre stage in AI's development and use.

"AI is not without its risks and the adoption of the principles proposed by the Committee will help to mitigate these. An ethical approach ensures the public trusts this technology and sees the benefits of using it. It will also prepare them to challenge its misuse.

"We want to make sure that this country remains a cutting-edge place to research and develop this exciting technology. However, start-ups can struggle to scale up on their own. Our recommendations for a growth fund for SMEs and changes to the immigration system will help to do this.

"We've asked whether the UK is ready willing and able to take advantage of AI. With our recommendations, it will be."

AI Code

One of the recommendations of the report is for a cross-sector AI Code to be established, which can be adopted nationally, and internationally. The Committee's suggested five principles for such a code are:

1. Artificial intelligence should be developed for the common good and benefit of humanity.

2. Artificial intelligence should operate on principles of intelligibility and fairness.

3. Artificial intelligence should not be used to diminish the data rights or privacy of individuals, families or communities.

4. All citizens should have the right to be educated to enable them to flourish mentally, emotionally and economically alongside artificial intelligence.

5. The autonomous power to hurt, destroy or deceive human beings should never be vested in artificial intelligence.

Recommendations included in the report

Other conclusions from the report include:

Many jobs will be enhanced by AI, many will disappear and many new, as yet unknown jobs, will be created. Significant Government investment in skills and training will be necessary to mitigate the negative effects of AI. Retraining will become a lifelong necessity.

Individuals need to be able to have greater personal control over their data, and the way in which it is used. The ways in which data is gathered and accessed needs to change, so that everyone can have fair and reasonable access to data, while citizens and consumers can protect their privacy and personal agency. This means using established concepts, such as open data, ethics advisory boards and data protection legislation, and developing new frameworks and mechanisms, such as data portability and data trusts.

The monopolisation of data by big technology companies must be avoided, and greater competition is required. The Government, with the Competition and Markets Authority, must review the use of data by large technology companies operating in the UK.

The prejudices of the past must not be unwittingly built into automated systems. The Government should incentivise the development of new approaches to the auditing of datasets used in AI, and also to encourage greater diversity in the training and recruitment of AI specialists.

Transparency in AI is needed. The industry, through the AI Council, should establish a voluntary mechanism to inform consumers when AI is being used to make significant or sensitive decisions.

At earlier stages of education, children need to be adequately prepared for working with, and using, AI. The ethical design and use of AI should become an integral part of the curriculum.

The Government should be bold and use targeted procurement to provide a boost to AI development and deployment. It could encourage the development of solutions to public policy challenges through speculative investment. There have been impressive advances in AI for healthcare, which the NHS should capitalise on.

It is not currently clear whether existing liability law will be sufficient when AI systems malfunction or cause harm to users, and clarity in this area is needed. The Committee recommend that the Law Commission investigate this issue.

The Government needs to draw up a national policy framework, in lockstep with the Industrial Strategy, to ensure the coordination and successful delivery of AI policy in the UK.

Further information

Image: iStockphoto

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UK can lead the way on ethical AI, says Lords Committee - News from Parliament

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The Chairman of the Committee, Lord Clement-Jones, said: "The UK has a unique opportunity to shape AI positively for the public's benefit and to lead the international community in AI's ethical development, rather than passively accept its consequences.

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"The Trump Show," which has produced two seasons' worth of epic cliffhangers and plot twists, is getting a competitor: "The Comey Show," which is scheduled to run for at least five weeks, and will needle and gall President Trump amid global, legal and political crises.

Why it matters: In both his prime-time interview with ABC's George Stephanopoulos and an interview with USA Today, fired FBI Director James Comey argued that Trump is "morally unfit to be president," making it clear that, like a skilled political candidate, he'll be repeating a specific message with fervor and discipline on a coast-to-coast book tour that includes a saturation schedule of interviews and audience events.

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Pentagon cloud plan favors Amazon, rivals say

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"The Trump Show," which has produced two seasons' worth of epic cliffhangers and plot twists, is getting a competitor: "The Comey Show," which is scheduled to run for at least five weeks, and will needle and gall President Trump amid global, legal and political crises.

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BERLIN - Think lawsuits involving humans are tricky? Try taking an intelligent robot to court.

While autonomous robots with humanlike, all-encompassing capabilities are still decades away, European lawmakers, legal experts and manufacturers are already locked in a high-stakes debate about their legal status: whether it's these machines or human beings who should bear ultimate responsibility for their actions.

The battle goes back to a paragraph of text, buried deep in a European Parliament report from early 2017, which suggests that self-learning robots could be granted "electronic personalities." Such a status could allow robots to be insured individually and be held liable for damages if they go rogue and start hurting people or damaging property.

Those pushing for such a legal change, including some manufacturers and their affiliates, say the proposal is common sense. Legal personhood would not make robots virtual people who can get married and benefit from human rights, they say; it would merely put them on par with corporations, which already have status as "legal persons," and are treated as such by courts around the world.

But as robots and artificial intelligence become hot-button political issues on both sides of the Atlantic, MEP and vice chair of the European Parliament's legal affairs committee, Mady Delvaux, and other proponents of legal changes face stiffening opposition. In a letter to the European Commission seen by POLITICO and expected to be unveiled Thursday, 156 artificial intelligence experts hailing from 14 European countries, including computer scientists, law professors and CEOs, warn that granting robots legal personhood would be "inappropriate" from a "legal and ethical perspective."

By seeking legal personhood for robots, manufacturers were merely trying to absolve themselves of responsibility for the actions of their machines - Noel Sharkey, emeritus professor of artificial intelligence and robotics at the University of Sheffield

The report from the Parliament's legal affairs committee recommended the idea of giving robots "electronic personalities," and could become a model for laws across Europe if turned into regulatory framework. Delvaux said that while she was not sure that legally defining robots as personalities was a good idea, she was "more and more convinced" that current legislation was insufficient to deal with complex issues surrounding liability and self-learning machines and that all options should be put on the table.

The AI experts behind the letter to the European Commission strongly disagree.

"By adopting legal personhood, we are going to erase the responsibility of manufacturers," said Nathalie Navejans, a French law professor at the Université d'Artois, who was the driving force behind the letter.

Noel Sharkey, emeritus professor of artificial intelligence and robotics at the University of Sheffield, who also signed on, added that by seeking legal personhood for robots, manufacturers were merely trying to absolve themselves of responsibility for the actions of their machines.

"This [European Parliament position] was what I'd call a slimy way of manufacturers getting out of their responsibility," he said.

'Black box' robots

As each side turns up the volume on its advocacy, one thing is clear: Money is pouring into the field of robotics, and the debate is set to turn louder.

In coming years, analysts predict the gold rush into emerging fields is only set to accelerate. The market for consumer robots, for instance - machines acting as companions in the household - is expected to almost triple within the next five years, from $5.4 billion in 2018 to $14.9 billion by 2023.

Sales of "cobots" - machines designed to work alongside humans - are forecast as increasing almost thirtyfold, from just over $100 million in 2015 to $3 billion 2020.

And the market for industrial robots - machines that can, for example, put together cars or perform sophisticated assembly line tasks - is expected to balloon as well, reaching $40 billion by 2020, compared to $25.7 billion in 2013.

The current boom has to do with the fact that robots just entered the second stage of their evolution, 59 years after the first industrial robot joined the assembly line of American General Motors factories.

In the decades that followed, machines remained largely reactive, programmed to complete defined tasks and react to a limited number of situations.

The idea behind coming up with an electronic personality was not about giving human rights to robots - but to make sure that a robot is and will remain a machine with a human backing it.

The latest developments, by contrast, enable machines to fulfill tasks that previously required human thinking. Current state-of-the-art technology allows computers to learn and make their own decisions by mimicking and proliferating human brain patterns.

The concern of lawmakers: Will such complex processes turn machines into " black boxes " whose decision-making processes are difficult or even impossible to understand, and therefore impenetrable for litigators seeking to attribute legal responsibility for problems?

Can robots marry?

That's why, advocates argue, Europe should grant "legal status" to the robots themselves, rather than burden their manufacturers or owners.

"In a scenario where an algorithm can take autonomous decision, then who should be responsible for these decisions?" Milan-based corporate lawyer Stefania Lucchetti said.

The current model, in which either the manufacturer, the owner, or both are liable, would become defunct in an age of fully autonomous robots, and the EU should give robots some sort of legal personality "like companies have," she added.

The "personality" she referred to is a concept that dates back to the 13th century, when Pope Innocent IV granted personhood status to monasteries. Today, virtually every country of the world applies the model to companies, which means that corporations have some of the legal rights and responsibilities of a human being, including being able to sign a contract or being sued. A similar legal model for robots, its advocates argue, would be less about giving rights to robots and rather about holding them responsible when things go wrong, for example by setting up a compulsory insurance scheme that could be fed by the wealth a robot is accumulating over the time of its "existence."

"This doesn't mean the robot is self-conscious, or can marry another robot," Lucchetti said.

Along similar lines, Delvaux stressed that the idea behind coming up with an electronic personality was not about giving human rights to robots - but to make sure that a robot is and will remain a machine with a human backing it.

Beyond Sophia

The controversy swirling around futuristic robots masks the reality that robots capable of human-like intelligence and decision-making remain a far-off prospect.

Today's robots are better than humans at some narrow applications, such as recognizing images, or playing the Chinese board game Go.

"I don't mind the idea of a show robot at all. But when they start bringing it to the U.N. and giving nations the wrong idea of what robotics can do and where AI is at the moment it's very, very dangerous" - Noel Sharkey

But such state-of-the-art applications excel only in one narrow field. Playing Go, or categorizing images, are essentially the only things such machines can do, unlike human beings, who can at the same time understand language, learn to play a variety of board games and recognize images.

Even so, media reports about galloping advances in robotics - which may suggest all-encompassing robot intelligence is within reach - have infiltrated public debate. That may lead lawmakers to rush into premature regulation, the signatories of the letter warn.

According to some researchers, no robot has done as much to convey false notions about robotics as Sophia: a humanoid robot that made its first appearance in March 2016 and has since then become a Saudi Arabian citizen, was given a title from the United Nations and opened the Munich Security Conference this year.

"I don't mind the idea of a show robot at all," said Sharkey, who co-signed the letter and is also co-founder of the Foundation for Responsible Robotics. "But when they start bringing it to the U.N. and giving nations the wrong idea of what robotics can do and where AI is at the moment it's very, very dangerous."

He added: "It's very dangerous for lawmakers as well. They see this and they believe it, because they're not engineers and there is no reason not to believe it."

Instead, the EU's existing civil law rules are sufficient to address questions of liability, the 156 AI experts argue in their open letter.

Delvaux said the Parliament's discussion about a full electronic personality is ongoing, and that "maybe at the end of the day, we'll come to the conclusion that it is not a good idea."

Her primary goal when suggesting legal personhood for robots was to raise a public debate about the issue, she said.

In that sense, she succeeded.

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BERLIN - Think lawsuits involving humans are tricky? Try taking an intelligent robot to court. While autonomous robots with humanlike, all-encompassing capabilities are still decades away, European lawmakers, legal experts and manufacturers are already locked in a high-stakes debate about their legal status: whether it's these machines or human beings who should bear ultimate responsibility for their actions.

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About halfway through a particularly tense game of Go held in Seoul, South Korea, between Lee Sedol, one of the best players of all time, and AlphaGo, an artificial intelligence created by Google, the AI program made a mysterious move that demonstrated an unnerving edge over its human opponent.

On move 37, AlphaGo chose to put a black stone in what seemed, at first, like a ridiculous position. It looked certain to give up substantial territory-a rookie mistake in a game that is all about controlling the space on the board. Two television commentators wondered if they had misread the move or if the machine had malfunctioned somehow. In fact, contrary to any conventional wisdom, move 37 would enable AlphaGo to build a formidable foundation in the center of the board. The Google program had effectively won the game using a move that no human would've come up with.

About the art

One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words. In the images that accompany this story, several artists demonstrate the use of a variety of visual clues to convey meanings far beyond the actual letters.

See the rest of the issue
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AlphaGo's victory is particularly impressive because the ancient game of Go is often looked at as a test of intuitive intelligence. The rules are quite simple. Two players take turns putting black or white stones at the intersection of horizontal and vertical lines on a board, trying to surround their opponent's pieces and remove them from play. Playing well, however, is incredibly hard.

Whereas chess players are able to look a few moves ahead, in Go this isn't possible without the game unfolding into intractable complexity, and there are no classic gambits. There is also no straightforward way to measure advantage, and it can be hard for even an expert player to explain precisely why he or she made a particular move. This makes it impossible to write a simple set of rules for an expert-level computer program to follow.

AlphaGo wasn't told how to play Go at all. Instead, the program analyzed hundreds of thousands of games and played millions of matches against itself. Among several AI techniques, it used an increasingly popular method known as deep learning, which involves mathematical calculations inspired, very loosely, by the way interconnected layers of neurons fire in a brain as it learns to make sense of new information. The program taught itself through hours of practice, gradually honing an intuitive sense of strategy. That it was then able to beat one of the world's best Go players represents a true milestone in machine intelligence and AI.

A few hours after move 37, AlphaGo won the game to go up two games to nothing in the best-of-five match. Afterward Sedol stood before a crowd of journalists and photographers, politely apologizing for letting humankind down. "I am quite speechless," he said, blinking through a storm of flash photography.

AlphaGo's surprising success points to just how much progress has been made in artificial intelligence over the last few years, after decades of frustration and setbacks often described as an "AI winter." Deep learning means that machines can increasingly teach themselves how to perform complex tasks that only a couple of years ago were thought to require the unique intelligence of humans. Self-driving cars are already a foreseeable possibility. In the near future, systems based on deep learning will help diagnose diseases and recommend treatments.

Deep learning means that machines can increasingly teach themselves how to perform complex tasks that only a couple of years ago were thought to require the unique intelligence of humans.

Yet despite these impressive advances, one fundamental capability remains elusive: language. Systems like Siri and IBM's Watson can follow simple spoken or typed commands and answer basic questions, but they can't hold a conversation and have no real understanding of the words they use. If AI is to be truly transformative, this must change.

Even though AlphaGo cannot speak, it contains technology that might lead to greater language understanding. At companies such as Google, Facebook, and Amazon, as well as at leading academic AI labs, researchers are attempting to finally solve that seemingly intractable problem, using some of the same AI tools-including deep learning-that are responsible for AlphaGo's success and today's AI revival. Whether they succeed will determine the scale and character of what is turning into an artificial-intelligence revolution. It will help determine whether we have machines we can easily communicate with-machines that become an intimate part of our everyday life-or whether AI systems remain mysterious black boxes, even as they become more autonomous. "There's no way you can have an AI system that's humanlike that doesn't have language at the heart of it," says Josh Tenenbaum, a professor of cognitive science and computation at MIT. "It's one of the most obvious things that set human intelligence apart."

Perhaps the same techniques that let AlphaGo conquer Go will finally enable computers to master language, or perhaps something else will also be required. But without language understanding, the impact of AI will be different. Of course, we can still have immensely powerful and intelligent software like AlphaGo. But our relationship with AI may be far less collaborative and perhaps far less friendly. "A nagging question since the beginning was 'What if you had things that were intelligent in the sense of being effective, but not like us in the sense of not empathizing with what we are?'" says Terry Winograd, a professor emeritus at Stanford University. "You can imagine machines that are not based on human intelligence, which are based on this big-data stuff, and which run the world."
Machine whisperers
A couple of months after AlphaGo's triumph, I traveled to Silicon Valley, the heart of the latest boom in artificial intelligence. I wanted to visit the researchers who are making remarkable progress on practical applications of AI and who are now trying to give machines greater understanding of language.

I started with Winograd, who lives in a suburb nestled into the southern edge of Stanford's campus in Palo Alto, not far from the headquarters of Google, Facebook, and Apple. With curly white hair and a bushy mustache, he looks the part of a venerable academic, and he has an infectious enthusiasm.

Back in 1968, Winograd made one of the earliest efforts to teach a machine to talk intelligently. A math prodigy fascinated with language, he had come to MIT's new AI lab to study for his PhD, and he decided to build a program that would converse with people, via a text prompt, using everyday language. It didn't seem an outlandish ambition at the time. Incredible strides were being made in AI, and others at MIT were building complex computer vision systems and futuristic robot arms. "There was a sense of unknown, unbounded possibilities," he recalls.

Not everyone was convinced that language could be so easily mastered, though. Some critics, including the influential linguist and MIT professor Noam Chomsky, felt that the AI researchers would struggle to get machines to understand, given that the mechanics of language in humans were so poorly understood. Winograd remembers attending a party where a student of Chomsky's walked away when he heard him say that he worked in the AI lab.

But there was reason to be optimistic, too. Joseph Weizenbaum, a German-born professor at MIT, had built the very first chatbot program a couple of years earlier. Called ELIZA, it was programmed to act like a cartoon psychotherapist, repeating key parts of a statement or asking questions to encourage further conversation. If you told the program you were angry at your mother, for instance, it would say, "What else comes to mind when you think about your mother?" A cheap trick, but it worked surprisingly well. Weizenbaum was shocked when some subjects began confessing their darkest secrets to his machine.

There's an obvious problem with applying deep learning to language. It's that words are arbitrary symbols, and as such they are fundamentally different from imagery.

Winograd wanted to create something that really seemed to understand language. He began by reducing the scope of the problem. He created a simple virtual environment, a "block world," consisting of a handful of imaginary objects sitting on an imaginary table. Then he created a program, which he named SHRDLU , that was capable of parsing all the nouns, verbs, and simple rules of grammar needed to refer to this stripped-down virtual world. SHRDLU (a nonsense word formed by the second column of keys on a Linotype machine) could describe the objects, answer questions about their relationships, and make changes to the block world in response to typed commands. It even had a kind of memory, so that if you told it to move "the red cone" and then later referred to "the cone," it would assume you meant the red one rather than one of another color.

SHRDLU was held up as a sign that the field of AI was making profound progress. But it was just an illusion. When Winograd tried to make the program's block world larger, the rules required to account for the necessary words and grammatical complexity became unmanageable. Just a few years later, he had given up, and eventually he abandoned AI altogether to focus on other areas of research. "The limitations were a lot closer than it seemed at the time," he says.

Winograd concluded that it would be impossible to give machines true language understanding using the tools available then. The problem, as Hubert Dreyfus, a professor of philosophy at UC Berkeley, argued in a 1972 book called What Computers Can't Do, is that many things humans do require a kind of instinctive intelligence that cannot be captured with hard-and-fast rules. This is precisely why, before the match between Sedol and AlphaGo, many experts were dubious that machines would master Go.

But even as Dreyfus was making that argument, a few researchers were, in fact, developing an approach that would eventually give machines this kind of intelligence. Taking loose inspiration from neuroscience, they were experimenting with artificial neural networks-layers of mathematically simulated neurons that could be trained to fire in response to certain inputs. To begin with, these systems were painfully slow, and the approach was dismissed as impractical for logic and reasoning. Crucially, though, neural networks could learn to do things that couldn't be hand-coded, and later this would prove useful for simple tasks such as recognizing handwritten characters, a skill that was commercialized in the 1990s for reading the numbers on checks . Proponents maintained that neural networks would eventually let machines to do much, much more. One day, they claimed, the technology would even understand language.

Over the past few years, neural networks have become vastly more complex and powerful. The approach has benefited from key mathematical refinements and, more important, faster computer hardware and oodles of data. By 2009, researchers at the University of Toronto had shown that a many-layered deep-learning network could recognize speech with record accuracy. And then in 2012, the same group won a machine-vision contest using a deep-learning algorithm that was astonishingly accurate.

A deep-learning neural network recognizes objects in images using a simple trick. A layer of simulated neurons receives input in the form of an image, and some of those neurons will fire in response to the intensity of individual pixels. The resulting signal passes through many more layers of interconnected neurons before reaching an output layer, which signals that the object has been seen. A mathematical technique known as backpropagation is used to adjust the sensitivity of the network's neurons to produce the correct response. It is this step that gives the system the ability to learn. Different layers inside the network will respond to features such as edges, colors, or texture. Such systems can now recognize objects, animals, or faces with an accuracy that rivals that of humans.

There's an obvious problem with applying deep learning to language. It's that words are arbitrary symbols, and as such they are fundamentally different from imagery. Two words can be similar in meaning while containing completely different letters, for instance; and the same word can mean various things in different contexts.

In the 1980s, researchers had come up with a clever idea about how to turn language into the type of problem a neural network can tackle. They showed that words can be represented as mathematical vectors, allowing similarities between related words to be calculated. For example, "boat" and "water" are close in vector space even though they look very different. Researchers at the University of Montreal, led by Yoshua Bengio, and another group at Google, have used this insight to build networks in which each word in a sentence can be used to construct a more complex representation-something that Geoffrey Hinton, a professor at the University of Toronto and a prominent deep-learning researcher who works part-time at Google, calls a "thought vector."

By using two such networks, it is possible to translate between two languages with excellent accuracy. And by combining this type of network with one designed to recognize objects in images, it is possible to conjure up surprisingly plausible captions.
The purpose of life
Sitting in a conference room at the heart of Google's bustling headquarters in Mountain View, California, one of the company's researchers who helped develop this approach, , is contemplating the idea of a machine that could hold a proper conversation. Le's ambitions cut right to the heart of why talking machines could be useful. "I want a way to simulate thoughts in a machine," he says. "And if you want to simulate thoughts, then you should be able to ask a machine what it's thinking about."

Google is already teaching its computers the basics of language. This May the company announced a system, dubbed Parsey McParseface, that can look at syntax, recognizing nouns, verbs, and other elements of text. It isn't hard to see how valuable better language understanding could be to the company. Google's search algorithm used to simply track keywords and links between Web pages. Now, using a system called RankBrain, it reads the text on pages in an effort to glean meaning and deliver better results. Le wants to take that much further. Adapting the system that's proved useful in translation and image captioning, he and his colleagues built Smart Reply, which reads the contents of Gmail messages and suggests a handful of possible replies. He also created a program that learned from Google's IT support chat logs how to answer simple technical queries.

Most recently, Le built a program capable of producing passable responses to open-ended questions; it was trained by being fed dialogue from 18,900 movies. Some of its replies seem eerily spot-on. For example, Le asked, "What is the purpose of life?" and the program responded, "To serve the greater good." "It was a pretty good answer," he remembers with a big grin. "Probably better than mine would have been."

There's only one problem, as quickly becomes apparent when you look at more of the system's answers. When Le asked, "How many legs does a cat have?" his system answered, "Four, I think." Then he tried, "How many legs does a centipede have?" which produced a curious response: "Eight." Basically, Le's program has no idea what it's talking about. It understands that certain combinations of symbols go together, but it has no appreciation of the real world. It doesn't know what a centipede actually looks like, or how it moves. It is still just an illusion of intelligence, without the kind of common sense that humans take for granted. Deep-learning systems can often be wonky this way. The one Google created to generate captions for images would make bizarre errors, like describing a street sign as a refrigerator filled with food.

Le asked, "What is the purpose of life?" and the program responded, "To serve the greater good."

By a curious coincidence, Terry Winograd's next-door neighbor in Palo Alto is someone who might be able to help computers attain a deeper appreciation of what words actually mean. Fei-Fei Li, director of the Stanford Artificial Intelligence Lab, was on maternity leave when I visited, but she invited me to her home and proudly introduced me to her beautiful three-month-old baby, Phoenix. "See how she looks at you more than me," Li said as Phoenix stared at me. "That's because you are new; it's early facial recognition."

Li has spent much of her career researching machine learning and computer vision. Several years ago, she led an effort to build a database of millions of images of objects, each tagged with an appropriate keyword. But Li believes machines need an even more sophisticated understanding of what's happening in the world, and this year her team released another database of images, annotated in much richer detail. Each image has been tagged by a human with dozens of descriptors: "A dog riding a skateboard," "Dog has fluffy, wavy fur," "Road is cracked," and so on. The hope is that machine-learning systems will learn to understand more about the physical world. "The language part of the brain gets fed a lot of information, including from the visual system," Li says. "An important part of AI will be integrating these systems."

This is closer to the way children learn, by associating words with objects, relationships, and actions. But the analogy with human learning goes only so far. Young children do not need to see a skateboarding dog to be able to imagine or verbally describe one. Indeed, Li believes that today's machine-learning and AI tools won't be enough to bring about real AI. "It's not just going to be data-rich deep learning," she says. Li believes AI researchers will need to think about things like emotional and social intelligence. "We [humans] are terrible at computing with huge data," she says, "but we're great at abstraction and creativity."

No one knows how to give machines those human skills-if it is even possible. Is there something uniquely human about such qualities that puts them beyond the reach of AI?

Cognitive scientists like MIT's Tenenbaum theorize that important components of the mind are missing from today's neural networks, no matter how large those networks might be. Humans have the ability to learn very quickly from a relatively small amount of data and have a built-in ability to model the world in 3-D very efficiently. "Language builds on other abilities that are probably more basic, that are present in young infants before they have language: perceiving the world visually, acting on our motor systems, understanding the physics of the world or other agents' goals," Tenenbaum says.

If he is right, then it will be difficult to re-create language understanding in machines and AI systems without trying to mimic human learning, mental model building, and psychology.
Explain yourself
Noah Goodman's office in Stanford's psychology department is practically bare except for a couple of abstract paintings propped against one wall and a few overgrown plants. When I arrived, Goodman was typing away on a laptop, his bare feet up on a table. We took a stroll across the sun-bleached campus for iced coffee. "Language is special in that it relies on a lot of knowledge about language but it also relies on a huge amount of common-sense knowledge about the world, and those two go together in very subtle ways," he explained.

Goodman and his students have developed a programming language, called Webppl, that can be used to give computers a kind of probabilistic common sense, which turns out to be pretty useful in a conversation. One experimental version can understand puns, and another can cope with hyperbole. If it is told that some people had to wait "forever" for a table in a restaurant, it will automatically decide that the literal meaning is improbable, and they most likely just hung around for a long time and were annoyed. The system is far from truly intelligent, but it shows how new approaches could help make AI programs that talk in a more lifelike way.

At the same time, Goodman's example also suggests just how difficult it will be to teach language to machines. Understanding the contextual meaning of "forever" is the kind of thing that AI systems will need to learn, but it is a rather simple and rudimentary accomplishment.

"I want a way to simulate thoughts in a machine," he says. "And if you want to simulate thoughts, then you should be able to ask a machine what it's thinking about."

Still, despite the difficulty and complexity of the problem, the startling success that researchers have had using deep-learning techniques to recognize images and excel at games like Go does at least provide hope that we might be on the verge of breakthroughs in language, too. If so, those advances will come just in time. If AI is to serve as a ubiquitous tool that people use to augment their own intelligence and trust to take over tasks in a seamless collaboration, language will be key. That will be especially true as AI systems increasingly use deep learning and other techniques to essentially program themselves.

"In general, deep-learning systems are awe-inspiring," says John Leonard, a professor at MIT who researches automated driving. "But on the other hand, their performance is really hard to understand."

Toyota, which is studying a range of self-driving technologies, has initiated a research project at MIT led by Gerald Sussman, an expert on artificial intelligence and programming language, to develop automated driving systems capable of explaining why they took a particular action. And an obvious way for a self-driving car to do this would be by talking. "Building systems that know what they know is a really hard problem," says Leonard, who is leading a different Toyota-backed project at MIT. "But yeah, ideally they would give not just an answer but an explanation."

A few weeks after returning from California, I saw David Silver, the Google DeepMind researcher who designed AlphaGo, give a talk about the match against Sedol at an academic conference in New York. Silver explained that when the program came up with its killer move during game two, his team was just as surprised as everyone else. All they could see was AlphaGo's predicted odds of winning, which changed little even after move 37. It was only several days later, after careful analysis, that the Google team made a discovery: by digesting previous games, the program had calculated the chances of a human player making the same move at one in 10,000. And its practice games had also shown that the play offered an unusually strong positional advantage.

So in a way, the machine knew that Sedol would be completely blindsided.

Silver said that Google is considering several options for commercializing the technology, including some sort of intelligent assistant and a tool for health care. Afterward, I asked him about the importance of being able to communicate with the AI behind such systems. "That's an interesting question," he said after a pause. "For some applications it may be important. Like in health care, it may be important to know why a decision is being made."

Indeed, as AI systems become increasingly sophisticated and complex, it is hard to envision how we will collaborate with them without language-without being able to ask them, "Why?" More than this, the ability to communicate effortlessly with computers would make them infinitely more useful, and it would feel nothing short of magical. After all, language is our most powerful way of making sense of the world and interacting with it. It's about time that our machines
caught up.

Will Knight is senior editor for AI and robotics at MIT Technology Review. His feature "The People's Robots" appeared in the May/June issue.

Tagged

Fei-Fei Li, Josh Tenenbaum, Google DeepMind, Go, artificial intelligence, AI, AlphaGo, Lee Sedol, Terry Winograd, EmTech 2016, MIT Technology Review Events

Credit

Courtesy of Mel Bochner and Peter Freeman Inc. (Bochner); Photo by Cathy Carver | Courtesy of Moved Pictures Archive | © 2016 Lawrence Weiner / Artists Rights Society, New York (Weiner); Courtesy of John Baldessari and Marian Goodman Gallery (Baldessari); Courtesy of Joseph Kosuth and Sean Kelly, New York; © 2016 Joseph Kosuth/Artists Rights Society (ARS), New York (Kosuth); © Tauba Auerbach; Courtesy of Paula Cooper Gallery (Auerbach)

Will Knight Senior Editor, AI

Will Knight is ... 2008 from the UK science weekly MIT Technology Review's Senior Editor for Artificial Intelligence. He covers the latest advances in AI and related fields, including machine learning, automated driving, and robotics. Will joined MIT Technology Review in More New Scientist magazine.

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Creating machines that understand language is AI's next big challenge

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About halfway through a particularly tense game of Go held in Seoul, South Korea, between Lee Sedol, one of the best players of all time, and AlphaGo, an artificial intelligence created by Google, the AI program made a mysterious move that demonstrated an unnerving edge over its human opponent.

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At its core, Amazon's goal is to remove as much friction as possible from a customer finding what they want, ordering it, and having it land on their doorstep. Its ambitions started with books, but have since extended to just about every other category, including clothes.

While it works to achieve a frictionless future in fashion, the company is testing a way to design new clothes without human designers.

MIT Technology Review reports that a team at the e-commerce company, working at a San Francisco research center, has devised an algorithm that analyzes images to learn about specific styles of clothing. It then creates similar new items from scratch. The technology is still in early stages and not ready for Amazon to put into use, but it shows what the company might have in store for the future.

To do it, the team uses an AI technique called generative adversarial network (GAN), originally developed by a Google researcher. It works by having two deep neural networks look at examples of existing fashion, and then go back and forth with each other, like a designer-critic team, to create something new that matches certain criteria. A shirt, for instance, must have two sleeves. It learns from past human creativity in fashion and, in a sense, replicates it.

It's not entirely clear how Amazon would put this technology to use. Theoretically, it could analyze what people are buying and see where there are holes in the market, using the new AI to generate designs for its many private fashion labels that could fill those gaps. Stitch Fix, a subscription clothing service, is currently using AI for that purpose and says the sales have been great.

Stitch Fix does, however, use human designers who turn the AI's suggestions into an actual garment. Whether Amazon's technology would require that kind of guidance is uncertain, but if not, it raises the question: Could the algorithm tell if a look it generates is a dud? An Amazon spokesperson said the company has no additional information it can provide.

It's perhaps telling that Amazon has also been working on AI that can judge whether an outfit is stylish. It recently announced Echo Look, which lets users take pictures of their outfits using a camera powered by Alexa, the company's interactive voice service. Among its features is the option for users to get a second opinion on an outfit they've photographed, using machine-learning algorithms combined with advice from fashion specialists at the company.

MIT Technology Review also notes that a group of Amazon researchers in Israel have machine learning that can analyze a few labels attached to images, in an environment like Instagram for example, and determine if a look is stylish.

Amazon's ambitions don't end at clothing design. Earlier this year, it received a patent for an on-demand clothing factory that would let it manufacture clothes quickly, and only after they had been ordered, saving the sunk costs of producing up front.

Imagine a future where Amazon allows you to shop a selection of AI-designed clothing that it only produces after someone buys it. The scenario might never come to pass, and if it does, it's still a long way off. But don't put it past Amazon to consider it.

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Amazon has an algorithm that designs clothes by replicating human creativity

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At its core, Amazon's goal is to remove as much friction as possible from a customer finding what they want, ordering it, and having it land on their doorstep. Its ambitions started with books, but have since extended to just about every other category, including clothes.

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~who decides what can be "forgotten"? i.e. the millions of poc who are criminalized for random things WILL THEIR PAST BE FORGOTTEN? see: cultural ideas of who is "dangerous"

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A businessman fighting for the "right to be forgotten" has won a UK High Court action against Google.

The man, who has not been named due to reporting restrictions surrounding the case, wanted search results about a past crime he had committed removed from the search engine.

The judge, Mr Justice Mark Warby, ruled in his favour on Friday.

But he rejected a separate claim made by another businessman who had committed a more serious crime.

The businessman who won his case was convicted 10 years ago of conspiring to intercept communications. He spent six months in jail.

The other businessman, who lost his case, was convicted more than 10 years ago of conspiring to account falsely. He spent four years in jail.

Both had ordered Google to remove search results about their convictions, including links to news articles, stating that they were no longer relevant.

They took Google to court when it refused to remove the search results.

Google said it would accept the rulings.

"We work hard to comply with the right to be forgotten, but we take great care not to remove search results that are in the public interest," it said in a statement.

"We are pleased that the Court recognised our efforts in this area, and we will respect the judgements they have made in this case."

'Legal precedent'

The right to be forgotten is a legal precedent set by the Court of Justice of the European Union in 2014, following a case brought by Spaniard Mario Costeja Gonzalez who had asked Google to remove information about his financial history.

Google says it has removed 800,000 pages from its results following so-called "right to be forgotten" requests. However, search engines can decline to remove pages if they judge them to remain in the public interest.

Explaining the decisions made on Friday, the judge said one of the men had continued to "mislead the public" while the other had "shown remorse".

The Open Rights Group, which campaigns for internet freedoms, said the rulings set a "legal precedent".

"The right to be forgotten is meant to apply to information that is no longer relevant but disproportionately impacts a person," said Jim Killock, executive director.

"The Court will have to balance the public's right to access the historical record, the precise impacts on the person, and the public interest."

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Google loses 'right to be forgotten' case

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A businessman fighting for the "right to be forgotten" has won a UK High Court action against Google. The man, who has not been named due to reporting restrictions surrounding the case, wanted search results about a past crime he had committed removed from the search engine.

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Facebook CEO Mark Zuckerberg gave interviews yesterday to several news organizations, including Recode, in an attempt to stem the fast-growing controversy about misuse of user data by a third-party developer, Cambridge Analytica.

In a wide-ranging interview, he admitted the social networking giant may have made mistakes in opening up its network so much a decade ago and that it led to the recent problems. Zuckerberg said that fixing those issues will now cost the company "many millions" of dollars.

As Facebook's stock continued to get hammered because of Wall Street worries about the impact in its business, Zuckerberg also said he was "open" to testifying to Congress, even as legislators ever more loudly call for his appearance in hearings.

And that is not all Silicon Valley's most famous mogul said, which is why we are posting the transcript of the 20-minute interview, which was conducted by Kara Swisher and Kurt Wagner of Recode.

A short amount of cross-talk about setting up the taping of the interview at the start was removed, but here is the interview (with some small adjustments to explain references made).
Kara Swisher: As you know from us emailing, I'm very interested in tough substantive discussions and questions about this, so that's why I've been so adamant. So let's just get started. Talk a little bit about the things you announced today. Let's have you explain each of them very briefly.
Mark Zuckerberg: Sure. At a high level, this is a major breach of trust issue, and our high-level responsibility is to make sure that this doesn't happen again. So, if you look at the problem, it kind of breaks down into a couple of areas. One is making sure that going forward, developers can't get access to more data than they should. The good news there is that actually the most important changes to the platform we made in 2014, three or four years ago, to restrict apps like [researcher Aleksandr Kogan's] from being able to access a person's "friends" data in addition to theirs.

So that was the most important thing, but then what we did on our platform is we also are closing down a number of other policies. Like, for example, if you haven't used an app in three months, the app will lose the ability to clear your data without you reconfirming it, and a number of things like that. So, that's kind of category 1 going forward. And again, the good news there is that as of three or four years ago, new apps weren't able to do what happened here. So this is largely ... this issue is resolved going forward for a while.

Then there's going backwards, which is before 2014, what are all the apps that got access to more data than people would be comfortable with? And which of them were good actors, like legitimate companies, good intent developers, and which one of them were scams, right? Like, what Aleksandr Kogan was doing, basically using the platform to gather a bunch of information, sell it or share it in some sketchy way. So what we announced there is, we're going to do a full investigation of every single app that had access to a large amount of people's data, before 2014 when we lost out the platform, and if we detect anything suspicious, we're basically going to send in a team to do a full forensic audit, to confirm that no Facebook data is being used in an improper way.
KS: So that begs the question ... this started off in 2007, 2008 when you were [launching] Facebook Connect, a lot of this stuff started very early, and I remember being at that event where you talked about this. Open and sharing, and it was helpful to growing your platform, obviously. Why wasn't this done before? What's in the mentality of your engineers of Facebook where you didn't suspect this could be a problem? KS: Well, whatever. People [at Facebook].
And of course, any developer that isn't comfortable with that, then we'll just ban them from the platform. If we find anything that is bad, then we'll of course also ban the developer, but we will then also notify and tell people, everyone whose data has been affected. Which we're also going to do here.

Well, I don't think it's engineers.

So, in 2007 we launched the platform.

The vision, if you remember is to help make apps social.
K S:K S: Right, so where's your opinion right now? Sorry to interrupt. KS: I'm going to push back on that, because values are what we argue about. And companies have values, and they have, you know, the New York Times has a set of values that they won't cross and they make decisions. Why are you so uncomfortable making those value decisions? You run the platform. It is more than just a benign platform that is neutral. It just isn't. I don't know, we can disagree on that, we obviously disagree on this. But why are you uncomfortable doing that? I get that. 2014 you absolutely did that. But I'm talking about the ... You know - and I've argued with [Facebook executives] about this - this anticipation of problems, of possible bad actors on this platform. Do you all have enough mentality, or do you not see ... I want to understand what happens within Facebook that you don't see that this is so subject to abuse. How do you think about that, and what is your responsibility?
So, the examples we had were, you know, your calendar should have your friend's birthday. Your address book should have your friend's picture. In order to do that, you basically need to make it so a person can log into an app and not just port their own data over, but also be able to bring some data from their friends as well. That was the vision, and a bunch of good stuff got created. There were a bunch of games that people liked. Music experiences, things like Spotify Travel, you know, things like Airbnb they were using it. But there was also a lot of scammy stuff.

There's this values tension playing out between the value of data portability, right? Being able to take your data and some social data ... To be able to create new experiences on the one hand, and privacy on the other hand, and just making sure that everything is as locked down as possible.

You know, frankly, I just got that wrong. I was maybe too idealistic on the side of data portability, that it would create more good experiences. And it created some, but I think what the clear feedback was from our community was that people value privacy a lot more. And they would rather have their data locked down and be sure that nothing bad will ever happen to it than be able to easily take it and have social experiences in other places. So, over time, we have been just kind of narrowing it down. And 2014 was a really big ...
KW: Did you ever think of doing these kinds of audits before 2014? Or even when you got that signed contract from ... or, excuse me, signed statement I guess, from Cambridge Analytica, did you think, "Well, we need to actually go out and check to make sure that they're telling us the truth." Why didn't you do this kind of stuff earlier, or did you think about doing this earlier?
Yeah. Well, I hope we're getting there. I think we remain idealistic, but I think also understand what our responsibility is to protect people now. And I think the reality is is that in the past we had a good enough appreciation of some of this stuff. And some of it was that we were a smaller company, so some of the issues and some of these bad actors just targeted us less, because we were smaller. But we certainly weren't in a target of nation states trying to influence elections back when we only had 100 million people in the community.

But I do think part of this comes from these idealistic values of openness and data portability and things that I think the tech community holds really dear, but are in some conflict with some of these other values, are in protecting people privately, right? And a lot of the most sensitive issues that we faced today are conflicts between our real values, right? Freedom of speech and hate speech and offensive content. Where is the line, right? And the reality is that different people are drawn to different places, we serve people in a lot of countries around the world, a lot of different opinions on that.
KS: All right, when you think about that idea of ... it's not exactly a "mistakes were made" kind of argument, but you are kind of making that. That idea. I want to understand, what systems are going to be in place, but it's sort of, you know, the horses are out of the barn door. Can you actually go get that data from them? Are you ... It's everywhere, I would assume. I've been told by many, many people that have access to your data, I was thinking of companies like RockYou and all kinds of things from a million years ago that have a lot of your data ... Can you actually get it back? I don't think you can. I can't imagine you can.
On that one specifically?
KS: Let me ask just two more quick questions.
You know, what I would really like to do is find a way to get our policies set in the way that reflects the values of the community so I'm not the one making those decisions. Right? I feel fundamentally uncomfortable sitting here in California at an office, making content policy decisions for people around the world. So there are going to be things that we never allow, right, like terrorist recruitment and ... We do, I think, in terms of the different issues that come up, a relatively very good job on making sure that terrorist content is off the platform. But things like where is the line on hate speech? I mean, who chose me to be the person that ...
KS: All right, the cost of this? And are you going to testify in front of Congress? And if so, when? KS: What is "open"? Is that a "yes" or a "no"?
I have to, because [I lead Facebook], but I'd rather not.
KW: Mark, can you give us a sense of the timing and cost for this? Like, the audits that you're talking about. Is there any sense of how quickly you could do it and what kind of cost it would be to the company? KS: Okay, last question Mark, and then you can go. How badly do you think Facebook has been hurt by this, and you yourself, the reputation of Facebook? KS: KS: Thank you so much, I know you have to talk to your employees ... Yes, let's not. Okay, Mark, I really appreciate you talking to us.
Well, I just want to make the decisions as well as possible, and I think that there is likely a better process, which I haven't figured out yet. So, for now, it's my job, right? And I am responsible for it. But I just wish that there were a way ... a process where we could more accurately reflect the values of the community in different places. And then in the community standards, have that be more dynamic in different places. But I haven't figured it out yet. So I'm just giving this as an example of attention that we debate internally, but clearly until we come up with a reasonable way to do that, that is our job, and I do well in that.

Kurt Wagner: Hey, Mark, this is Kurt. I'm curious, you talked about going back and trying to figure out if there were other developers that had used your API before 2014, and checking were there any other bad actors that maybe you guys missed at the time. I'm curious how you actually go about doing that, and if it's actually possible at this point to go out and detect, you know, if someone collected data in 2012, if that data still exists.

Well, the short answer is the data isn't on our servers so it would require us sending out forensic auditors to different apps. The basic process that we've worked out - and this is a lot of what we were trying to figure out over the last couple of days and why it took a little while to get this post out - is we do know all the apps that registered for Facebook and all the people who are on Facebook who register for those apps and have a log of the different data requests that the developer has made.

So we can get a sense of what are reputable companies, what are companies that were doing unusual things ... Like, that either requested data in spurts, or requested more data than it seemed like they needed to have. And anyone who either has a ton of data or something unusual, we're going to take the next step of having them go through an audit. And that is not a process that we can control, they will have to sign up for it. But we'll send in teams, who will go through their servers and just see how they're handling data. If they still have access to data that they're not supposed to, then we'll shut them down and notify ... and tell everyone whose data was affected.

This is a complex process. It's not going to be overnight. It's going to be expensive for us to run, and it's going to take a while. But look, given the situation here, that we had a developer that signed a legal certification saying that they deleted the data, now two years later we're back here and it seems like they didn't, what choice do we have? This is our responsibility to our community is to make sure that we go out and do this. So, even though it's going to be hard and not something that our engineers can just do sitting in their offices here, I still think we have to go do this.

In retrospect, it was clearly a mistake. Right? The basic chronology here is in 2015, a journalist from the Guardian pointed out to us that it seemed like the developer Aleksandr Kogan had sold shared data to Cambridge Analytica and a few other firms. So as soon as we learned that, we took down the app, and we demanded that Kogan, Cambridge Analytica and all the other folks give up the formal, legal certification that they didn't have any other data. And, at the time, Cambridge Analytica told us that not only do we not have the data and it's deleted, but so we actually never got access to raw Facebook data. Right? What they said was, this app that Kogan built, it was a personality quiz app, and instead of raw data they got access to some derived data, some personality scores for people. And they said that they used it in some models and it ended up not being useful so they just got rid of it.

So, given that, that they said that they never had the data and deleted what derivative data that they had, at the time it didn't seem like we needed to go further on that. But look, in retrospect it was clearly a mistake. I'm explaining to you the situation at the time and the actions that we took, but I'm not trying to say it was the right thing to do. I think given what we know now, we clearly should have followed up, and we're never going to make that mistake again.

I think we let the community down, and I feel really bad and I'm sorry about that. So that's why we're going to go and do these broad audits.

Not always. But the goal isn't to get the data back from RockYou. You know, people gave their data to RockYou. So RockYou has the right to have the data. What RockYou does not have the right to do is share the data or sell it to someone without people's consent. And part of the audits and what we're going to do is see whether those business practices were in place, and if so we can kind of follow that trail and make sure that developers who might be downstream of that comply or they're going to get banned from our platform overall.

It isn't perfect. But I do think that this is going to be a major deterrent going backwards. I think it will clean up a lot of data, and going forward the more important thing is just preventing this from happening in the first place, and that's going to be solved by restricting the amount of data that developers can have access to. So I feel more confident that that's going to work, starting in 2014 and going forward. Again, for the last few years already it hasn't been possible for developers to get access to that much.

[Here, there is logistical cross-talk with a person on his staff, since Zuckerberg had to head to an employee meeting.]

All right, I'm talking to you while walking over there for Q&A.

You know, I'm open to doing that. I think that the way that we look at testifying in front of Congress is that ... We actually do this fairly regularly, right? There are high-profile ones like the Russian investigation, but there are lots of different topics that Congress needs and wants to know about. And the way that we approach it is that our responsibility is to make sure that they have access to all the information that they need to have. So I'm open to doing it.

Well.

Well look, I am not 100 percent sure that's right. But the point of congressional testimony is to make sure that Congress gets the data in the information context that they need. Typically, there is someone at Facebook whose full-time job is going to be focused on whatever the area is. Whether it's legal compliance, or security. So I think most of the time if what they're really focused on is getting access to the person who is going to be most knowledgeable on that thing, there will be someone better. But I'm sure that someday, there will be a topic that I am the person who has the most knowledge on it, and I would be happy to do it then.

I think it depends on what we find. But we're going to be investigating and reviewing tens of thousands of apps from before 2014, and assuming that there's some suspicious activity we're probably going to be doing a number of formal audits, so I think this is going to be pretty expensive. You know, the conversations we have been having internally on this is, "Are there enough people who are trained auditors in the world to do the number of audits that we're going to need quickly?" But I think this is going to cost many millions of dollars and take a number of months and hopefully not longer than that in order to get this fully complete.

I think it's been a pretty big deal. The No. 1 thing that people care about is privacy and the handling of their data. You know, if you think about it, the most fundamental thing that our services are, whether it's Facebook or Whatsapp or Instagram, is this question of, "Can I put content into it?" Right? Whether it's a photo or a video or a text message. And will that go to the people I want to send it to and only those people? And whenever there is a breach of that, that undermines the fundamental point of these services. So I think it's a pretty big deal, and that's why we're trying to make sure we fully understand what's going on, and make sure that this doesn't happen again. I'm sure there will be different mistakes in the future, but let's not make this one again.

I'm walking into my Q&A now. All right, see ya.

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Here's the transcript of Recode's interview with Facebook CEO Mark Zuckerberg about the Cambridge Analytica controversy and more

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Facebook CEO Mark Zuckerberg gave interviews yesterday to several news organizations, including Recode , in an attempt to stem the fast-growing controversy about misuse of user data by a third-party developer, Cambridge Analytica.

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By the time lawmakers were openly asking Mark Zuckerberg to make their state's internet faster or telling him how much their kids love Instagram, the damage had already been done: Mark Zuckerberg had been owned. Looking less like a titan of industry than an agoraphobic giving a TED Talk, Zuckerberg submitted himself to fear-mongering questions about user data, Cambridge Analytica, online censorship, and Russian interference in the 2016 election during a pair of hearings in front of the Senate and the House Energy and Commerce Committee.

The hearings were dramatic and, in their own way, a gripping bit of television. We laughed when we found out he had to use a booster seat because of course he did, and we laughed when we saw a photo of his notes on Reddit, because of course that happened too. We cringed as he also had to answer no less than seven questions about whether or not Facebook had intentionally censored conservative vloggers Diamond and Silk. Most importantly, though, we couldn't help but be transfixed as Zuckerberg was forced to detail the way things we take for granted as young people who use the internet are actually quite sinister, when viewed through the lens of a Congressional hearing.

Though they may be movers and shakers on the Hill, the Senators and House members who lobbed questions at Zuckerberg are, in essence, subject to the same power imbalance as we are when they log onto Facebook - and perhaps even more so, given the lack of internet literacy that many of them displayed with their questions. That Zuckerberg was made to explain very basic things about how his multi-billion-dollar social media platform worked to these elected officials was in its own way an ignominy, the same as if you or I were at a party and had to take a call from our dad who needed help finding where the WiFi password was printed on the router.

Still, they fulfilled their roles as our elected representatives in a way that rarely actually happens in America, giving Zuckerberg a piece of their constituents' minds - even if many of their questions were nonsensical or completely unrelated to the issue of whether or not Facebook improperly gave user data to Cambridge Analytica. It felt like the tables had been turned, with the man who holds the world's secrets suddenly legally bound to tell his - or at least tell the truth, or at least not lie while being evasive as possible. He looked uncomfortable. We were able to mock him. We finally got a chance to sift through his trash.

In his 2015 book So You've Been Publicly Shamed, the British journalist Jon Ronson dug up the following bit of history while discussing the dethroning of New Yorker writer Jonah Lehrer, who was revealed by journalist Michael Moynihan to have been a serial plagiarist:

A book of Delaware laws I discovered at the Massachusetts Historical Society revealed that if [a person] had been found guilty of 'lying or publishing false news' in the 1800s, he would have been 'fined, placed in the stocks for a period not exceeding four hours, or publicly whipped with not more than forty stripes.' If the judge had chosen a whipping, local newspapers would have published a digest detailing the amount of squirming that had occurred. [...] If [the] whipper had been deemed to have not whipped hard enough, the reviews would have been scathing.

Switch a few of the nouns around, and you get essentially happened to Zuck this week. The booster seat and the camera trained upon his blank, terrified face functioned as the stocks, each hearing a whipping and each question a lash. Though the point of the hearings were to hold Zuckerberg and the tech industry at large to account for abuse of customer trust, from a viewer's perspective, their actual content ultimately seemed less important than the fact that a visibly uncomfortable Zuckerberg had to sit there and provide answers.

While speaking with the House Energy and Commerce Committee on the second day of hearings, Zuckerberg seemed largely unfamiliar with the details of much of Facebook's business operations; in exchanges with seven different representatives from both sides of the political divide, he responded to tough questions with some variation of, "I'm not familiar with that." While it's possible that Zuckerberg, as the head of an enterprise that employs tens of thousands of people, was genuinely unfamiliar with the day-to-day workings of Facebook, this may have been a strategy on his part - as TechCrunch pointed out, though he was not technically under oath, lying to Congress is still a crime.

After the publication of So You've Been Publicly Shamed, Ronson would tweet a startling insight while comparing Lehrer to another person featured in the book: "I believe our shame-worthiness often lies in the space between who we are and how we present ourselves to the world." If we accept Ronson's premise, then our renewed zest for public shaming is itself is a side-effect of social media culture - collective outrage at the discovery that one's public and private selves are incongruous. And if this is the case, then Zuckerberg is one of the architects of modern shame. After all, Facebook and its sister service Instagram are two of the chief tools that we use to create the distance of which Ronson speaks - broadcasting our successes while shrouding our failures, dreading the moment that this dissonance is discovered. The wealth generated by these social networks has effectively rendered Zuckerberg's private life from ever being exploited or even truly understood - after all, we're talking about someone with access to the best public relations teams that money can buy and a personal security force worthy of the head of a nation-state.

But as he sat in his booster seat, struggling to foreground Facebook's positive contributions to the world while avoiding disclosing its more sinister elements without technically lying, Zuckerberg was forced to feel the same discomfort that plagues our everyday lives. Perhaps our glee at watching Zuck squirm is undergirded by a subliminal hope that now that he has felt an IRL version of the same gap that his services subject us to, he will feel a bit more empathy for the rest of us. Given that Facebook's stock jumped skyward in the hours after Zuckerberg's testimony on Tuesday, it seems that, to far too many people, this hope was enough.

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By the time lawmakers were openly asking Mark Zuckerberg to make their state's internet faster or telling him how much their kids love Instagram, the damage had already been done: Mark Zuckerberg had been owned.

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The GDPR was proposed by the European Commission in 2012 as an update to an existing EU data-privacy law, Data Protection Directive 95/46/EC, which had been on the books since 1995. The European Parliament passed its own version of the GDPR in 2014 with the Council of the European Union following suit in 2015, at which time the three bodies got together to hash out the final wording of the law. That process lasted until 2016. Now, after a two-year grace period, the GDPR will go into effect in May.

Once it does, it will provide an unprecedented level of privacy protection for EU citizens living both in an EU member nation or abroad. It will effectively regulate the privacy practices of any company that processes the personal data of people residing within the EU, regardless of where the company itself is located -- including the cloud. That is, companies will be held responsible for the handling of the personal data they have collected from users. What's more, it grants people the " right to be forgotten" as well as the right to request both copies of their personal data and information pertaining to how and why their data is being processed.

Users will also enjoy data portability, the ability to move their personal data from one company to another. This rule offers an interesting secondary effect that Facebook might not like. With the ability to move one's data freely between services, it could help prevent the lock-in effect that helps companies like Facebook and Google establish insurmountable market dominance by lowering the barriers of entry for new, competing services.

The GDPR also significantly strengthens consent protections for EU residents/citizens as well. Companies will be prohibited from using "long illegible terms and conditions full of legalese, as the request for consent must be given in an intelligible and easily accessible form, with the purpose for data processing attached to that consent," according to the GDPR website. "It must be as easy to withdraw consent as it is to give it."

When questioned by Rep. Gene Green, a Texas Democrat, about how Facebook would implement this practice in the US, Zuckerberg asserted that the FB app will include a step-by-step tool that walks users through their settings, allowing them to adjust their privacy controls as they wish. Whether users will use the tool in appreciable numbers remains to be seen.

To ensure companies will comply with these broad demands, the GDPR offers some serious penalties for those who would ignore the law. Infractions carry a maximum fine of 4 percent of annual global turnover (aka the company's annual revenue) or €20 million, whichever is greater. The penalties are tiered, mind you, with minor infractions like not having your records in order or not properly notifying authorities in the event of a data breach carrying a 2 percent fine.

To its credit, Facebook has committed to applying the GDPR benchmarks, not just " controls and settings" to all of its global network. "Overall, I think regulations like this are very positive," Zuckerberg told reporters on a conference call in April. "We intend to make all the same controls available everywhere, not just in Europe."

"Is it going to be exactly the same format? Probably not," he continued. "We'll need to figure out what makes sense in different markets with different laws in different places. But let me repeat this: We're going to make all the same controls and settings available everywhere, not just in Europe." That said, there's no word yet on when Facebook would actually implement such changes.

From a technical standpoint, there's not much preventing Facebook from implementing these protections worldwide. The problem, it turns out, is political. As a Facebook representative explained to Techcrunch, the GDPR protections run contrary to data-collection laws in some countries, which means that they can't legally be rolled out everywhere. Still, the company remains committed to expanding the protections to as many users as it can.

While it's all well and good that Facebook is doing the right thing for once rather than moving fast and breaking stuff, there's no reason for governments not to implement their own data-protection legislation. In fact, some local governments are already planning privacy bills. San Francisco supervisor Aaron Peskin announced one such bill on Tuesday which would prohibit the city from doing business with any company that does not adhere to the "the highest standards for data protection." Details of the bill, which will go before voters in November, have not yet been released.

But even without national legislation, the US government already has a de facto data-protection-enforcement mechanism. It's called the Federal Trade Commission. The FTC has aggressively pursued a number of companies including Google and Uber over the past few years using Section 5 of the FTC Act, which prohibits unfair or deceptive trade practices. The FTC has successfully argued that companies that have suffered data breaches violated Section 5 because said breaches were the result of the companies' failure to adopt "reasonable" data-protection schemes.

A few companies have fought against this litigation, rather than settle and issue consent decrees, including Wyndham Hotels and LabMD. These companies argue first that there is no legal definition of what constitutes a "reasonable" data-protection scheme and, second, that no level of cybersecurity is high enough to defend against each and every hacking attempt.

In a 2017 lawsuit against D-Link, the FTC once again invoked Section 5, arguing that the company failed to take reasonable precautions to harden its products against known and reasonable threats. The FTC charges point out that D-Link left its private key, which hackers can use to cajole machines into running malware, on a public website for six months, and the company's software suffers a known "command injection" vulnerability.

However, the case gets a bit sticky because the FTC goes on to argue that D-Link's actions -- just like LabMD's -- may cause harm to its customers. D-Link has countered, arguing that the mere potential for harm is insufficient to bring litigation. According to D-Link's filing, "the FTC speculates that consumers were placed "at risk" to be hacked but fails to allege, as it must, that actual consumers suffered or are likely to suffer actual substantial injuries."

Both the D-Link and LabMD lawsuits are ongoing but illustrate the need for a legislative solution to the issue of data privacy in America, rather than having the courts craft it one case at a time. However, given the partisan climate in Washington, passing a bill similar to the GDPR seems unlikely.

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Can Facebook really apply the EU's data-privacy rules worldwide?

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The GDPR was proposed by the European Commission in 2012 as an update to an existing EU data-privacy law, Data Protection Directive 95/46/EC, which had been on the books since 1995.

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Since time is short, I will jump straight into the heart of things. My thesis today is simple: digital technologies are both our best hope and our worst enemy. Big problems like climate change and disease are unlikely to be tackled without them. Moreover, the Internet of Things shows some promising early signs that shared resources can be managed differently and more effectively, empowering smaller, local communities in an unprecedented way.

But digital technologies also create political and economics challenges of their own. They aggravate various neoliberal tendencies of contemporary society and entrench corporate interests over those of the public. This is not surprising given that the companies that own and operate these technologies are often in the avantgarde of the neoliberal agenda. The political task ahead, then, is to amplify the positive uses of these technologies and minimize their negative ones.

When the very term "digital technologies" spans everything from electronic books to drones to smart thermostats, we badly need some analytical clarity. Today I will group them into three categories: sensors, filters, profiles. This triad can explain much of our contemporary technological landscape.

Take something as banal as making a Google search. Google's search box functions as a sensor of sorts - it captures your "intent" to find something. To deliver the relevant results, Google has to rely on filters to separate relevant results from irrelevant ones. It determines relevance partly by drawing on a "profile" of you that it stores it its memory - and it adds your current search (and your subsequent clicks) to that profile. But since Google is now present in many different domains - from self-driving cars to maps to books to videos - your "profile" is really a totality of all your interactions with Google.

Likewise, Uber draws on sensors - our smartphones - to understand where we are in the city; uses filters to match supply and demand at the most profitable price; and relies on "profiles" - of both the driver and the passenger - to reduce mutual concerns about misbehavior, adding information generated on each trip to the profile of both parties.

This ability to capture our behavior (in the form of clicks or location) in real-time and to store it for future, personalized use is one of the key features of the emerging data-centric capitalism. Its promise is the ultimate and total personalization of our everyday experience based on the preferences that are captured in our "profiles." Such personalization can also increase the efficiency of resource use, reduce waste, lead to more sustainability: it's not just a myth of Silicon Valley.

Think of the announcement about the partnership between Uber and Spotify, the music streaming service: from now on, you the passenger would be able to play your favorite Spotify songs in any Uber car. This is possible precisely because our music preferences have been collected into a profile - a digital identity of sorts - and that profile can now be shared across various platforms.

The Uber/Spotify example might seem trivial but think of the many different "profiles" that the new smart devices can - and some already do - generate: smart thermostats generate profiles of our preferred energy use, smartphones (not to mention self-driving cars) generate profiles of our physical activity and movement, search engines and social networks generate profiles of our information needs and reading habits. Anybody thinking about the future provision of transportation, education, energy, health services cannot ignore this data - for if they do, a bunch of (mostly American) entrepreneurs will emerge to disrupt them.

This data, once available, can lead to all sorts of socially useful experimentation and innovation. Entire communities might opt out for a different model of public transportation, whereby a bus service would pick up passengers on a unique route that is mapped out anew every day based on actual transportation needs of citizens in a given community. Cities like Seoul and Helsinki are experimenting with such models already. The same applies to energy generation and resource sharing more broadly.

But let me emphasize that this wave of social experimentation can only become possible if the community has access to the underlying data. Without the data, communities will be stuck with the models imposed on them by the corporate providers of those services. So instead of having personalized bus services, we would forever be stuck with Uber's individualistic model.

This is an important point to keep in mind: the only level of action that technology companies realize is that of the individual consumer. We are all invited to join the sharing economy but only as entrepreneurs who will put up our skills, our free time, our flats, our cars, our "dead capital" as some call it, for rent on the market.

This is, after all, what today's sharing economy is about: it's about relying on information and communication technologies to establish efficient markets in everything and turn everyone into a psychotic entrepreneur. Why psychotic? Well, because we are invited to always be anxious about our reputation: our every interaction with various parts of the sharing economy is recorded, ranked, and stored for posterity, affecting all our future interactions.

It's in this sense that the sharing economy is truly neoliberalism on steroids: it creates markets everywhere while also producing a new subjectivity in its participants. Some of you may have heard of a recent episode in Britain, where a woman was told she could not use AirBnb because she has less than 100 Facebook friends - and it's through our Facebook's identity that Airbnb establishes our "authenticity" and "validity" as customers.

The end game here is easy to predict. The basic relationship is simple: whoever controls the most and the best sensors will eventually control the profiles. Thus, ultimately, we'll end up with just two companies - Facebook and Google - controlling the entire field of "digital identity." This means, among other things, that these two companies will become the key intermediaries in how every other service - energy, health, education, transportation - is provided.

Both of these companies, each in its own way, benefit from network effects: Facebook's service is more valuable the greater the number of people who pursue their social activities within Facebook while Google's service is more valuable the more of the world's knowledge it has organized.

To me, it seems obvious that Google's search results are better if it knows where you are, what you have searched for in the past, who your friends are, and so on. It very well may be that both search and social networking are, in fact, the kinds of activities that can only be meaningfully pursued by monopolies that draw on an extensive base of information gathered from various - rather than just one - social domains.

Thus, instead of breaking up Google into various components - for example, making search separate from maps or maps separate from email - a different kind of break-up is in order. We must take the matter of digital identity completely out of commercial jurisdiction and instead turn it into a public good. Think of this is as the intellectual infrastructure of the data-centric capitalism.

To reiterate: If we are faced with emerging data-centric capitalism, then the only way to guarantee that citizens won't be crushed by it is to ensure that its main driving force - data - remains squarely in public hands. I don't have time to expand on this at greater length but there need to be a greater consolidation of public interest across all the three layers - sensors/filters/profiles - that I've mentioned.

It might sound counterintuitive but this is how things should be: my every click on any app or site, my every interaction with my smart thermostat or my smart car, my every move in the city should accrue to me, the citizen - and not to the companies offering these services. By assuming that "click capital" - and this is what it is, it's a form of capital - naturally belongs to corporations, the public would eventually see its control over them diminish completely.

Furthermore, some basic services - very simple searches, basic email functionality, and so on - could and should be provided free and as part of public infrastructure. In exchange for this, some of the anonymized data in our digital profiles could be used by public bodies - cities, municipalities, utilities - to improve their service offerings, making them more sustainable and personalized. Personalization, by the way, does not need to lead to the kinds of reputation concerns that arise in the context of using Uber or Airbnb where clients are ranked and evaluated: one can still have full personalization and anonymity.

This doesn't mean that technology companies would simply disappear. Instead, they can offer whatever advanced and personalized bonus services they want - after they license the use of this data. Google might offer features - some of them paid and desired, perhaps, just by 5% of the users - that would not be offered in the basic email service. It might also offer some advanced personalization of search thanks to its algorithms and advanced artificial intelligence technology. But note that other companies - including start-ups - would suddenly be able to compete with Google, as they will be able to draw on as much data about their customers as Google and Facebook alone can do now.

To conclude, let me outline two scenarios: a pessimistic and an optimistic one. Bad things, as usual, are easier to predict. Well, if things continue as they are, we'll end in a world where one or two giant technology companies become key gateways to all other services solely because they control our digital identities. Those services, too, would be provided by extremely ruthless technology companies keen to disrupt everything under the sun using the most brutal tactics: think Uber and Airbnb. Alternative modes of social and economic organization - which would try to use resources collectively but on a logic different from the neoliberal one - would be blocked at every possible moment.

How do we avoid this scenario and move towards something more positive? Well, the first step is to problematize the question of data. Is data an asset? Who owns it and can it really be owned? If we are moving into a data-centric and data-intensive capitalism, what does it mean for the public not to be able to control the key resources of the age - that is, data? Can politics still maintain any effective control over the market if its key resource - data - lies beyond its reach?

It's only by answering such questions that Europe can mount a response to the alliance between Silicon Valley and neoliberalism. It won't do to create a European Google: to think in those terms is to miss the shift to data-centric capitalism. We should not just think of new ways to regulate Google and Facebook and the rest as they exist today; we must also rethink the very basic form in which the services that they currently provide are to be provided in the future. It's not at all clear that the model with which we have ended up would be favored by anybody concerned with public interest.

But once again: breaking them up into individual units is not going to do the job, whatever its appeal might be to Google's competitors and adversaries. The right way to think about cutting up such companies would be in terms of basic and advanced services: the former could be provided for free and be accessible to all while the companies can make money on advanced services but without hoarding the data generated in the context of their use.

Thus, what's needed is structural and institutional innovation that could reclaim data as a public good, place it outside of the market, and then promote entrepreneurial activities on top of it. This won't be easy but the incentives, for politicians at least, could not be greater: another decade of inaction and Google and Facebook will end up running their own quasi-state, as they will control both our identity and our access to basic infrastructure (this, by the way, is already happening in parts of the developing world). A more depressing development for human freedom can hardly be imagined.
This is the transcript of a speech delivered in Berlin in December 2014 at a 'philosophy meets politics' event of the Kulturforum der Sozialdemokratie. Have something to add to this story? Share it in the comments below.

About Evgeny Morozov

Evgeny Morozov is contributing editor at The New Republic and the author of 'The Net Delusion: The Dark Side of Internet Freedom' and 'To Save Everything, Click Here: The Folly of Technological Solutionism'. In 2010-2012 he was a visiting scholar at Stanford University and a Schwartz fellow at the New America Foundation.

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Digital Technologies And The Future Of Data Capitalism

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Since time is short, I will jump straight into the heart of things. My thesis today is simple: digital technologies are both our best hope and our worst enemy. Big problems like climate change and disease are unlikely to be tackled without them.

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soooo much of tech is publicly funded yet so many tech companies LOVE NOT PAYING THEIR TAXES
~also, people put tech dudes like steve jobs on pedestals tho they ARE publicly funded but no we will just glamorize this one dude and perpetuate the idea that one person is out here changing the world (what about COLLECTIVISM)

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Without public research funding, there'd be no iPhone - which makes Apple's relentless tax dodging even more whack.

The iPhone has changed so much about how we live and interact with one another that it's hard to believe that the original iPhone went on sale just over 10 years ago, popularizing the concept of the smartphone. Since June 29, 2007, smartphones have become an essential part of our everyday lives - to the point where more people now browse the web on mobile than desktop, more Google searches come from mobile platforms, and more people in many developing countries use smartphones as their primary Internet-accessing device, bypassing PC Internet connections altogether.

Of course, not all smartphones are iPhones. In 2016, Apple was responsible for only 14.4 percent of smartphones sold globally, but there can be no denying that the original iPhone set the template for what a smartphone must be - a template that was further refined in the years that followed. Apple has sold more than 1.2 billion iPhones over the product's lifecycle, bringing in over $700 billion in revenue and over $100 billion in profit.

The claim made by many Silicon Valley libertarians that the private market is superior to public funding simply isn't supported by the evidence.

As the company prepares to unveil the 10th-anniversary iPhone, which it hopes will redefine the category once again, it's worth remembering that without public research funding, many of the technologies that are fundamental to smartphones would not exist. Moreover, the claim made by many Silicon Valley libertarians that the private market is superior to public funding simply isn't supported by the evidence.

Publicly Funded Tech is Central to Silicon Valley's Success

If we were to listen only to Silicon Valley CEOs and libertarian venture capitalists, they would tell us that tech companies and the "move fast and break things" model of capitalism that they practice are responsible for a level of innovation and entrepreneurship that has been seldom seen in the past. The technologies developed by start-ups and in the secretive labs of multinational conglomerates would not be possible without private funding and are threatened by any regulation - new or existing. The way to maximize innovation, they say, is for the government to get out of the way and let entrepreneurs do pretty much whatever they want.

But history contradicts these assertions.

The success of Apple, Google and many of the other major corporations that now dominate the Valley is not a result of the model they now preach. Instead, it's highly unlikely that these companies would be as successful as they are today without the support the government has provided.

Steve Jobs may have been a genius - he certainly had an eye for design - but his most successful product would not exist if it weren't for the billions of dollars that the US government spends every year on research and development. The best accounting of this has been done by Mariana Mazzucato, author of The Entrepreneurial State, who skillfully explains that touch-screen displays, GPS, the Internet and even Siri were the product of public research funding - features the iPhone wouldn't be very compelling without.

And that's not to say that Apple should get no credit for the revolutionary product it created. The company assembled those technologies in a compelling package and has developed many of its own innovations to enhance it along the way. But that doesn't change the fact that the fundamentals wouldn't exist without the government.

In her research, Mazzucato even found that at an early stage, Apple received funding from the federal government's Small Business Investment Company, which was created to provide stable, long-term support for new businesses. It was only after securing this endorsement that venture capitalists became interested. And Apple wasn't the only company to get public money. The development of Google's search algorithm - the very core of its business - was funded by the National Science Foundation, and it's likely that Elon Musk's companies would struggle without the billions they receive in public subsidies.

It's clear that Silicon Valley's thought leaders significantly discount the importance of public support to the innovations that its companies depend on. Instead of being thankful for government initiatives, the rising power of tech has corresponded with a renewed effort by corporations to minimize the amount of taxes they pay, and that greed is threatening the continuation of this virtuous cycle.

Tech Companies Are in It for Themselves

Over the past few decades, the major tech companies have led the way in developing schemes to reduce their tax burden by setting up various shell accounts and subsidiaries in tax havens around the world. Eric Schmidt even bragged that he was " very proud " of Google's tax-avoidance schemes, which he considers a central constituent of modern capitalism.

However, as a result of increased tax avoidance and the slashing of the corporate tax rate by successive governments over the past several decades, the amount of taxes paid by corporations has significantly declined both as a percentage of government revenue and as a percentage of GDP. This may seem like a positive development to corporate executives, but what it really means is that less money is available to fund the programs that are key to supporting small businesses and funding important research projects that lack a clear road to profitability.

And whether or not tech libertarians want to admit it, that's a big problem. The right loves to say that the government shouldn't pick winners, but the reality is that it has a pretty good record of picking the right ones. In a review of Mazzucato's book, Jeff Madrick acknowledges that "including Solyndra, only roughly 2 percent of the projects partly financed by the federal government have gone bankrupt."

There's also an important distinction to make between private venture capital and the kind of support the government can provide. Venture capitalists rarely want to get involved at the early stages of a project when the prospect of return on investment isn't clear. They prefer to wait until much later, when they can provide short-term support that will pay back within a few years. Public funding, on the other hand, usually supports research at a very early stage, when risk is much higher, which is why it was so important in the development of the foundational technologies of the Internet age.

With Great Profits Comes Great Responsibility

Even though corporate giants are paying less in taxes, they're not trying to replace the functions served by public dollars. Instead of investing more of their money in R&D, they're sitting on record cash piles - Apple's stands at more than $260 billion - which they're increasingly spending on stock buybacks and dividends to artifically boost their share price, making their executives and wealthy shareholders even richer.

The public money that funds scientific advancement and technological innovation has been essential to human progress. Whether it's optical storage, microchips, communication satellites or wind and solar technologies, the discoveries that drive our world forward are a result of the long-term investments that only the government dependably provides.

There's no denying that corporations benefit immensely from this public spending, just as Apple did with the creation of the iPhone. And there's no problem with that. The problem arises when those same companies reap the rewards while trying to avoid the responsibilities that come with them.

The only way this will change is by countering the lies of Silicon Valley libertarians, educating people about the importance of public research funding and showing them how tech companies make enormous profits from public investments while use mind-numbing schemes to reduce their own contributions. As Apple announces its new iPhone, it's worth wondering whether a company that has benefited so much from public investment is really worth our support when it's hoarding billions of dollars offshore just to avoid paying US taxes. I'm not sure about you, but that doesn't sound like good corporate citizenship to me.

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Love Your iPhone? Don't Thank Apple. Thank the US Government.

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Without public research funding, there'd be no iPhone - which makes Apple's relentless tax dodging even more whack. The iPhone has changed so much about how we live and interact with one another that it's hard to believe that the original iPhone went on sale just over 10 years ago, popularizing the concept of the smartphone.

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okay i'm always skeptical of people being like "oh there's no more alternative culture anymore" but AS JOHN WATERS SAID (in ref to their outfits but) doesn't the new alt culture include hackers? like v much based on the same anti-corporate stance, but they just don't SEEM as cool/edgy??

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Though I barely qualify as a millennial - I was born in 1982, a year after the Pew Research Center sets the cutoff, and right on the cusp according to the U.S. Census Bureau - I have to confess that I have long savored my classification. I enjoy being the subject of thinkpiece after thinkpiece about phones, debt, political leanings; part of the the generation destined to destroy everything from napkins to Applebee's. But according to this Huffington Post article, which went viral last summer, I am not actually a millennial after all but a "xennial" - part of a microgeneration between Gen X and millennials that combines their governing attributes, Gen X "cynicism" and milliennial "striving."

Defining generations has always struck me as like astrology - a potential conversation starter that shouldn't be taken too seriously. But one "xennial" periodization struck me as too apt to ignore: analog childhood, digital adulthood. My adolescence coincided with the adolescence of the web, between its infancy as a preserve of academics and geeks and its mature ubiquity as social media (or now, "platforms"). Both unfolded in a decade that itself seems liminal, hard to pin down: the 1990s. Between the conquest of neoliberalism and the onslaught of neoconservativism - for some, a time of flannels and the other trappings of "alternative" culture but for me the time of the internet. As major media corporations quickly determined the most effective methods for presenting the latest dissident music culture, I'd discovered an impossibly labyrinthine digital alternative, full of parody, pranks, and politics that MTV and the Gap seemingly could never conquer. And though digital culture has never yielded an unconditional surrender to commerce and conformity, something else has happened: The internet's ways became the foundation for all forms of expression, from "culture jam" to culture, period.

The internet was important to me then because I experienced it as an escape from provincial Ohio - as an extension of the books, movies, and music that already served this purpose. But media was also my home. My suburban ennui was inextricable from the full-spectrum dominance of mass commercial culture; the television was always on. Though I watched quite a lot of it, I understood that television was my enemy. So the brief times I got to experience something different - the occasional trip downtown to the art theater or the indie record store - felt like unchecked rebellion, even if that rebellion was just another act of consumption.

Television had been under suspicion since it infiltrated American homes in the 1940s and '50s, but the '90s were a great time to hate it. Bolstered by deregulation and the expansion of cable, it had never seemed more powerful or more deeply loathed. A mere decade after TV journalists had been credited with turning public opinion against the Vietnam War, television news had become a problem, not for what it reported but by sheer virtue of its form, which was seen as inherently open to manipulation and hostile to substantive facts. As political journalist William Greider wrote in 1984, "whatever the newspapers printed about Reagan, no matter how harsh, became almost irrelevant; only the pictures really mattered." While Noam Chomsky meticulously detailed the way capitalist media companies and the state could construct a propaganda apparatus within a democracy, brasher voices blamed television for unleashing America's basest elements: "Ronald Reagan is merely an anthology of the worst of American popular culture, edited for television," wrote media critic Mark Crispin Miller. "Reagan won because he was the perfect television spectacle."

All the concerns of academic postmodernism - the depthlessness of image-based culture, the end of grand meta-narratives in favor of the fragmentary, the loss of historical context and the rise of self-referentiality and intertextuality - could be detected in the distraught reaction to a decade of Reagan's rule. Guy Debord's claim, in the 1967 book The Society of the Spectacle, that "everything that was directly lived has moved away into a representation," seemed to ring ever truer, and Jean Baudrillard, who became a touchstone for cultural criticism then, took this further, diagnosing the Western world as a "hyperreality" where representation had, in folding in on itself, mushroomed into an expanded universe that referred, ultimately and unverifiably, only to itself.

If we are trapped in a world of representations of representations, than what is to be done? In 1993, the year before I got online, writer Mark Dery penned a manifesto of sorts that addressed this question: " Culture Jamming: Hacking, Slashing, and Sniping in the Empire of Signs." Dery reconceived the totalizing mediascape as a kind of battleground and, following semiotician Umberto Eco, theorized a new kind of political actor: "communications guerrillas, who would restore a critical dimension to passive reception" by making parodic versions of pop culture, corporate logos, and advertising slogans. Rather than completely sabotage the signal - think Roddy Piper blowing up the aliens' mind-control device in John Carpenter's 1988 film They Live - culture jammers intervened in the flow of media, détourning it as Debord's Situationists had advocated, to inculcate viewers with a critical perspective on media.

Dery's manifesto was not simply a call to arms, but a diagnostic that tried to knit together an assortment of contemporary aesthetic practices into an oppositional movement. Those practices, however, had already begun to crystallize under a different banner, the flimsy and seemingly self-negating term "alternative."

As nationwide circuits for punk re-emerged, with Sonic Youth and then Nirvana as flagships, the concept of alternative was more and more frequently invoked but remained notoriously difficult to define. This was a running joke at the time: "Alternative to what?" was the obligatory rejoinder.

Even with the benefit of academic hindsight, "alternative media" has remained too baggy to hem in. Mitzi Waltz's book on the subject, Alternative and Activist Media (2005), notes that it refers first to "media that provide a different point of view from that usually expressed, that cater to communities not well served by the mass media, or that expressly advocate social change." It was defined by what it negates, which, as Waltz notes, means that "alternative media are 'alternative' only in the context of their response to, and participation in, the cultures within which they are produced and consumed." Rather than articulate a clear vision of, say, a radically reorganized society, alternative is cursed to indicate the locus of rebellion but without anything programmatic following behind. In the context of a totalitarian mass media apparatus of the 1990s, this kind of reactionary inflection point felt significant enough. But as soon as the ground underneath shifts, that raison d'être disappears.

What it leaves behind is, often enough, little more than a sneer, a prank. The continual impulse to negate that was intrinsic to alternative revealed itself in the ironic pose and reflexive sarcasm so forcefully pinned to Generation X as its major cultural contribution. The mixture of radicalism bereft of seriousness is perfectly encapsulated by Sonic Youth guitarist Thurston Moore's pastiche performance of a left intellectual in the tour documentary 1991: The Year Punk Broke: "I think we should destroy the bogus capitalist process that is destroying youth culture," he babbles to some gobsmacked German fans. "The first step is to destroy the record companies. Do you not agree?"

Yet even without concrete precepts, other than perhaps a vague commitment to the ethos of "Do It Yourself" - what we now call, in its fully commodified form, "artisanal" - there nevertheless seemed to be something in the air. In 1993, Jürgen Habermas, the ur-theorist of the public sphere, was provoked to modify his view that the public sphere would inevitably be colonized by capitalism, positing instead a "periodically recurring violent revolt of a counterproject to the hierarchical world of domination, with its official celebrations and everyday disciplines."

The early internet seemed like a perfect example of this revolt, an ideal setting for the apparently anti-corporate media criticism of alternative culture. Dery notes this with enthusiasm, enlisting alternativity as part of the web's natural structure: Online space was "interactive rather than passive, nomadic and atomized rather than resident and centralized, egalitarian rather than elitist." Again, the implicit foil here is television. The problem of TV was that it was seen as structurally producing a unidirectional and passive consumerist subjectivity. You watched what others chose to show you, or chose among their choices. But the web was something else: an unruly, unmappable mess that required tenacity and creativity to navigate, especially before the development of search engines. The web cultivated a researcher's élan: Do a deep dive through a "rabbit hole" of links, and you might be rewarded with the treasure of truly eccentric content. (I'm still addicted to that feeling.)

Caught up in its radical difference from established media, many a media scholar temporarily shelved any antipathy to technological determinism and embraced rhetoric about the web's inherently egalitarian and non-hierarchical nature. Yet if the web made for an alternative public sphere, this did not come about automatically as a consequence of its technological differences. Rather, it was a product of how people made their way through its networks and responded to the battles that flashed across its landscapes. That is, this alternate public sphere developed as a historical phenomenon.

One way the internet built a set of alternative media and cultural practices was through the practical demands going online made on would-be users. Like the punk scenes that flowed into alternative music, the early web was DIY, both by choice and by necessity, a kind of sprawling folk creation that artist Olia Lialina has dubbed "the vernacular web": "bright, rich, personal, slow and under construction." Corporations went online sluggishly and cautiously, which meant that much of the work of designing the web and filling it with information was left to amateurs and hobbyists. If you, like me, wanted to look up Nine Inch Nails lyrics, you had to go to someone's meticulously (and likely poorly) crafted fan page. Official sites, if they existed at all, tended to hold back the good stuff anyway. What was one corporate-sanctioned background wallpaper and some old tour dates compared with a trove of lovingly hand-scanned images and arduously compiled discographies, compiled and given away freely by a fan just like you?

Second, there were real conflicts between corporations and the new capabilities being explored on the web. Many of the internet's early adopters - programmers like Eric Raymond and Richard Stallman - had cut their teeth in the fight for free and open-source software and bequeathed to web culture an extensively articulated antipathy to copyright, which aligned with the art pranks of the early culture jammers. But this indifference to intellectual property extended beyond politicized rebels to anyone self-publishing online. The cease-and-desist notices sent to X-Files devotees, Harry Potter fanfiction writers, and even the tender souls with pages hosting images of Disney characters spoke to how quotidian the fight against corporate control and intellectual property could be online.

This politicization of copyright forged a strange alliance between those enthralled to the avatars of mass culture and those who sought to undermine them through parody. But at the time it made perfect sense. The web's homespun aesthetics - the irreverence for professionalism contained in every gaudy color choice and trademark-flaunting Tinkerbell gif - came to signify, like the deliberate rawness of alternative music, a proudly adversarial culture. Among my earliest online activities were downloading a bitmap of the AdBusters " Corporate States of America" flag, and reading all manner of rough-and-ready cultural criticism, from reviews of Aphex Twin albums to rants about the vapidity of MTV. Soon I would be writing these sorts of things myself, posting them to my own ramshackle Geocities page. In its most heroic form, this online alternative media meant sites like muckraking anarchist infoshops, some still producing new anti-authoritarian FAQs after all these years. If we're being honest, though, the major players at the time were shock sites like Rotten.com, which drew relatively huge audiences for its outrageous images without any of the apparatus of built-in likes and automated feedback loops that now makes for viral culture.

But the occasional Goatse was the price we paid for liberty: Extreme anti-authoritarianism and pornography have traveled arm in arm since at least the libelles that scandalized France's ancien régime. After all, the internet was a frontier, as J.P. Barlow told us, and its rugged independence needed defending. The prophylactic web offered then by America Online presaged a web of safe and bland curation, of filters and restrictions, and so it was attacked in a thousand ways - rhetorically, of course, but more directly as well. A popular and rather easy-to-use set of hacking tools, AOHell, let even a novice script kiddie wreak havoc (more properly spelled HaVoK) on the gentler sorts just beginning to participate on the web, knocking newbies offline and flooding chat rooms with vulgar ASCII art. AOL's merger with media conglomerate Time Warner proved the righteousness of our cause.

This kind of culture jamming was part of a defense against the intrusion of dreaded corporations, with their standardization, censorship, and perceived paternalistic approach to culture. But it was also the mark of a subcultural elitism. In meatspace, I was an unfashionable nerd, but online I was part of a thriving subculture where my outré tastes were acknowledged, and celebrated. And this, as much as anti-corporate rebellion, was a major attraction of dissident digital culture: It was a source of identity and status. This is the same mechanism that transformed the lackadaisical slackers of the alternative 1990s into the sneering hipsters of the indie 2000s. It is also, to some extent, what transformed niche gamers into the frothing swarms of Gamergate.

Of course, the pre-corporate web is gone, enclosed into a handful of proprietary platforms where our digital activity can be rationalized and monetized. Our free-ranging through shabby websites have been replaced by algorithmically curated feeds of standardized posts. But my point is less to mourn the death of the open web than to confront how the political valence of the normative ideals it embodied - an independent, homemade, anti-commercial "alternative" culture with a flippant orientation toward established media - have shifted. As the web was emerging from its adolescence, these ideals seemed inherently "progressive," to use a shopworn term, but they have quickly deteriorated. Now they are suspect. What changed?

The internet did conquer the "dinosaurs" of old media. But rather than culturally jammed, the old media were economically disrupted. In their own grand act of appropriation, two platforms, Facebook and Google, snatched up the revenue sources of old media by seizing upon their product - the ability to deliver demographically aligned stables of data-producing consumers (a.k.a., us) - and supercharging it. We've got identity now, too much of it. Social media jacked the old media's mass audiences and remixed them into targeted micro-demographics. The data analytics company YouGov tells me that Sonic Youth fans tend to be male, urban, Democrat, and earn six figures. One in five work in advertising and marketing. Truly, no alternative here.

Online interactivity has been limited to a few large sites oriented toward advertising and shopping. Scrolling through your feed - the word itself conjures a pig's trough - feels more like flipping through channels than surfing the web of yore. What once seemed like the birth of an interactive and participatory new media environment has shifted to an ostensibly more consumer-friendly (and more scrutinized) method of watching television, and today's cultural critics, rather than condemn television, help us use our high-speed connections to select which shows to "binge" on.

But beyond the conquest of digital cool, the internet, which not so long ago was viewed as having helped elect the U.S.'s first black president and spread " democratic revolutions " across the world, is now blamed for stoking the flames of dangerous right wing populism. Specifically, it is the techniques of culture jamming that, rather than show us a way out, have come under fire for bringing us to this point. Indeed, if culture jamming has an apotheosis, it was the 2016 election, where memes, hacking, conspiracy theories, infodumps, and pranks consistently scandalized the media and galvanized support for the alternative outsider candidate, who happened to be a billionaire game show host.

In the wake of Trump's win, media hoaxing - "culture jamming in its purest form" according to Dery - has become the pernicious "fake news" that nudged voters into the arms of a dangerous incompetent. Trump was even able to détourn establishment media's criticism of reactionary propaganda and turn it against them, making "fake news" a rallying cry for his supporters against CNN and the New York Times. And one has to admit that 4channers convincing people that Hillary Clinton was involved in a child-sex-trafficking ring run out of a pizza place is not miles away, in form, from the famous culture-jamming antics of the Yes Men, who have printed and distributed thousands of imitations of the New York Times and the New York Post.

During the election, all-volunteer cadres of racist meme warriors weaponized alternative aesthetics until even Hillary Clinton felt it necessary to publicly acknowledge Pepe the Frog, a character appropriated from underground comics, as a white supremacist symbol. In one of the purest examples of the inversion of the old values of the web, the cartoon's creator, Matt Furie, has leaned on his intellectual property rights to issue DMCA takedowns of unauthorized uses of the frog.

In this truly topsy-turvy world, "alternative" has been truncated and appended to "right," where irreverent appropriation is thriving. The style guide for "alt"-Nazi outlet the Daily Stormer boils down culture-jamming techniques to their essence. Rather than write news stories, Stormer specializes in reappropriation and recontextualization, deliberately modeled on snarky liberal sites like Gawker, with the goal to "hijack culture" and "co-opt the perceived authority of the mainstream media." Rather than weighty sturm und drang, these fascists strive for a light and irreverent tone: "we rely on lulz." The Stormer 's founder, Andrew Anglin, hails from the same Ohio suburb as I do. I might have run into him in the halls of my high school, but he attended the alternative program.

The alt-right cultivates a desire for an idealized past where white supremacy and patriarchy were more firmly entrenched, an aspiration unremarkable among American conservatives - normie - but for its lulzy vulgarity. Since Trump, though, a parallel nostalgia has risen on the shell-shocked #Resistance: a yearning for the past of Big Media. When political theorist Francis Fukuyama, who has taken aim at "postmodern relativism" for decades, despairs over the internet's ability to "liberate us from gatekeepers" of authority, it comes as no surprise. But when Joan Donovan, a researcher from the tech-savvy Data & Society think tank, reproduces Fukuyama's criticism almost exactly - "we have few gatekeepers and we've meshed all of the different ways in which we consume reality" - something has changed.

For critics like Jackson Lears, the post-election obsession with internet-based disinformation offers a convenient scapegoat for Democrats unwilling to confront their political failures. But it reveals something else: a complete reversal of the 1990s sensibilities that yearned to leave stodgy Big Media verities behind and valued a subversive and jocular underground media. So powerful is this reversal that it has produced the surreal spectacle of reverence for the New York Times, whose deceptions and collusions with the Bush regime, as Lears wryly notes, facilitated the Iraq War, and for the Washington Post, that illuminator of democracy now owned by Amazon's Jeff Bezos, one of the wealthiest and most exploitative employers in the country.

Those who awoke on November 9, 2016 and found themselves in a nation they no longer recognized reached for old stabilities and comforts - for those who might once again keep the gates. Even Clinton partisan Peter Daou's much-mocked platform Verrit, which promises to verify each of its talking points with a numeric code, speaks, in its clumsy fashion, to the yearning for stable truths and trustworthy institutions, even as its own bizarre recursivity comes off as the kind of knotty joke a culture jammer might play. (Facebook has recently unveiled a similar system but, in keeping true to their business model, has outsourced the work of authentication to their users.)

In short, we wanted off the frontier. We wanted the state back. We wanted its protection from hackers (especially Russian ones); we wanted its legal concepts of property, expression, identity, movement, and context; we wanted it to regulate Facebook and Google in ways we can barely articulate. We wanted to call our congressperson on the phone because it's more "meaningful" than email. We wanted an end to anonymity. We wanted God. We wanted big media. Hell, we wanted IBM and ITT and AT&T and Union Carbide, if only they'd have us.

Once, not long ago, critical media scholars told us to jam culture for the sake of good. Now when we spread an obvious parody on Twitter, we are part of the problem, demonstrating "people's willingness to suspend disbelief and their susceptibility to confirmation bias." In the wake of Trump's election, intellectuals and politicos have not enjoined us to create a "counterproject" media sphere to combat hegemonic ideology. They have not told us to hack, snipe, poach, or otherwise take to the semiotic hills to wage guerrilla war. Instead, we've been told to bolster capitalist media: to subscribe to the New York Times, to dutifully consume advertisements by whitelisting our favorite sites, to obtain our music from commercial platforms - so the artists get paid, of course.

Before, in the 1990s, one radical solution was finding means of creating more critical, combative, active media consumers and expanding the range of perspectives on offer. "Alternative" was, it seems to me now, itself a kind of insufficient consumerist prerogative, a demand for more choices that was agnostic to the content of those choices. It certainly left room for the reactionary alternative media we have today, which exploits as an alibi the reflexive ironization that the '90s avant-garde used to obfuscate its aims and seduce outsiders: Poe's Law as a weapons-grade version of alternative culture's skepticism of earnestness.

But the rush back into the arms of establishment media seems like another kind of problem. It speaks to another simple solution, that the solution to Trump's careening demagoguery is a return to the neoliberal technocracy and its officially sanctioned ideologies. It is a desire for a narrower world where corporations promise to, once again, produce a stable sense of shared reality through mass culture. If the world cannot be better, it can at least be predictable, the way television was. The new alternative is no alternative, again.
This essay is part of a collection of essays on the theme of ALTERNATIVE. Also from this week, Adam Clair on the alternative channel of loneliness.

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Though I barely qualify as a millennial - I was born in 1982, a year after the Pew Research Center sets the cutoff, and right on the cusp according to the U.S. Census Bureau - I have to confess that I have long savored my classification.

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all of this is bizarre and weird but what about the bit that is like "when ur taxi driver tells u to buy, u should sell" WEIRD forms of hierarchies there and VERY MUCH BASED on profit maximization don't think i like that

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Image: Flickr/Aranami. Composition: Jordan Pearson
Jackson Palmer is an Australian entrepreneur and technologist best known for creating the infamously successful "joke" cryptocurrency Dogecoin. Currently based out of San Francisco, Jackson works as a product manager but is still active in the cryptocurrency space. Jackson has holdings in various cryptocurrencies, including less than $50 worth of Dogecoin. You can follow him on Twitter and Read More: Such Weird: The Founders of Dogecoin See the Meme Currency's Tipping Point
When I jokingly tweeted about "investing in Dogecoin" in late 2013, I never imagined that the tongue-in-cheek cryptocurrency I had just brought into the world would still be around in the year 2018, let alone hit a $2 billion market cap like it just did over the weekend.

Last year saw an explosion of interest and investment in cryptocurrencies across the board, so it's tempting to see 2017 as the best year to date for the industry. But I feel it is shortsighted to mistake this explosive growth as being sustainable-in fact, I feel 2017 was arguably the worst year for cryptocurrencies yet. To understand why, let's revisit what I learned from the currency I created as a joke.
Read More: The Guy Who Ruined Dogecoin
Dogecoin started as a parody of the multitude of alternative cryptocurrencies, or " altcoins," flooding the market at the time. As interest in Dogecoin grew through social media and an active Reddit community, it went on to become an educational gateway for many people dipping their toes into the world of cryptocurrencies for the first time, thanks to its low price and welcoming community.

In 2013, the vision for the future of cryptocurrencies seemed relatively clear: To deliver a peer-to-peer alternative to cash that, through decentralization, did away with the need for trust in financial institutions, which the 2008 crisis showed to be unscrupulous, and often corrupt. Bitcoin, which ignited the cryptocurrency movement in 2009, brought real technical innovation to the table in achieving this vision. Back then, I hoped that through the power of community, a project such as Dogecoin may help drive further awareness of and innovation in that technology.

However, as I quickly learned, a passionate community of people throwing around money is like blood in the water to the shark-like scammers and opportunists who, in late 2014, co-opted the Dogecoin community and fleeced its members for millions of dollars.

By 2015, the energy in the community had changed-those who got burned by the scammers began to disappear and the community's interest in Dogecoin declined, as did its price in US dollars. At the same time, confidence in Bitcoin was shaken: hacks and scams dominated the news cycle, and merchant adoption failed to grow at forecasted rates. Despite these events, huge sums of venture capital continued to pour into fresh cryptocurrency companies backed only by buzzword-laden websites and lacking any discernible business model.

In light of all this, in 2015 I decided to back away from any involvement in Dogecoin and cryptocurrency in general. I handed development of Dogecoin over to a team of community members that I trusted. I made it clear at the time that any Dogecoin I previously held-the small amount I have now came from people " tipping " me after I left-had been sent to charity drives run by the community, and that I'd made zero profit from my involvement with the project.

I saw the space being overrun by opportunists looking to make a buck, rather than people investing in evolving the technology (which, even back then, we knew was facing real technical issues.) Over the following two years, I monitored the space from afar. What I noticed was a shift away from developing the core technology powering these networks to churning out shiny new projects that shoehorned in "blockchain" wherever possible.

There is a popular saying in financial markets along the lines of, "When your taxi driver is telling you to buy stock, you know it's time to sell." Basically, when a stranger with (presumably) little experience in the stock market is giving you tips, it's an indication that the market is too popular for its own good. Having been out of the cryptocurrency space for two years, in early 2017 when my Uber drivers started talking to me about Ethereum, I knew we were entering a renewed period of speculative crypto-mania.
Read More: A Trip to Dogecoin's First Conference
No trend better exemplified this than the "ICO," or Initial Coin Offering. In 2017, thousands of fledgling companies collectively raised over one billion dollars ( one ICO alone raised $700 million in December) in exchange for virtual "tokens" which buyers could then trade immediately on a secondary market-often for a large profit. I began having flashbacks to the scams from the Dogecoin days. For example, a token called PlexCoin raised nearly $15 million in an ICO last year before Canadian and US regulators froze the creator's assets and a Canadian court sentenced him to jail.

These concerning observations have led me back into the cryptocurrency space to help educate my co-workers, friends, and family who are asking me if they should pour their money into cryptocurrencies. Hopefully, if I do my job, they will better understand the potential pitfalls of doing so.

Over the past year we've seen the collective market cap of all cryptocurrency assets balloon to more than $700 billion USD, largely because of speculative trading. Everyday, it seems there is a fresh news article about the 20 year-old who became a millionaire in Bitcoin. Or in the case of my own creation-Dogecoin-how a currency that hasn't received a software update since 2015 briefly passed a $2 billion market cap ($1.5 billion at the time of writing).

Dogecoin's valuation is the result of market mania that has resulted in inexperienced investors buying up low-priced assets on a whim, hoping that they will follow Bitcoin's meteoric trajectory. This irrational enthusiasm, coupled with large players manipulating largely unregulated markets, has resulted in a weekly cycle of rallies and crashes across just about every crypto asset. While the Dogecoin community on Reddit has seen a recent uptick in participation, the majority of new discussion seems to fixate on the USD price and speculation as to when it will rally once again.

It's great to see mainstream excitement about cryptocurrency, but the continued focus on price and potential to "get rich quick" distracts from the laudable goals that projects like Bitcoin set out with. Even more importantly, the underlying technology is still facing technical challenges related to scaling that need to be addressed. At the time of writing, it costs an average of of $30 to send any amount of money using the Bitcoin network. At the same time, a token that touts itself as "the blockchain solution for the global dental industry" has just surpassed a $1 billion market cap. Something isn't right here.

While FOMO-driven amateur investors rush to invest in the next "blockchain for x" ICO hoping for a 100 percent return, merchant adoption of Bitcoin is reportedly decreasing to its lowest level in years. Recently, major players like Microsoft and video game marketplace Steam removed the option to pay in Bitcoin from their online stores.

At the same time, it seems like Bitcoin's original anti-establishment principles are being diluted even further. We're seeing money pouring into the industry from large institutional traders, and Bitcoin futures contracts-basically betting on whether Bitcoin's price will go up or down- have begun trading on Wall Street. Which leaves me asking: what happened to removing the supposedly corrupt financial institutions from the table?

Given the immense price increases and media hype, there's a tendency to see 2017 as the best year for cryptocurrencies yet, but I would argue the opposite. In many ways, 2017 marked the year that cryptocurrency stopped being about technologically innovative peer-to-peer cash and instead essentially became a new, unregulated penny stock market. 2017 was also the year that the very institutions Bitcoin originally sought to dismantle have begun to co-opt it for profit.

Still, I can't concede that it's game over for cryptocurrencies. It's difficult to predict how much the current crypto bubble will inflate, or when it'll burst (not if). The burning question on my mind is this: Once the cryptocurrency price bubble pops and takes all the hype with it, will the community be able to recover the energy it needs to build real, innovative technology once again?

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My Joke Cryptocurrency Hit $2 Billion and Something Is Very Wrong

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Image: Flickr/Aranami. Composition: Jordan Pearson Jackson Palmer is an Australian entrepreneur and technologist best known for creating the infamously successful "joke" cryptocurrency Dogecoin. Currently based out of San Francisco, Jackson works as a product manager but is still active in the cryptocurrency space. Jackson has holdings in various cryptocurrencies, including less than $50 worth of Dogecoin.

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"Amazon isn't evil, it's just very good at capitalism...Who designs the technologies that shape our social relationships? How does the value generated through consumers’, workers’, and owner activities get distributed? How do we change the algorithms and logistics processes that clearly do not serve the majority of us? "

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1-Click ordering a massively discounted flat-screen TV, or seventy pounds of coarse-grained salt, it can be easy to forget, or temporarily repress, all those stories you've read about, say, working conditions in Amazon's warehouses, or its propagation of the gig economy through contract labor.

The same applies, of course, to Uber rides, or Big Macs. But Amazon seems to have a particularly ubiquitous grasp on the average American wallet. Which gets one thinking, is Amazon just another massive corporate entity to feel a vague sense of guilt about giving your money to? Or is it actually evil? And-if it is evil-does that make you evil for using it?

For this week's Giz Asks, we asked a broad spectrum of experts-philosophers, business professors, lawyers, heads of nonprofits and policy resource centers-to weigh in on those questions. What ensued were wide-ranging discussions on the nature of evil, capitalism and consumer-level action and responsibility. If you're a Prime member, or Jeff Bezos, you might be pleased to hear that, despite the tax-dodging and predatory pricing and labor exploitation detailed below, our experts were for the most part hesitant to saddle Amazon with that particular word-but then, there's a difference between being "not evil" and "good."

Charlotte Garden
Associate Professor, Seattle University School of Law

Evil suggests something outside of the norm, and-unfortunately-I don't think Amazon's labor practices qualify as that.

Amazon (and e-commerce generally) shifts employment from brick-and-mortar retail stores to warehouses. Warehouse jobs often pay better than retail store jobs, but they are also more geographically concentrated and skew more towards men and the non-disabled. So an Amazon warehouse near your city could mean more local jobs (though even that is disputed)-but if you live in a rural area far from an airport, you're never going to get an Amazon fulfillment center, even as Amazon makes it harder for your local stores to survive.

There's also the kind of jobs Amazon is creating. Warehouse work is always hard work, but there are major differences between working at an Amazon fulfillment center and working in a unionized warehouse with full employer-paid health benefits and for-cause protection from firing. And, if Amazon's new patents for a wearable monitor that tracks how quickly workers are moving is anything to go by, things are likely to get worse unless Amazon workers and consumers demand that they get better.

Improving working conditions at Amazon (and companies like it) is going to take collective pressure. That could come in the form of a union drive at Amazon warehouses, but it could also come from Amazon's customers. Amazon isn't immune to public disapproval-for example, it only took a day after a journalist reported that Amazon was requiring seasonal warehouse workers to sign non-compete agreements for Amazon to drop that requirement.

I understand (from first-hand experience) why people use Amazon-it's a time-saver, and people lead busy lives-so I won't criticize Amazon shoppers. But if you have the bandwidth to re-direct your purchasing dollars, locally owned business and larger unionized stores (like Costco) would surely appreciate it. Maybe even more important, support good jobs policies, and demand that state and local agencies charged with enforcing labor standards be adequately empowered and funded. Finally, states and municipalities often give tax concessions to lure Amazon fulfillment centers; citizens could call for them to be made contingent on improved wages and working conditions. There is room for improvement, if we demand it.

Lilly Irani
Assistant Professor, Communication, Science Studies, Design Lab, UC San Diego

Amazon is not evil. It is just very, very good at capitalism. And we have a system of social organization that rewards them for squeezing workers, promising a fully automated future for the financial markets, and replacing brick and mortar as it careens towards monopoly. Amazon's crowdsourced data processing system, Mechanical Turk, puts thousands of data processing workers at the disposal of AI and Machine Learning engineers. But Amazon, like Uber, Lyft, and Microsoft before it, employs these workers as independent contractors who earn a median wage of $2/hour. Amazon's warehouses choreograph workers to the rhythms of robots who move products as far as they can before human dexterity comes into play. Amazon managers, working for efficiency, speedy delivery, and cost reduction, push these workers harder and harder- tracked by the scanners they use as they pick and box-for as little money as the law and enforcement officials allow. And Amazon now owns Whole Foods and experiments in surveillance and AI driven retail with Amazon Go stores. But as internet users, we have no effective say in how the data we generate on company platforms get bought, sold, and used. We have no say in how companies engineer our attention, change our work processes, cultivate our consumption, and steward our histories.

To call Amazon evil is to make the problem a moral problem. Many of Amazon's tendencies, however, are not unique to the company, to tech, or to business. I worked at Google for four years; Google also used hidden, underpaid workers and oceans of our data to monetize our lives. And its motto was "Don't be Evil." Evil is not the problem. Lack of democracy is. Who designs the technologies that shape our social relationships? How does the value generated through consumers', workers', and owner activities get distributed? How do we change the algorithms and logistics processes that clearly do not serve the majority of us? Compassionate, moral CEOs and corporate social responsibility cannot address the scope of the problem. There is always a more efficient, ruthless, and creative company that can come along and supplant the ethical ones. When we're talking about evil, we're actually talking about capitalism and how it directs our technological futures when there is no opt out.

We need to support workers' organizations and consumer unions that scrutinize technological claims on behalf of people, not investors, CEOs, and consultants. We need to look beyond Universal Basic Income and its implied assent to the automation of whatever companies find convenient; income alone does not ensure access to health, education, and information for all. If you're a tech worker, join the Tech Worker Coalition or Tech Solidarity. We need political movements that create policies, laws, and institutions that put us in charge of our technologies.

Greg LeRoy
Executive Director of Good Jobs First

Yes, Amazon is evil. It's aggressive about dodging taxes, and about getting everyone else to subsidize its inevitable growth through tax breaks. Amazon's original business model involved legally dodging the obligation to collect sales taxes, and then using the resulting price advantage to gain market share. It did this by locating its first warehouses in very few states, most of which do not have a sales tax, and then shipping its goods to customers in all the other states that do tax retail sales. This enabled Amazon to not have "nexus" in sales-tax states, so those states could not compel it to collect the tax.

But after Amazon created its Prime membership and that model evolved towards next-day and even same-day delivery, Amazon could no longer avoid nexus. It was also getting pursued by some states for skirting the rules; Texas alone came after it for $269 million in uncollected sales taxes. So in 2011, apparently realizing it would now have to build warehouses in or near every major market with lots of Prime customers (and more than half of U.S. households are said to be Prime members), Amazon started caving on the sales tax issue. But it also realized it could get economic development subsidies to "create" new jobs (even though e-commerce jobs grow at the expense of bricks-and-mortar retail jobs)... In [2012] alone, Amazon pulled down 21 tax-incentive deals for its warehouses and cloud-computing data centers (Amazon Web Services). And it has been on a tax-break jag ever since, getting at least 24 more last year alone-even though its business model requires it to have all these fulfillment centers! All told, we've identified $1.39 billion in 136 such subsidy deals given to Amazon, with the full costs of several remaining undisclosed as Amazon has tried to become more secretive about them.

Shannon Vallor
William J. Rewak, S.J. Professor, Philosophy, Santa Clara University and author of Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting

Ever since Google formulated its original 'Don't be evil' motto, too many conversations about technology ethics have devolved into the simplistic dilemma of 'good vs. evil,' which is not the most helpful or constructive ethical concept to work with. 'Evil' is that which we have decided lies outside the boundary of the moral community. You don't reason with evil or apply ethical pressure to evil, you denounce and abhor it, and do whatever you can to neutralize its power and protect others from it.

So: is Amazon evil? Is Amazon outside the boundary of the moral community, something to be utterly despised and excluded? No, and that's not the most helpful way to frame the problem of Amazon's failure to fulfill its responsibilities to the larger society of which it is a part. Nor does it make sense to single out Amazon and not the litany of other large corporate actors that also frequently fail to uphold their part of the social contract. That said, it does make sense for voters and customers to call them to account. This can only really be done by fundamentally changing the incentive structures of our economic and political systems, so that corporations like Amazon incur real, meaningful costs when they evade their ethical responsibilities and act as 'free riders' on society-profiting and drawing public resources from the social fabric that makes their existence possible without paying enough in taxes to sustain that fabric, or without repairing the social wear and tear that results from their own activities.

Does that mean that an individual who continues to patronize Amazon is 'evil'? Again, that's not a helpful category. As long as the socioeconomic order continues to reward unethical actors and punish or neglect ethical ones, then the effect of such strategies, however ethical, will be limited. What is really needed is a political sea change.

Stacy Mitchell

Co-Director of the Institute for Local Self-Reliance

The relevant question is not whether Amazon is "evil." (It's not.) It's whether we should allow Amazon to entrench itself as the gatekeeper to the consumer economy-or use our antitrust laws to check its power and insist on an open and competitive market.

To understand the nature of the threat Amazon poses, it's important to stop thinking of the company as a retailer. Amazon's strategy is to own the infrastructure that other businesses rely on to get to market. Because most online shopping searches now start at Amazon, rather than at a search engine, virtually every retailer and manufacturer that wants to reach people online has little choice but to set up shop on Amazon's platform.

The obvious problem here is that Amazon competes with these same companies. Studies and reporting show that Amazon exploits their dependence to undermine them as rivals. According to Harvard Business School research, for example, when sellers list new products, Amazon monitors their transactions and begins selling their most popular items itself.

We've been here before. There was a time when powerful industrialists gained control of the railroads and exploited that control to limit their competitors' access to market. Americans responded by using antitrust laws to break up the railroad trusts and stop their anti-competitive behavior, and that's what we need to do now with Amazon.

Doing so would safeguard the web's inventiveness and the economy's dynamism by ensuring that businesses have a chance to emerge and grow without being stifled by a dominant Overlord-especially one who has a taste for the villainous photo-op.

David Larson
Senior Fellow, Dispute Resolution Institute and Professor, Mitchell-Hamline School of Law

You think about economic philosophers, and you go back to utopian socialists and Marxists, who would say that capitalism in itself is evil and anybody that participates is therefore evil. Then you have things like the US Supreme Court's decision in Citizens United, which said corporations have first amendment rights when it comes to political contributions. Then you could say, well, okay, on the one hand, if corporations actually have first amendment rights, which we typically think belong to individuals, and we think evil comes from individuals, well then, maybe corporations have obligations just like individuals do-an obligation not to be evil.

One thing that you might say is maybe a little bit evil is Amazon's treatment of geriatric migrant workers. Some would say, well, Amazons' being benevolent, because these are people that don't have retirement savings, they've lost their jobs, they don't have any options, so this is an option that Amazon is offering to people. But the work is hard, and strenuous, and sometimes the days are 10 or 12 hours, and older bodies can't necessarily handle that very well. So some would say, boy, they're really exploiting a gap in our society-that we're not taking care of older workers, and they're losing their jobs through downsizing and age discrimination, and Amazon is being somewhat evil in an opportunistic way in taking advantage of them.

Are we evil if we use Amazon? I don't know if we're evil, but we certainly may be inattentive.

Christopher L. Sagers
James A. Thomas Distinguished Professor of Law, Cleveland State University

I humbly think that Amazon is a problem in more than one way-a potentially really big problem. But I also think that in economic policy it is actually not very useful to ask who is "evil" and who is not. That isn't because greed and power seem good or indifferent to me-I think they seem pretty bad. It's because, in economic policy, they don't seem relevant to getting the policies right. If Amazon wants to destroy its competitors through retail price competition, and wants to push down its suppliers' margins with its power as an indispensable distributor, well, it is only doing what every business does to some degree all the time. So a big problem in trying to make policy by asking who's the good guy is that we might look for them for a pretty long time without finding any. And that tends to be an affirmatively good thing so long as even those aggressive and vicious competitors are confronted by others that can meaningfully respond in kind. In fact, it's when we try to handle economic policy conflicts as if they are morality plays that we tend to get cases seriously wrong, and wind up disserving the people that the policies were meant to help. It's better to try to understand economic problems as the unfolding logic of a social process, and leave the morality to one's clergy.

Sarah Kaine
Associate Professor, Management Discipline Group, University of Technology Sydney and Core Member of the Centre for Business and Social Innovation

and Emmanuel Josserand
Professor, Management Discipline Group, University of Technology Sydney and Director of the Centre for Business and Social Innovation

A good indication of Amazon's values is captured in the name of its crowdsourcing website-Mechanical Turk-where clients post tasks (often collections of micro-tasks) and "turkers" complete them. In his book Uberworked and Underpaid: How Workers are disrupting the Digital Economy, Trebor Scholz explains that the name Mechanical Turk refers to an 'invention' of the late 1700s in which a chess master was hidden in a box controlling an automated set of mechanical hands that looked to be moving the pieces and playing the game independently. Amazon Mechanical Turk is designed to hide, not acknowledge human labour.

It might be libelous to assert the Amazon 'intends to harm,' per the Oxford English Dictionary's definition of evil, but the litany of allegations against Amazon ranging from the individual (the mistreatment of workers, differential pricing to customers), to the market (anti-competitive behavior including the suppression of competitor products), to the social (tax avoidance)-suggest an organization that not only lacks a moral compass but could be well on its way to a state of 'profound immorality'.

As for whether using it makes us evil...well, it depends on who 'we' are. It is hard to argue that a consumer buying from Amazon on a website among millions intends to harm, or even that they are conscious to harm. But some of us do know about Amazon's approach. So if we know is it forgivable to want to save a few dollars on our next superfluous gadget? Now that you have read this are you morally bound not to buy from Amazon? Maybe it is worth a thought if you can afford the extra cost.

But if you're a single mother with a couple of kids and a minimum wage job, that's another story. Ethical and activist consumerism are luxury goods and probably worth the price if you can still put a meal on the table or afford a pair of sneakers for your kids. If that is not the case-if for, instance, the downward pressure on wages exerted by the likes of Amazon has affected your salary-maybe you don't have a choice. And who could blame you for choosing to do the right thing for your family?

This demonstrates the paradox -that the race to the bottom which increases inequalities in our societies feeds its own market. The question is: for how long, and at what cost?

So, if you have the time to read this instead of 'ubering' on top of your day job to pay the rent, yes, you can probably consider yourself evil if you keep shopping with Amazon.

Do you have a burning question for Giz Asks? Email us at tipbox@gizmodo.com.

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Is Amazon Evil and Am I Evil for Using It?

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1-Click ordering a massively discounted flat-screen TV, or seventy pounds of coarse-grained salt, it can be easy to forget, or temporarily repress, all those stories you've read about, say, working conditions in Amazon's warehouses, or its propagation of the gig economy through contract labor.

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WHOOOO CAN WE TRUST? ANSWER: NOT LAWMAKERS WHO ARE ANTI-STRONG ONLINE PRIVACY LAWS
Q: who chose the panel? what is the ulterior motive here? given how unimpressive and lite the questions have been, what's the real point here? so the zucc can be like "but they cleared me"???

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This time last year, Republicans in Congress were rushing to pass legislation repealing the Federal Communications Commission's (FCC) online privacy protections that prevented internet service providers like AT&T and Comcast from harvesting and selling internet personal data without explicit permission from their customers.

The move was deeply unpopular, but the GOP reportedly hoped voters would be distracted by the controversy surrounding the attempted repeal of the Affordable Care Act. Democrats were united against the legislation, and President Trump quietly signed it into law.

Just one year later, many of the same lawmakers who voted to repeal the privacy rules were eager to grill Mark Zuckerberg about Facebook's high-profile privacy problems as the embattled CEO testified before Congress this week. Zuckerberg has built an empire on data gathered from Facebook users and used to sell targeted ads -- and the scandals are piling up.

Rep. Marsha Blackburn, a Tennessee Republican who introduced the legislation in the House that repealed the FCC privacy rules, told Zuckerberg that Facebook was "beginning to look like The Truman Show."

"My constituents in Tennessee want to know that they have a right to privacy," Blackburn told Zuckerberg during a marathon hearing held by the House Energy and Commerce Committee on Tuesday.

If Blackburn is so concerned about privacy, then why did she push to repeal some of the only online privacy protections on the federal books?

Critics point to Blackburn's campaign finance records, which show that telecom companies subject to the FCC rules she helped throw out are some of her top donors. The answer also lies in an increasingly partisan debate over net neutrality and how the government should regulate competing companies that create and shape the web.

Perhaps aware of the bad optics surrounding the repeal of the FCC privacy rules, Blackburn introduced her own online privacy protection proposal a few months later. Her bill would require both internet service providers (ISPs) and web services like Facebook to ask users for permission before sharing their sensitive personal information with third parties.

The bill, known as the BROWSER Act, sounds good on paper but includes several caveats that critics say are designed to benefit her backers in the telecom industry, including language that would preempt states from instituting tougher privacy protections on their own.

Tim Karr, a spokesperson for the digital rights group Free Press, said Blackburn is known for designing legislation to benefit companies like Verizon and AT&T that have donated to her campaigns.

"There is a legitimate question about whether Rep. Blackburn is a good faith actor in this space; she has routinely come down in defense of the phone and cable companies at the expense of edge companies like Facebook and Google," Karr said in an interview.

During Tuesday's hearing, Blackburn demanded to know whether Zuckerberg would commit to backing her bill. Zuckerberg ducked the question, telling the congresswoman that he wasn't "directly familiar" with the details of the legislation.

"Let's get familiar with the details," Blackburn responded.

Facebook Is Not the Internet

Blackburn's privacy bill must now compete with several others aimed at big web platforms, but unlike his counterparts in the broadband industry, Zuckerberg is not kicking and screaming in the face of regulation. Zuckerberg was more supportive when Democratic lawmakers brought up plans to roll out privacy regulation, signaling that Facebook is willing to be regulated as long as it can work with the party most aligned with Silicon Valley to shape what those regulations look like.

In fact, he repeatedly told lawmakers during hearings in the House and the Senate that he supports federal privacy regulations if they're done "right," and Facebook users across the globe would benefit from upgrades resulting from new privacy rules established in Europe.

Blackburn's legislation, on the other hand, would ensure that online content platforms like Facebook and Google would never regain a competitive advantage over internet ISPs that they would have enjoyed under the FCC's privacy rules.

It all goes back to the 2015 Open Internet order that established much-debated net neutrality rules at the FCC. Just like telephone companies are required to treat calls from other providers equally, the order reclassified ISPs as "common carriers" that must refrain from discriminating against data on their networks. This also allowed the FCC to impose the privacy rules Blackburn helped scrap last year.

Those rules required ISPs to ask customers for permission before selling personal information and data about their browsing habits to third parties, which providers routinely do unless users take initiative to opt-out. Republicans and the telecom industry cried foul, arguing that the rules did not apply to companies like Facebook, which continue to profit from collecting data without asking users to opt-in to targeted advertising schemes first.

Digital rights advocates argue that there is a key difference between an ISP and an edge provider like Facebook that justified the FCC's targeted regulation. You need an ISP to connect to the internet, but once online, signing up for Facebook and sharing data on its network is totally optional.

This explains why Zuckerberg is open to privacy regulations. If users don't trust Facebook to protect their privacy, they may move on to other platforms. Deleting an account with an ISP and switching to a new provider is not as simple, and in many parts of the country, consumers can only choose between two or three providers -- if they have a choice at all.

"You can get by without Facebook; you do suffer an economic consequence if you are a business and it's important and requires regulation, but the fact is, it's not on the same level as fundamental communications infrastructure," said Harold Feld, vice president of the digital rights group Public Knowledge, in an interview.

Zuckerberg was careful to make this distinction between the internet services we pay for and the Facebook services that users get for free. He repeatedly told lawmakers that users "own" their data and can control how information they post on his website is shared.

"I would differentiate between the ISPs, which I consider to be the pipes of the internet, and the apps for platforms on top," Zuckerberg told a packed Senate hearing Monday, adding that people have different expectations of internet providers and websites, so it would make sense to regulate them differently as well.

Of course, the sheer ubiquity and popularity of Facebook, and services like Instagram and WhatsApp have made the products virtual necessities for both individuals and businesses, and Zuckerberg is doing everything he can to convince lawmakers to shrug off antitrust concerns. Still, Karr said Facebook could never be considered a common carrier service.

"There's a tendency to try to look at edge providers and platforms and ISPs as the same thing, but they are different and those legal definitions are important," Karr said.

A Widening Partisan Divide

Under the FCC's net neutrality rules, the government considered the internet more like a public utility that everyone needs to use than an information service like Facebook. The ISPs hated this and asked their allies in the Republican Party to dig them out. Their wish was granted after President Trump won the election and installed a Republican majority at the FCC, which promptly threw out the net neutrality rules late last year.

Democrats are fighting to restore net neutrality and declare ISPs "common carriers" once again. This would benefit edge providers like Facebook and Google, which fear that, without net neutrality, they could be forced to pay ISPs extra to reach customers at priority speeds. It also explains why Blackburn's legislation would prevent the FCC from reinstating privacy rules for the AT&Ts and Comcasts of the world, leaving the job up to the Federal Trade Commission (FTC) instead.

Blackburn's plan would let the FTC regulate privacy at web platforms like Facebook as well, and she pitches her bill as a one-size-fits-all solution for the whole internet "ecosystem." After two days of hearings, it was clear Zuckerberg and many Democrats would rather see different regulations for the companies that hardwire the internet and the companies that build websites and apps. Feld said Blackburn's bill is clearly backed by the telecom industry.

"The FTC, which doesn't have a privacy statute and operates pursuant to its general consumer protection statute, is the lowest common denominator on privacy," said Feld, who added that the FTC must win in court to make enforcement actions. "To the extent that there is a privacy rule, it's the weakest possible privacy rule."

Congress could have left the FCC privacy rules for ISPs in place and then figured out what to do about Facebook's glaring privacy problems, but Republicans scrapped those rules instead, leaving the public with no protections in place while lawmakers engage in an increasingly partisan debate over how to regulate the internet. For that, at least, you can blame the GOP.

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Zuckerberg Grilled by Same Lawmakers Who Repealed Online Privacy Protections

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This time last year, Republicans in Congress were rushing to pass legislation repealing the Federal Communications Commission's (FCC) online privacy protections that prevented internet service providers like AT&T and Comcast from harvesting and selling internet personal data without explicit permission from their customers.

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workers were fired for trying to unionize?!?!?? and weren't allowed to use SLACK??
~ think: tech restrictions/dominance imposed by management: this literally controls what we see/how we think
~ "there are no real defined rules." tech companies SEEM very cool and chill about workers bc they have board games in the office but clearly there are rules but workers are given no benefit of the doubt if ""broken"". WHO IS MAKING THE RULES IF THERE'S NO UNION, WHO IS SUPPORTING THE WORKERS

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Earlier this year, a tech company named Lanetix fired its entire staff of software engineers for trying to unionize with NewsGuild-Communications Workers of America (CWA). While the outcome of the campaign is still unknown - NewsGuild-CWA has filed a complaint with the National Labor Relations Board alleging illegal retaliation - the Lanetix fight is potentially [...]

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Earlier this year, a tech company named Lanetix fired its entire staff of software engineers for trying to unionize with NewsGuild-Communications Workers of America (CWA). While the outcome of the campaign is still unknown - NewsGuild-CWA has filed a complaint with the National Labor Relations Board alleging illegal retaliation - the Lanetix fight is potentially [...]

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Outside contributors' opinions and analysis of the most important issues in politics, science, and culture.

"In a lot of ways Facebook is more like a government than a traditional company," Facebook CEO Mark Zuckerberg has said.

He elaborated on this claim in a recent interview with Vox's Ezra Klein. After noting that the Facebook community consists of more than 2 billion people around the world, he wondered if executives "sitting in an office here in California" were the right people to be making decisions for a constituency of that size. He asked, "How can you set up a more democratic or community-oriented process that reflects the values of people around the world?"

It's good to see Zuckerberg starting to grapple with Facebook's political responsibilities. But Zuckerberg and Facebook face far bigger challenges than he acknowledges in the interview.

As the technology writer Zeynep Tufekci has argued, it may be nearly impossible for Facebook to reform itself, given its underlying business model. And even if Facebook can reform itself, it faces some extraordinary challenges in building trust with its users and regulators.

The best way to understand this is to start from Zuckerberg's comparison of Facebook to a government. Facebook is so powerful in its own domain that it is, indeed, like a sovereign state. It can upend the business models of companies that depend on it, or completely change the ways its individual users relate to each other - without them even realizing what has happened.

As Larry Lessig observed decades ago, computer code is law. And today, Facebook's code establishes critical rules by which more than 2 billion of the world's people and millions of businesses interact online.

This means that Facebook is a powerful sovereign and Mark Zuckerberg is the key lawgiver. In some ways, of course, the comparison is inexact. Facebook doesn't have the power to tax, and it certainly doesn't have what Louis XIV called "the final argument of kings" - the ability to use physical violence to force people to comply with its demands.

And Facebook must answer to the regulators of other powerful sovereign governments, that of the United States and others around the world. But this is less of a check on power than it first appears because the impact of social media on society and the economy is still poorly understood, and regulation takes time to catch up.

Still, once you begin to think about Facebook as a government, a great deal falls into place. Zuckerberg's dilemmas are not the dilemmas of a corporation but the dilemmas of a king. Thanks to decades of research on political economy, we have some idea of what those dilemmas are and how difficult they are to solve.

A king is all-powerful. That makes his declarations about wanting to give up authority hard to take seriously.

It is difficult for a king's subjects to trust him because he has absolute power over them. Yet it is also difficult for a king to give up that control.

One of the key problems of political economy, therefore, is "tying the king's hands" - allowing the sovereign enough power to do his job, but constraining him so that he does not abuse his trust. Facebook's version of this problem is doubly hard, in that the company faces mixed incentives.

On the one hand, it has to reassure its users, but on the other it has to answer to the advertisers who drive its business model and allow it to make profits - and to the stock-market investors who create such extraordinary wealth for its owners and employees by speculating on the future growth of those profits.

Despite Zuckerberg's vision of democracy and community control, Facebook more closely resembles an autocratic than a democratic regime. Zuckerberg is the chair, chief executive officer, and controlling shareholder of Facebook.

Standard arguments in political economy suggest that this combination will make it difficult for Facebook to generate trust. Zuckerberg's promises about new governance arrangements, privileging transparency, and accountability may be sincere. Even so, as game theorists like the late Thomas Schelling have noted, costly commitments are not credible unless there is some means to enforce them when the time comes to deliver. Facebook's corporate structures mean that such promises are hard to turn into credible commitments unless there is some external incentive that will make them enforceable.

Zuckerberg has defended the way power at Facebook is concentrated in his own person. And it may be true that, as he argues, this unusual corporate governance arrangement allows Facebook to hold off shareholders obsessed with short-term profits and think instead about the long-term interests of its users. But that argument bears an uncanny resemblance to ones made on behalf of "rational" political autocrats. The historian Edward Gibbon, describing the Roman emperor Septimius Severus, argued:

The true interest of an absolute monarch generally coincides with that of his people. Their numbers, their wealth, their order, and their security, are the best and only foundations of his real greatness; and, were he totally devoid of virtue, prudence might supply its place, and would dictate the same course of conduct.

Modern political economists are more likely to emphasize how potential clashes of interest between autocrats and their subjects can generate terrible outcomes and mutual distrust. For example, a classic article by Nobel Prize-winning economist Douglass North and Barry Weingast, on constitutions and commitment problems, highlights how absolute rulers cannot be trusted to be trustworthy.

English kings successfully tied their own hands

North and Weingast point out that from 1603 to 1714, when the United Kingdom was ruled by the absolutist Stuarts, the crown found it enormously hard to persuade bankers to lend it money. The bankers knew that the head of state could simply decide later to repudiate any loan agreement and just keep whatever it had "borrowed." The result was that the crown was perpetually short of funds and had to resort to forced "loans" that made merchants more determined to keep their money hidden from the government, hurting economic growth.

This only changed after the Glorious Revolution, when a constitutional settlement gave Parliament supremacy - significantly reducing the king's role and making the monarch subject to the law. The Parliament took on taxing, budgetary, and lending authority. These political limits meant that lenders could trust the crown to repay its debts, making it much easier for the British government to raise money cheaply and efficiently.

Margaret Levi and David Stasavage show that there are other benefits when the executive authority is truly responsible to a legislature representing citizens. Citizens are happier to comply with government demands for taxes, military service, and compliance with the law. When governments are beholden to their constituencies, citizens can respond to broken promises by stopping complying and, at the extreme, removing them from office. When citizens have power over government, the government has strong reason to behave trustworthily, hence generating trust.

This is why tying the king's hands is a necessary precondition to trust and peaceful economic exchange. It is also a fundamental basis of democracy, which uses institutions to constrain governments to act accountably towards their citizens.

Facebook can't chop off people's heads and it has to obey the laws of the jurisdictions where it operates, but, even so, it faces a version of the problem that plagued the Stuarts. Facebook can unilaterally and arbitrarily change many of the laws of its realm (terms of service and market making algorithms among them).

Even if you feel manipulated, there may not be much you can do about it. Network effects - which Facebook has gone to great lengths to reinforce - lock both businesses and users into Facebook, even if they all individually might prefer a different system of rule. As with citizens of traditional states, users of Facebook can exit if they wish, but it is extremely difficult.

The result is that even if Zuckerberg and his lieutenants have good intentions, they will still be too powerful for people to trust easily. It's possible for powerful actors to break out of these "trust traps," but it is very hard. North and Weingast discuss two ways in which kings' hands can be tied: voluntarily or by compulsion.

There are different approaches to tying the king's hands - some more credible than others

First, the king can try to adhere to an informal norm of behaving responsibly. However, this is very hard to maintain over the long term, as new demands and changing circumstances challenge even the most sincere commitments. Facebook's competitor Google used to have a simple motto: "Don't be evil."

Over time, the company succumbed to the temptation to accept practices that motto would once have forbidden, becoming just a little bit evil, and then just a little bit more, and more, until much of its original idealism seems to have become submerged.

In 2010, Google's then-CEO Eric Schmidt said: "Google policy is to get right up to the creepy line and not cross it," indicating a much more flexible approach to pushing its users' boundaries.

Second, the king can agree to a constitutional settlement in which he gives up power to become more trustworthy. Zuckerberg has proposed setting up independent bodies that would hear appeals from users regarding Facebook's decisions. This might be the corporate version of a constitutional compromise.

However, the devil will be in the details. History tells us that it is very hard for kings to curb their power in this way. Even when they recognize that tying their hands is in their long-term interests - because they risk rebellion if their legitimacy comes to be doubted - they are often overwhelmed by the desire to cheat.

For example, even when nation-states seem to give up power to international arbitrators and judges, they create sneaky backdoor incentives to rig the odds in their favor. Rulers can also, more simply, retake power or arbitrarily change the course of policy, either for their own benefit or because they believe they know better what is in the best interest of their community.

If and when Facebook starts to build its own systems of trust, it will face similar temptations. If, for example, Facebook has the power to appoint and reappoint its own "independent" appeal judges, those judges are going to have excellent financial reasons for keeping Facebook happy. They will not have, as federal judges in the United States have, an externally binding constitution to anchor their judgments and provide true independence.

Some past efforts by Facebook to introduce democracy and limitations have failed

Furthermore, democratic processes are only legitimate when they have some real likelihood of binding the monarch to make decisions that he doesn't like. When in 2009, Facebook faced a previous furor over changes to the ways it shared its users' data, it responded by proposing a "site governance" system under which its users would have some collective control over their data. In Zuckerberg's words back then:

The past week reminded us that users feel a real sense of ownership over Facebook itself, not just the information they share. Companies like ours need to develop new models of governance. Rather than simply reissue a new Terms of Use, the changes we're announcing today are designed to open up Facebook so that users can participate meaningfully in our policies and our future.

However, Facebook's attempted model of governance involved mass referendums, which were confusing and hard to organize around, and had very low participation. The final referendum was held in 2012, and involved setting the terms under which Facebook could share user data with other organizations. Facebook announced that it would only consider the referendum binding in the (extremely unlikely) case that 30 percent of its global users voted. Since only 668,000 users voted, Facebook felt free to ignore the result, and it has not held any referendums since.

Now, Zuckerberg is arguing in his interview with Klein for establishing a far more independent process: "You can imagine some sort of structure, almost like a Supreme Court, that is made up of independent folks who don't work for Facebook, who ultimately make the final judgment call on what should be acceptable speech in a community that reflects the social norms and values of people all around the world."

It's heartening to see Zuckerberg recognizing that Facebook needs real democratic legitimacy and accountability - and that it's considering more binding procedures. However, this is only the first step on an incredibly difficult journey. We don't have many good models showing how corporate accountability and democratic accountability can be combined.

If Facebook finds a way to deliver on this promise by giving others the power to appoint those who decide what behavior must be regulated and how, and by making data sufficiently available for a healthy oversight and decision process, it will be a significant move toward tying the king's hands. However, this system will have to involve an irreversible ceding of power if it is to be credible, and to create the trust that Facebook is now so sorely lacking.

There are those who will say that the market will eventually rein in any company that doesn't properly serve its customers. Here, economic history serves up the same lesson as political history: When companies become too powerful, they are often ruthlessly successful in extending and preserving that power. At some point, when customers and competitive markets seem helpless and the harms become overwhelmingly obvious, governments typically step in.

They may go so far as to break up monopolies, but more often they tie powerful companies' hands by limiting the behaviors that have caused the most obvious harm. European regulations on Facebook's privacy violations are a good case in point. The risk of course is that technology typically moves much faster than government, and today's regulation may prove insufficient for tomorrow's challenges.

Facebook has an opportunity to get ahead of this situation by taking proactive steps to tie its own hands before they are tied for it. Its voluntary adoption of the provisions of the Honest Ads Act, whether or not it passes in Congress, is a good example. (The act, proposed by US Sen. Mark Warner (D-VA), would make public who is making sizable political-ad buys on major online platforms, among other requirements.) But if the law does not pass, Facebook will be back in its old situation of being free to change the rules when convenient.

What we need is a partnership between government and platforms in which platforms voluntarily agree to limits on their behavior and establish independent bodies capable of true oversight, and the government provides a backstop of known consequences for the failure to observe those limits. We are hoping that in his appearance before Congress this week, Mark Zuckerberg provides detailed proposals for reestablishing trust, not just vague promises to do better.

The governments and regulatory regimes that we do have are the product of imperfect processes of trial and error over long periods of time. Because we know it will take a long time to create a new cooperative approach to regulating social media, we cannot begin it too soon.

U pdate, 4/9: On Monday, Facebook announced it is taking a significant, if small, step in this direction by giving access to some of its data to scholars for research on the impact of social media on democracy. The research enterprise will be funded by a consortium of foundations and without any Facebook money; the nonpartisan and independent Social Science Research Council will oversee it. According to the council's president, Alondra Nelson, "SSRC-appointed review committees will actively engage with technologists, advocates, and ethicists to develop 21st-century academic standards for anonymized digital data use."

Facebook pledges not to interfere with the research. The hope is to implement a model that other platforms will also adopt to better serve democracy. To be sure, this does not rise to a full binding of hands, but Facebook is ceding power and agreeing to independent oversight.

Henry Farrell is a professor of political science and international affairs at George Washington University. Find him on Twitter @henryfarrell. Margaret Levi is the Sara Miller McCune director of the Center for Advanced Study in the Behavioral Sciences at Stanford University and a professor of political science at Stanford. Find her on Twitter@margaretlevi. Tim O'Reilly is the founder and CEO of O'Reilly Media and the author of . Find him on Twitter@timoreilly.

The Big Idea is Vox's home for smart discussion of the most important issues and ideas in politics, science, and culture - typically by outside contributors. If you have an idea for a piece, pitch us at thebigidea@vox.com.

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Mark Zuckerberg runs a nation-state, and he's the king

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Artboard 1 Outside contributors' opinions and analysis of the most important issues in politics, science, and culture. "In a lot of ways Facebook is more like a government than a traditional company," Facebook CEO Mark Zuckerberg has said. He elaborated on this claim in a recent interview with Vox's Ezra Klein.

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Yair Rosenberg wanted to troll the trolls.

Rosenberg, a senior writer for Jewish-focused news-and-culture website Tablet Magazine, had become a leading target of anti-Semitic Twitter users during his reporting on the 2016 U.S. presidential campaign. Despite being pelted with slurs, he wasn't overly fixated on the Nazis who had embraced the service. "For the most part I found them rather laughable and easily ignored," he says.

But one particular type of Twitter troll did gnaw at him: the ones who posed as minorities-using stolen photos of real people-and then infiltrated high-profile conversations to spew venom. "Unsuspecting readers would see this guy who looks like an Orthodox Jew or a Muslim woman saying something basically offensive," he explains. "So they think, Oh, Muslims are religious. Jews are religious. And they are horrifically offensive people."

Rosenberg decided to fight back. Working with Neal Chandra, a San Francisco-based developer he'd never met, he created an automated Twitter bot called Imposter Buster. Starting in December 2016, it inserted itself into the same Twitter threads as the hoax accounts and politely exposed the trolls' masquerade ("FYI, this account is a racist impersonating a Jew to defame Jews").

Imposter Buster soon came under attack itself-by racists who reported it to Twitter for harassment. Unexpectedly, the company sided with the trolls: It suspended the bot for spammy behavior the following April. With assistance from the Anti-Defamation League, Rosenberg and Chandra got that decision reversed three days later. But their targets continued to file harassment reports, and last December Twitter once again blacklisted Imposter Buster, this time for good.

Rosenberg, who considers his effort good citizenship rather than vigilantism, still isn't sure why Twitter found it unacceptable; he never received an explanation directly from the company. But the ruling gave racists a win by technical knockout.

For all the ways in which the Imposter Buster saga is unique, it's also symptomatic of larger issues that have long bedeviled Twitter: abuse, the weaponizing of anonymity, bot wars, and slow-motion decision making by the people running a real-time platform. These problems have only intensified since Donald Trump became president and chose Twitter as his primary mouthpiece. The platform is now the world's principal venue for politics and outrage, culture and conversation-the home for both #MAGA and #MeToo.

This status has helped improve the company's fortunes. Daily usage is up a healthy 12% year over year, and Twitter reported its first-ever quarterly profit in February, capping a 12-month period during which its stock doubled. Although the company still seems unlikely ever to match Facebook's scale and profitability, it's not in danger of failing. The occasional cries from financial analysts for CEO Jack Dorsey to sell Twitter or from critics for him to shut it down look more and more out of step.

Despite Twitter's more comfortable standing, Dorsey has been increasingly vocal about his service's problems. "We are committed to making Twitter safer," the company pledged in its February shareholder letter. On the accompanying investor call, Dorsey outlined an "information quality" initiative to improve content and accounts on the service. Monthly active users have stalled at 330 million-a fact that the company attributes in part to its ongoing pruning of spammers. Twitter's cleanup efforts are an admission, albeit an implicit one, that the array of troublemakers who still roam the platform-the hate-mongers, fake-news purveyors, and armies of shady bots designed to influence public opinion-are impeding its ability to grow. (Twitter did not make Dorsey, or any other executive, available to be interviewed for this story. Most of the more than 60 sources we spoke to, including 44 former Twitter employees, requested anonymity.)

Though the company has taken significant steps in recent years to remove bad actors, it hasn't shaken the lingering impression that it isn't trying hard enough to make the service a safer space. Twitter's response to negative incidents is often unsatisfying to its users and more than a trifle mysterious-its punishment of Rosenberg, instead of his tormentors, being a prime example. "Please can someone smart make a new website where there's only 140 characters and no Nazis?" one user tweeted shortly after Twitter introduced 280-character tweets in November.

Twitter is not alone in wrestling with the fact that its product is being corrupted for malevolence: Facebook and Google have come under heightened scrutiny since the presidential election, as more information comes to light revealing how their platforms manipulate citizens, from Cambridge Analytica to conspiracy videos. The companies' responses have been timid, reactive, or worse. "All of them are guilty of waiting too long to address the current problem, and all of them have a long way to go," says Jonathon Morgan, founder of Data for Democracy, a team of technologists and data experts who tackle governmental social-impact projects.

The stakes are particularly high for Twitter, given that enabling breaking news and global discourse is key to both its user appeal and business model. Its challenges, increasingly, are the world's.

How did Twitter get into this mess? Why is it only now addressing the malfeasance that has dogged the platform for years? "Safety got away from Twitter," says a former VP at the company. "It was Pandora's box. Once it's opened, how do you put it all back in again?"

In Twitter's early days, as the microblogging platform's founders were figuring out its purpose, its users showed them Twitter's power for good. Galvanized by global social movements, dissidents, activists, and whistle-blowers embracing Twitter, free expression became the startup's guiding principle. "Let the tweets flow," said Alex Macgillivray, Twitter's first general counsel, who later served as deputy CTO in the Obama administration. Internally, Twitter thought of itself as "the free-speech wing of the free-speech party."

This ideology proved naive. "Twitter became so convinced of the virtue of its commitment to free speech that the leadership utterly misunderstood how it was being hijacked and weaponized," says a former executive.

The first sign of trouble was spam. Child pornography, phishing attacks, and bots flooded the tweetstream. Twitter, at the time, seemed to be distracted by other challenges. When the company appointed Dick Costolo as CEO in October 2010, he was trying to fix Twitter's underlying infrastructure-the company had become synonymous with its "fail whale" server-error page, which exemplified its weak engineering foundation. Though Twitter was rocketing toward 100 million users during 2011, its antispam team included just four dedicated engineers. "Spam was incredibly embarrassing, and they built these stupidly bare-minimum tools to [fight it]," says a former senior engineer, who remembers "goddamn bot wars erupting" as fake accounts fought each other for clicks.

Twitter's trust and safety group, responsible for safeguarding users, was run by Del Harvey, Twitter employee No. 25. She had an atypical résumé for Silicon Valley: Harvey had previously worked with Perverted Justice, a controversial volunteer group that used web chat rooms to ferret out apparent sexual predators, and partnered with NBC's To Catch a Predator, posing as a minor to lure in pedophiles for arrest on TV. Her lack of traditional technical and policy experience made her a polarizing figure within the organization, although allies have found her passion about safety issues inspiring. In the early days, "she personally responded to individual [affected] users-Del worked tirelessly," says Macgillivray. "[She] took on some of the most complex issues that Twitter faced. We didn't get everything right, but Del's leadership was very often a factor when we did."

Harvey's view, championed by Macgillivray and other executives, was that bad speech could ultimately be defeated with more speech, a belief that echoed Supreme Court Justice Louis Brandeis's 1927 landmark First Amendment decision that this remedy is always preferable to "enforced silence." Harvey occasionally used as an example the phrase "Yo bitch," which bad actors intend as invective, but others perceive as a sassy hello. Who was Twitter to decide? The marketplace of ideas would figure it out.

By 2012, spam was mutating into destructive trolling and hate speech. The few engineers in Harvey's group had built some internal tools to enable her team to more quickly remove illegal content such as child pornography, but they weren't prepared for the proliferation of harassment on Twitter. "Every time you build a wall, someone is going to build a higher ladder, and there are always more people outside trying to fuck you over than there are inside trying to stop them," says a former platform engineer. That year, Australian TV personality Charlotte Dawson was subjected to a rash of vicious tweets-e.g., "go hang yourself"-after she spoke out against online abuse. Dawson attempted suicide and was hospitalized. The following summer, in the U.K., after activist Caroline Criado-Perez campaigned to get a woman's image featured on the 10-pound note, her Twitter feed was deluged with trolls sending her 50 rape threats per hour.

The company responded by creating a dedicated button for reporting abuse within tweets, yet trolls only grew stronger on the platform. Internally, Costolo complained that the "abuse economics" were "backward." It took just seconds to create an account to harass someone, but reporting that abuse required filling out a time-consuming form. Harvey's team, earnest about reviewing the context of each reported tweet but lacking a large enough support staff, moved slowly. Multiple sources say it wasn't uncommon for her group to take months to respond to backlogged abuse tickets. Because they lacked the necessary language support, team members had to rely on Google Translate for answering many non-English complaints. User support agents, who manually evaluated flagged tweets, were so overwhelmed by tickets that if banned users appealed a suspension, they would sometimes simply release the offenders back onto the platform. "They were drowning," says a source who worked closely with Harvey. "To this day, it's shocking to me how bad Twitter was at safety."

Twitter's leadership, meanwhile, was focused on preparing for the company's November 2013 IPO, and as a result it devoted the bulk of its engineering resources to the team overseeing user growth, which was key to Twitter's pitch to Wall Street. Harvey didn't have the technical support she needed to build scalable solutions to Twitter's woes.

Toxicity on the platform intensified during this time, especially in international markets. Trolls organized to spread misogynist messages in India and anti-Semitic ones in Europe. In Latin America, bots began infecting elections. Hundreds used during Brazil's 2014 presidential race spread propaganda, leading a company executive to meet with government officials, during which, according to a source, "pretty much every member of the Brazilian house and senate asked, 'What are you doing about bots?'" (Around this time, Russia reportedly began testing bots of its own to sway public opinion through disinformation. Twitter largely tolerated automated accounts on the platform; a knowledgeable source recalls the company once sending a cease-and-desist letter to a bot farmer, which was disregarded, a symbol of its anemic response to this issue.) Twitter's leadership seemed deaf to cries from overseas offices. "It was such a Bay Area company," says a former international employee, echoing a common grievance that Twitter fell victim to Silicon Valley myopia. "Whenever [an incident] happened in the U.S., it was a company-wide tragedy. We would be like, 'But this happens to us every day!"

It wasn't until mid-2014, around the time that trolls forced comedian Robin Williams's daughter, Zelda, off the service in the wake of her father's suicide-she later returned-that Costolo had finally had enough. Costolo, who had been the victim of abuse in his own feed, lost faith in Harvey, multiple sources say. He put a different department in charge of responding to user-submitted abuse tickets, though he left Harvey in charge of setting the company's trust and safety guidelines.

Hashtag Wars

Discourse on Twitter often devolves into face-offs for opposing worldviews.

Soon, the threats morphed again: ISIS began to leverage Twitter to radicalize followers. Steeped in free-speech values, company executives struggled to respond. Once beheading videos started circulating, "there were brutal arguments with Dick," recalls a former top executive. "He'd say, 'You can't show people getting killed on the platform! We should just erase it!' And [others would argue], 'But what about a PhD student posting a picture of the Kennedy assassination?' " They decided to allow imagery of beheadings, but only until the knife touches the neck, and, according to two sources, the company assigned support agents to search for and report beheading content-so the same team could then remove it. "It was the stupidest thing in the world," says the source who worked closely with Harvey. "[Executives] already made the policy decision to take down the content, but they didn't want to build the tools to [proactively] enforce the policy." (Twitter has since purged hundreds of thousands of ISIS-related accounts, a muscular approach that has won the platform praise.)

Costolo, frustrated with the company's meager efforts in tackling these problems, sent a company-wide memo in February 2015 complaining that he was "ashamed" by how much Twitter "sucked" at dealing with abuse. "If I could rewind the clock, I'd get more aggressive earlier," Costolo tells Fast Company, stressing that the "blame" lays on nobody "other than the CEO at the time: me."

"I often hear people in Silicon Valley talking about fake news and disinformation as problems we can engineer our way out of," says Brendan Nyhan, codirector of Bright Line Watch, a group that monitors threats to democratic processes. "That's wrong. People are looking for a solution that doesn't exist."

The Valley may be coming around to this understanding. Last year, Facebook and YouTube announced initiatives to expand their content-policing teams to 20,000 and 10,000 workers, respectively. Twitter, meanwhile, had just 3,317 employees across the entire company at the end of 2017, a fraction of whom are dedicated to improving "information quality."

Putting mass quantities of human beings on the job, though, isn't a panacea either. It introduces new issues, from personal biases to having to make complicated calls on content in a matter of seconds. "These reviewers use detailed rules designed to direct them to make consistent decisions," says Susan Benesch, faculty associate at Harvard's Berkman Klein Center for Internet and Society and director of the Dangerous Speech Project. "That's a hard thing to do, especially at scale."

Humans are often to blame for overly broad purges that capture benign content that doesn't violate policy, such as when YouTube did a sweep for extremist and gun-related videos after the Parkland shooting, deleting specific clips and even entire channels that shouldn't have been subject to elimination. A YouTube spokesperson admitted to Bloomberg, "Newer members may misapply some of our policies resulting in mistaken removals."

The enormity of this quality-control conundrum helps explain why Twitter frequently fails, at least initially, to remove tweets that users report for harassment-some including allusions to death or rape-even though they would appear to violate its community standards. The company also catches flak for taking action against tweets that do offend these rules but have an extraordinary context, as when it temporarily suspended actress Rose McGowan for including a private phone number in a flurry of tweets excoriating Hollywood notables in the wake of the Harvey Weinstein sexual harassment scandal. "You end up going down a slippery slope on a lot of these things," says a former C-level Twitter executive. " 'Oh, the simple solution is X!' That's why you hear now, 'Why don't you just get rid of bots?!' Well, lots of [legitimate media] use automated [accounts] to post headlines. Lots of these easy solutions are a lot more complex."

Five months after Costolo's February 2015 lament, he resigned from Twitter. Cofounder Jack Dorsey, who had run the company until he was fired in 2008, replaced Costolo as CEO (while retaining the same job at his payments company, Square, headquartered one block away in San Francisco). Dorsey, an English major in a land of computer scientists, had deep thoughts about Twitter's future, but he couldn't always articulate them in a way that translated to engineers. "I'd be shocked if you found somebody [to whom] Jack gave an extremely clear articulation of his thesis for Twitter," says the former top executive, noting that Dorsey has described the service by using such metaphors as the Golden Gate Bridge and an electrical outlet for a toaster. Once, he gathered the San Francisco office for a meeting where he told employees he wanted to define Twitter's mission-and proceeded to play the Beatles's "Blackbird" as attendees listened in confused silence.

There was no doubt, though, that he believed in Twitter's defining ethos. "Twitter stands for freedom of expression. We stand for speaking truth to power," Dorsey tweeted on his first official day back as Twitter's CEO, in October 2015.

By the time Dorsey's tenure got under way, Twitter had gotten a better handle on some of the verbal pollution plaguing the service. The company's anti-abuse operations had been taken over by Tina Bhatnagar, a no-nonsense veteran of Salesforce who had little patience for free-speech hand-wringing. Bhatnagar dramatically increased the number of outsourced support agents working for the company and was able to reduce the average response time on abuse-report tickets to just hours, though some felt the process became too much of a numbers game. "She was more like, 'Just fucking suspend them,'" says a source who worked closely with her. If much of the company was guided by Justice Brandeis's words, Bhatnagar represented Justice Potter Stewart's famous quote about obscenity: "I know it when I see it."

This ideological split was reflected in the company's organizational hierarchy, which kept Harvey and Bhatnagar in separate parts of the company-legal and engineering, respectively-with separate managers. "They often worked on the exact same things but with very different approaches-it was just bonkers," says a former high-level employee who felt ricocheted between the two factions. Even those seemingly on the same team didn't always see eye to eye: According to three sources, Colin Crowell, Twitter's VP of public policy, at one point refused to report to Harvey's boss, general counsel Vijaya Gadde (Macgillivray's successor), due in part to disagreements about how best to approach free-speech issues.

Contentiousness grew common: Bhatnagar's team would want to suspend users it found abusive, only to be overruled by Gadde and Harvey. "That drove Tina crazy," says a source familiar with the dynamic. "She'd go looking for Jack, but Jack would be at Square, so the next day he'd listen and take notes on his phone and say, 'Let me think about it.' Jack couldn't make a decision without either upsetting the free-speech people or the online-safety people, so things were never resolved."

Dorsey's supporters argue that he wasn't necessarily indecisive-there were simply no easy answers. Disputes that bubbled up to Dorsey were often bizarre edge cases, which meant that any decision he made would be hard to generalize to a wide range of instances. "You can have a perfectly written rule, but if it's impossible to apply to 330 million users, it's as good as having nothing," says a source familiar with the company's challenges.

Dorsey had other business demands to attend to at the time. When he returned as CEO, user growth had stalled, the stock had declined nearly 70% since its high following the IPO, the company was on track to lose more than $500 million in 2015 alone, and a number of highly regarded employees were about to leave. Although Twitter made some progress in releasing new products, including Moments and its live-video features, it struggled to refresh its core experience. In January 2016, Dorsey teased users with hints at an expansion of Twitter's long-standing 140-character limit, but it took another 22 months to launch 280-character tweets. "Twitter was a hot mess," says Leslie Miley, who managed the engineering group responsible for safety features until he was laid off in late 2015. "When you switch product VPs every year, it's hard to keep a strategy in place."

Then the U.S. presidential election arrived. All of Twitter's warts were about to be magnified on the world stage. Twitter's support agents, the ones reviewing flagged content and wading through the darkest muck of social media, witnessed the earliest warning signs as Donald Trump started sweeping the primaries. "We saw this radical shift," says one at the time. Discrimination seemed more flagrant, the propaganda and bots more aggressive. Says another: "You'd remove it and it'd come back within minutes, supporting Nazis, hating Jews, [memes featuring] ovens, and oh, the frog...the green frog!" (That would be Pepe, a crudely drawn cartoon that white supremacists co-opted.)

A July 2016 troll attack on SNL and Ghostbusters star Leslie Jones- incited by alt-right provocateur Milo Yiannopoulos -proved to be a seminal moment for Twitter's anti-harassment efforts. After Jones was bombarded with racist and sexist tweets, Dorsey met with her personally to apologize and declared an "abuse emergency" internally. The company banned Yiannopoulos. It also enhanced its muting and blocking features and introduced an opt-in tool that allows users to filter out what Twitter has determined to be "lower-quality content. "The idea was that Twitter wouldn't be suppressing free speech-it would merely not be shoving unwanted tweets into its users' faces.

But these efforts weren't enough to shield users from the noxiousness of the Clinton-Trump election cycle. During the Jones attack, screenshots of fake, Photoshopped tweets purporting to show divisive things Jones had shared spread virally across the platform. This type of disinformation gambit would become a hallmark of the 2016 election and beyond, and Twitter did not appreciate the strength of this new front in the information wars.

Of the two presidential campaigns, Trump's better knew how to take advantage of the service to amplify its candidate's voice. When Twitter landed massive ad deals from the Republican nominee, left-leaning employees complained to the sales team that it should stop accepting Trump's "bullshit money."

The ongoing, unresolved disputes over what Twitter should allow on its platform continued to flare into the fall. In October, the company reneged on a $5 million deal with the Trump campaign for a custom #CrookedHillary emoji. "There was vicious [internal] debate and back-channeling to Jack," says a source involved. "Jack was conflicted. At the eleventh hour, he pulled the plug." Trump allies later blasted Twitter for its perceived political bias.

On November 8, employees were shocked as the election returns poured in, and the morning after Trump's victory, Twitter's headquarters were a ghost town. Employees had finally begun to take stock of the role their platform had played not only in Trump's rise but in the polarization and radicalization of discourse.

"We all had this 'holy shit' moment," says a product team leader at the time, adding that everyone was asking the same question: "Did we create this monster?"

In the months following Trump's win, employees widely expected Dorsey to address Twitter's role in the election head-on, but about a dozen sources indicate that the CEO remained mostly silent on the matter internally. "You can't take credit for the Arab Spring without taking responsibility for Donald Trump," says Leslie Miley, the former safety manager.

Over time, though, Dorsey's thinking evolved, and he seems to be less ambivalent about what he'll allow on the platform. Sources cite Trump's controversial immigration ban and continued alt-right manipulation as influences. At the same time, Twitter began to draw greater scrutiny from the public, and the U.S. Congress, for its role in spreading disinformation.

Dorsey empowered engineering leaders Ed Ho and David Gasca to go after Twitter's problems full bore, and in February 2017, as part of what some internally called an "abuse sprint," the company rolled out more aggressive measures to permanently bar bad actors on the platform and better filter out potentially abusive or low-quality content. "Jack became a little bit obsessed," says a source. "Engineering in every department was asked to stop working on whatever they were doing and focus on safety."

Twitter's safety operations, previously siloed, became more integrated with the consumer-product side of the company. The results have been positive. In May 2017, for example, after learning how much abuse users were being subjected to via Twitter's direct messages feature, the team overseeing the product came up with the idea of introducing a secondary inbox to capture bad content, akin to a spam folder. "They're starting to get things right," says a former manager at the company, "addressing these problems as a combination of product and policy."

During a live video Q&A Dorsey hosted in March, he was asked why trust and safety didn't work with engineering much earlier. The CEO laughed, then admitted, "We had a lot of historical divisions within the company where we weren't as collaborative as we could be. We've been recognizing where that lack of collaboration has hurt us."

Even previous victims of Twitter abuse have recognized that the company's new safety measures have helped. "I think Twitter is doing a better job than they get public credit for," says Brianna Wu, the developer who became a principal target of Gamergate, the loose-knit collective of trolls whose 2014 attacks on prominent women in the gaming industry was a canary in the Twitter-harassment coal mine. "Most of the death threats I get these days are either sent to me on Facebook or through email, because Twitter has been so effective at intercepting them before I can even see them," she adds, sounding surprisingly cheery. (Wu's encounters with the dark side of social networking helped inspire her current campaign for a U.S. House seat in the Boston area, with online safety as one of her principal issues.)

Twitter has also been more proactive since the election in banning accounts and removing verifications, particularly of white nationalists and alt-right leaders such as Richard Spencer. (The blue check mark signifying a verified user was originally designed to confirm identity but has come to be interpreted as an endorsement.) According to three sources, Dorsey himself has personally directed some of these decisions.

Twitter began rolling out a series of policy and feature changes last October that prioritized civility and truthfulness over free-speech absolutism. For instance, while threatening murder has always been unacceptable, now even speaking of it approvingly in any context will earn users a suspension. The company has also made it more difficult to bulk-tweet misinformation.

Such crackdowns haven't yet eliminated the service's festering problems: After February's Parkland mass shooting, some surviving students became targets of harassment, and Russia-linked bots reportedly spread pro-gun sentiments and disinformation. Nobody, though, can accuse Twitter of not confronting its worst elements. The pressure on Dorsey to keep this momentum going is coming from Wall Street, too: On a recent earnings call, a Goldman Sachs analyst pressed Dorsey about the company's progress toward eliminating bots and enforcing safety policies. "Information quality," Dorsey responded, is now Twitter's "core job."

This past Valentine's Day, Senator Mark Warner entered his stately corner suite in Washington, D.C.'s Hart Senate Office Building, poured himself a Vitaminwater, and rushed into an explanation of why Silicon Valley needs to be held accountable for its role in the 2016 election. As the Democratic vice chairman of the Senate Intelligence Committee, Warner is swamped with high-profile hearings and classified briefings, but the topic is also personal for the self-described "tech guy" who made a fortune in the 1980s investing in telecoms.

Warner is coleading the committee's investigation into Russian election interference, which has increasingly centered on the growing, unfettered power of technology giants, whom he believes need to get over their "arrogance" and fix their platforms. "One of the things that really offended me was the initial reaction from the tech companies to blow us off," he began, leaning forward in his leather chair. " 'Oh no! There's nothing here! Don't look!' Only with relentless pressure did they start to come clean."

He saved his harshest words for Twitter, which he said has dragged its feet far more than Facebook or Google. "All of Twitter's actions were in the wake of Facebook's," Warner complained in his gravelly voice, his face reddening. "They're drafting!" The company was the only one to miss the January 8 deadline for providing answers to the Intelligence Committee's inquiries, and, making matters worse, Twitter disclosed weeks later that Kremlin-linked bots managed to generate more than 450 million impressions, substantially higher than the company previously reported. "There's been this [excuse of], 'Oh, well, that's just Twitter.' That's not a long-term viable answer."

Warner stated that he has had offline conversations directly with Mark Zuckerberg, but never Dorsey. Throwing shade, Warner smiled as he suggested that the company may not be able to commit as many resources as Facebook and Google can because it has a "more complicated, less lucrative business model."

The big question now is what government intervention might look like. Warner suggested several broad policy prescriptions, including antitrust and data privacy regulations, but the one with the greatest potential effect on Twitter and its rivals would be to make them liable for the content on their platforms. When asked if the European Union, which has been more forceful in its regulation of the technology industry, could serve as a model, the senator replied, "[I'm] glad the EU is acting. I think they're bolder than we are."

If the U.S. government does start taking a more activist role in overseeing social networks, it will unleash some of the same nettlesome issues that Europe is already working through. On January 1, for instance, Germany began enforcing a law known as (deep breath) Netzwerkdurchsetzungsgesetz, or NetzDG for short. Rather than establish new restrictions on hate speech, it mandates that large social networks remove material that violates the country's existing speech laws-which are far more stringent than their U.S. equivalents-within 24 hours of being notified of its existence."Decisions that would take months in a regular court are now [made] by social media companies in just minutes," says Mirko Hohmann, a Berlin-based project manager for the Global Public Policy Institute.

As evidence of how this approach can create unintended outcomes, he points to an instance in which Twitter temporarily shut down the account of a German humor magazine after it tweeted satirically in the voice of Beatrix von Storch, a leader of a far-right party. "No court would have judged these tweets illegal, but a Twitter employee under pressure did," Hohmann says. (The company apparently even deleted an old tweet by one of NetzDG's architects, Heiko Maas, in which he called another politician an idiot.)

In the U.S., rather than wait for federal action or international guidance, state lawmakers in Maryland, New York, and Washington are already working to regulate political ads on social networks. As Warner said, the era of Silicon Valley self-policing is over.

Whether or not the federal government steps in, hardening the big social networks against abuse will involve implementing solutions which haven't even been invented yet. "If there was a magical wand that they could wave to solve this challenge, with the substantial resources and expertise that they have, then they absolutely would," says Graham Brookie, deputy director of the Atlantic Council's Digital Forensic Research Lab.

Still, there are many things Twitter can do to protect its platform. Using technology to identify nefarious bots is a thorny matter, but Twitter could label all automated accounts as such, which wouldn't hobble legitimate feeds but would make it tougher for Russian bots to pose as heartland Trump supporters.

"The issue here is not that there is automation on Twitter," says Renée DiResta, head of policy for Data for Democracy and a founding advisor for the Center for Humane Technology. "The issue is that there are automated accounts that trying to be treated as real people, that are acting like real people, that are manipulating people."

Twitter could also do more to discourage people from creating objectionable content in the first place by making its rules more visible and digestible. Susan Benesch, whose Dangerous Speech Project is a member of Twitter's Trust and Safety Council, says she's implored executives to raise the visibility of the "Twitter Rules" policies, which outline what you can't say on the service. "They say, 'Nobody reads the rules,'" she recounts. "And I say 'That's right. And nobody reads the Constitution, but that doesn't mean we shouldn't have civics classes and try to get people to read it.'"

The company could also build trust by embracing transparency as more than a buzzword, sharing more with users and marketers about how exactly Twitter works and collaborating with outside researchers. Compared to other social-media behemoths, its business model is far less reliant on using secretive algorithms to monetize its users' data and behaviors, giving it an opportunity to be open in ways that the rest seldom are. "The way that people use Twitter, it becomes a little bit easier to see things and understand things," says Jason Kint, CEO of publisher trade group Digital Content Next. "Whereas it's incredibly difficult with YouTube and I'd say with Facebook it's fairly difficult."

Toward this more collaborative end, and inspired by research conducted by nonprofit Cortico and MIT's Laboratory for Social Machines, Twitter announced in March that it will attempt to measure its own "conversational health." It invited other organizations to participate in this process, and Twitter says it will reveal its first partners in July.

The effort is intriguing, but the crowdsourced initiative also sounds eerily similar to Twitter's Trust and Safety Council, whose mission since it was convened in February 2016 has been for advocates, academics, and grassroots organizations to provide input on the company's safety approach.

Many people who worked for Twitter want not a metric but a mea culpa. According to one source who has discussed these issues with the company's leadership, "Their response to everything was basically, 'Look, we hear you, but you can't blame Twitter for what happened. If it wasn't us, it would've been another medium.' The executives didn't own up to the fact that we are responsible, and that was one of the reasons why I quit."

Even Senator Warner believes that before his colleagues consider legislation, the tech companies' CEOs ought to testify before Congress. "I want them all, not just Dorsey. I want Mark and I want [Google cofounders] Sergey [Brin] and Larry [Page]," he said. "Don't send your lawyers, don't send the policy guys. They owe the American public an explanation."

When Twitter debuted its new health metrics initiative, the American public seemed to finally get one, after Dorsey tweeted about Twitter, "We didn't fully predict or understand the real-world negative consequences. We acknowledge that now." He continued: "We aren't proud of how people have taken advantage of our service, or our inability to address it fast enough. . . . We've focused most of our efforts on removing content against our terms, instead of building a systemic framework to help encourage more healthy debate, conversations, and critical thinking. This is the approach we now need."

One week later, Dorsey continued to acknowledge past missteps during a 47-minute live video broadcast on Twitter. "We will make mistakes-I will certainly make mistakes," he said. "I have done so in the past around this entire topic of safety, abuse, misinformation, [and] manipulation on the platform."

The point of the live stream was to talk more about measuring discourse, and Dorsey tried to answer user-submitted questions. But the hundreds of real-time comments scrolling by on the screen illustrated the immense challenge ahead. As the video continued, his feed filled with anti-Semitic and homophobic insults, caustic complaints from users who fear Twitter is silencing their beliefs, and plaintive cries for the company to stop racism. Stroking his beard, Dorsey squinted at his phone, watching the bad speech flow as he searched for the good.

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"Did We Create This Monster?" How Twitter Turned Toxic

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Yair Rosenberg wanted to troll the trolls. Rosenberg, a senior writer for Jewish-focused news-and-culture website Tablet Magazine, had become a leading target of anti-Semitic Twitter users during his reporting on the 2016 U.S. presidential campaign. Despite being pelted with slurs, he wasn't overly fixated on the Nazis who had embraced the service.

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when are we gonna highlight THIS IMPACT OF THE TECH AGE

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Gonna submit this as a Google Doodle. Fingers crossed!

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Gonna submit this as a Google Doodle. Fingers crossed! https://t.co/9tooPYlueL

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Gonna submit this as a Google Doodle. Fingers crossed! pic.twitter.com/9tooPYlueL
— joey alison sayers (@joeyalison) April 5, 2018

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Gonna submit this as a Google Doodle. Fingers crossed! https://t.co/9tooPYlueL

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Gonna submit this as a Google Doodle. Fingers crossed! https://t.co/9tooPYlueL

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Gonna submit this as a Google Doodle. Fingers crossed!

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"We don’t have a technology problem, we have a social problem."
but also social problems are becoming increasingly exacerbated by tech (see: INEQUALITIES) and also tech companies are in the hands of capitalists s o what we need to have is a socialist tech revolution? (i like this idea)

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The project is in its early days, but the discussions - and caliber of the people involved - underscored how the World Wide Web's direction in recent years has stirred a deep anxiety among some technologists. The revelations by Edward J. Snowden that the web has been used by governments for spying and the realization that companies like Amazon, Facebook and Google have become gatekeepers to our digital lives have added to concerns.

On Tuesday, Mr. Berners-Lee and Mr. Kahle and others brainstormed at the event, called the Decentralized Web Summit, over new ways that web pages could be distributed broadly without the standard control of a web server computer, as well as ways of storing scientific data without having to pay storage fees to companies like Amazon, Dropbox or Google.

Efforts at creating greater amounts of privacy and accountability, by adding more encryption to various parts of the web and archiving all versions of a web page, also came up. Such efforts would make it harder to censor content.

"Edward Snowden showed we've inadvertently built the world's largest surveillance network with the web," said Mr. Kahle, whose group organized the conference. "China can make it impossible for people there to read things, and just a few big service providers are the de facto organizers of your experience. We have the ability to change all that."

Many people conflate the internet's online services and the web as one and the same - yet they are technically quite different. The internet is a networking infrastructure, where any two machines can communicate over a variety of paths, and one local network of computers can connect with other networks.

The web, on the other hand, is a popular means to access that network of networks. But because of the way web pages are created, managed and named, the web is not fully decentralized. Take down a certain server and a certain web page becomes unavailable. Links to pages can corrode over time. Censorship systems like China's Great Firewall eliminate access to much information for most of its people. By looking at internet addresses, it is possible for governments and companies to get a good idea of who is reading which web pages.

In some ways, the efforts to change the technology of creating the web are a kind of coming-of-age story. Mr. Berners-Lee created the World Wide Web while working at CERN, the European Organization for Nuclear Research, as a tool for scientists. Today, the web still runs on technologies of the older world.

Consider payments. In many cases, people pay for things online by entering credit card information, not much different from handing a card to a merchant for an imprint.

At the session on Tuesday, computer scientists talked about how new payment technologies could increase individual control over money. For example, if people adapted the so-called ledger system by which digital currencies are used, a musician might potentially be able to sell records without intermediaries like Apple's iTunes. News sites might be able to have a system of micropayments for reading a single article, instead of counting on web ads for money.

"Ad revenue is the only model for too many people on the web now," Mr. Berners-Lee said. "People assume today's consumer has to make a deal with a marketing machine to get stuff for 'free,' even if they're horrified by what happens with their data. Imagine a world where paying for things was easy on both sides."

Mr. Kahle's Internet Archive, which exists on a combination of grants and fees from digitizing books for libraries, operates the Wayback Machine, which serves as a record of discontinued websites or early versions of pages.

To make that work now, Mr. Kahle has to search and capture a page, then give it a brand new web address. With the right kind of distributed system, he said, "the archive can have all of the versions, because there would be a permanent record located across many sites."

The movement to change how the web is built, like a surprising number of technology discussions, has an almost religious dimension.

Some of the participants are extreme privacy advocates who have created methods of building sites that can't be censored, using cryptography. Mr. Cerf said he was wary of extreme anonymity, but thought the ways that digital currencies permanently record transactions could be used to make the web more accountable.

Still, not all the major players agree on whether the web needs decentralizing.

"The web is already decentralized," Mr. Berners-Lee said. "The problem is the dominance of one search engine, one big social network, one Twitter for microblogging. We don't have a technology problem, we have a social problem."

One that can, perhaps, be solved by more technology.

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The project is in its early days, but the discussions - and caliber of the people involved - underscored how the World Wide Web's direction in recent years has stirred a deep anxiety among some technologists. The revelations by Edward J.

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As Tim Berners Lee said recently: 'We don't have a technology problem, we have a social problem.'

Perhaps the most worrying image in recent days is the slow motion scene of Zuckerberg's face as it dawns upon him that his dorm room invention is beyond his control, and beyond his comprehension. He lacks the political bandwidth to fathom what is happening, so is looking for a technological solution. It does not exist.

In the maelstrom concerning Cambridge Analytica, it has been too easy to be distracted by the conspiracies. Whether a company was able to influence an election. Whether Facebook data was stolen or shared. Whether a pro Brexit campaign overspent. These may be important questions to some - but they are not the thing that is most striking about this story.

Certainly our relationships - individually and collectively- with platforms such as Facebook need to be examined. What we knew when we signed up and what we willingly gave up are questions that we have to answer by ourselves. Together we need to demand wider discussion and education surrounding data economics, however hard the hard stuff might be. We also need to think politically about this for, in the end, Platform capitalism is about power. And it appears to be a very real disruption to the way we have been doing things.

The wide scale flow of data that is being collected across the networked landscape - from weather reports, smart meters, congestion monitors, traffic flows, consumption patterns, crime hot spots, pedometers, energy surges, happiness gauges, employee work rates, public transit schedules, stock market fluctuations. This information is always mediated, and always unevenly distributed. And the results of this can be seen in the redistribution of power and formation of new inequalities.

It is increasingly more difficult to find the edges between the private and the public world. This is intentional. From the outset, developers like the visionary Mark Weiser's at Xerox PARC hoped that "the most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.' When it is no longer possible to tell where the network ends, we are in trouble.'

The exposure of the inequality of information is perhaps the most pernicious result of the current 'scandal'. It may soon be proved - and it would not be surprising at all - that the claims of psychographic skills are wholly overblown. The idea that big data offers insights beyond the imagination is somewhat doubtful beyond the marketing hot air. Even after that is disposed of, the more dangerous consequence remains the inequalities that emerge from uneven access to data. Who has access, and who does not, has become a new political economy and like every currency, there are deep social consequences.

The first is the threat to privacy. It was Edward Snowden who said: "Privacy is the right to a self . . . Privacy is what gives you the ability to share with the world who you are on your own terms." But the ability to share, and to withhold, or to take back, private information is becoming increasingly difficult.

Richard Clarke, the former White House security chief, announced in June 2015: 'over time, there will be fewer people who recall pre-Information Age privacy, more people who will have grown up with few expectations of privacy.' He later made it clear that future expectation for privacy would also be unequally distributed: 'Privacy may then be a commodity that only the wealthy can acquire.' So privacy becomes a luxury that only the rich can afford. As one commentator wittily puts it: 'it is Orwellian if it is accurate, Kafkaesque if wrong.'

Secondly, we need to acknowledge the relationship between inequality and trust. You cannot see trust, you can only perceive the consequences of its absence, or the benefits of its influence. It is invisible, but it can be found in many different places: religious experience ('trust the Lord'), as well as the scientific laboratory, ('trust your eyes'); it is to be hoped for by politicians at the stump ('trust in me') and with the handshake to seal the deal ('my word is my bond'). But it can also be found in the small transactions and interactions that we daily navigate: between individuals and amongst groups and institutions, or in the relationship between the city and the citizen. It can come with obligations and strictures on time, behaviour, reciprocity or even threat. Trust assumes an order of things, and a universally agreed norm of behaviour. But how does it work?

For political scientists like Francis Fukuyama trust forms the bedrock of a market economy: 'one of the most important lessons we can learn from an examination of economic life is that a nation's well-being, as well as its ability to compete, is conditioned by a single, pervasive cultural characteristic: the level of trust inherent in the society.'

This is illustrated by a thought experiment: a buyer and a seller decide to do a deal but agree that they will both bring a closed bag to the meeting and exchange bags without looking inside. What social pressures will encourage the buyer to put the full sum of cash into his bag; will the merchant risk his reputation by defrauding his customer? Fukuyama suggests that a marketplace without a sufficient level of trust levies a disadvantageous reputation upon itself. The lack of trust will eventually cost a society dear.

In Fukuyama's city, everything has been reduced to the marketplace, everything has a price and can be exchanged; one invests in order to get something out: A trusts B so that X will happen. It is trust, Fukuyama argues, that underpinned the rise of the West and could be found in the development of the rule of law in opposition to absolutism, religious tolerance which allowed every merchant to be equal on the trading floor, as well as the rise of urbanism that was a refuge of freedom away from the obligations of the ancien regime.

Robert Putnam, author of 'Bowling Alone', proposes an alternative definition of trust. For Putnam trust and sociability are connected: trust grows out of us being together, and is nurtured in the associations, bowling teams, church congregations that hold a community together. Trust disappears when we spend less time with each other: 'people who trust each other are all-round good citizens, and those more engaged in community life are both more trusting and more trustworthy.' Trust thus accrues social capital, a form of currency that can be exchanged and put to profit in a number of different ways. In this view, one does not trust solely because of its instant advantages, but also has long term benefits.

Alternatively, for the German sociologist, Niklas Luhmann, trust is a means to controlling the future, a sophisticated symbolic means to mitigate risk. Others believe that trust results from rights, and can only exist in places where the rights of the individual are respected. Therefore, in totalitarian states or dictatorships trust becomes a defiant act, and on occasions even be an act of revolution. Vaclav Havel in the face of Czechoslovakian suppression included trust as one arrow in the quiver of the 'power of the powerless'.

For Eric Uslaner, trust is not the result of business deals or social interaction, but was hard-wired into our social selves, based on a basic belief in the goodwill of others. Trust came first. It is not based on a set of relationships at a certain moment - a calculation that trusting will produce benefits - but a general trusting: 'A trusts B to do X' is replaced by 'A trusts'. Trust is therefore connected to optimism, confidence, tolerance and well being, not just strategic reckoning.

This type of trust, for Uslaner, leads to social engagement rather than the negotiated results of coming together. Better cooperation then leads to the promotion of equality, policies of democracy and a belief in generalised rights. the generalised truster is 'happier in their personal lives and believe that they are masters of their own fate. They are tolerant of people who are different from themselves and believe that dealing with strangers opens up opportunities more than it entails risks'.

But it seems increasingly difficult to expect to find trust within our everyday lives. This generalised trust has, for some reason, plummeted in the past decades. This is because distrust goes hand in hand with the rise of inequality. As Uslaner points out, inequality undermines the sense of common purpose and ownership, it attacks optimism and a sense of being in control of one's fate. This is the same conclusion that Richard Wilkinson and Kate Pickett came to in 'The Spirit Level': 'think of trust as an important marker of the ways in which greater material equality can help create a cohesive, co-operative community, to the benefit of all.'

The impact of this growing inequality and distrust has been clear on the physical fabric of the city: in the dividing up of neighbourhoods and the privatisation of public spaces. But it can also be more clearly seen in the data sphere. Especially when it appears that everything, and everyone, can be reduced to data.

The recent book called 'Everybody Lies' proposes that computation thinking by Big Data is more useful - and truthful - than previous forms of knowledge making. The book states 'Big Data allows us to finally see what people really want and really do, not what they say they want and say they do'. The author continues with the bold claim that the collected set of Google searches constitutes the 'most important data set ever collected on the human psyche.'

Is he saying that we should not longer trust people on what they say and do, only on the digital traces that they leave across the networked platform? Are we meant to discount everything we know about another person which does not appear on some harvested data set? Are we, therefore, nothing more than the sum of our data. What happens when this belief in the primacy of data over all other forms of knowledge.

This can be seen in particular in the issue of social credit that is currently being developed by the Chinese government. Here, a digital system of surveillance has been put together that produces a 3 digit sincerity score that can rise and fall, depending on your transactions, behaviour and social interactions. This number replaces all other forms of reputation and trust. This in effect is taking credit scoring as a tool of social discipline to its logical conclusion.

Furthermore, we see it in the claims of the Blockchain, the distributed ledger that replaces the need for any other system of trust. At the heart of the Bitcoin cryptocurrency bubble, the blockchain is claimed to be the solution to diverse problems of smart contracts, rights management, transaction records as well as plethora of other get rich quick CPOs. But there is very little proof yet that it is up to the job and that it is an adequate replacement for trust. But does it really do this, or does it demand that we exchange one form of trust for another. we go from trusting an institution - a bank, a lawyer's firm, an archive - for another: an algorithmic black box. Ironically, this black box claims to be more transparent than any previous arrangement, the solution to problems of technology's making in the first place.

But the greatest threat posed by the imbalance of data resulting from Platform Capitalism, is the loss of trust in democracy.

Our democratic future depends on the equitable access to this information. But this is increasingly being denied. In fact within the new 'political, economic and cultural arrangement of institutions and network devices', as Philip N. Howard notes in hisfascinating Pax Technica, new relationships and power structures are being drafted between traditional political offices and those who are in control of the data flows. There seems to be little space for the citizen in this new politics, except as the subject of rent and a source of data.

It is no irony therefore that the first book selected by Mark Zuckerberg's book club was 'The End of Power', which has little time for the messiness of democracy, noting: 'Politics was always the art of the compromise, but now politics is downright frustrating - sometimes it feels like the art of nothing at all.' Reduce everything to the data, he seems to be saying, you no longer need to listen, discuss, negotiate: data, and those who control it, will dictate what is the right thing to do.

This is the thing we should be thinking about when we think about the news of robbed elections and data breaches.

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Trust: Data, Cities, Democracy - Leo Hollis - Medium

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As Tim Berners Lee said recently: 'We don't have a technology problem, we have a social problem.' Perhaps the most worrying image in recent days is the slow motion scene of Zuckerberg's face as it dawns upon him that his dorm room invention is beyond his control, and beyond his comprehension.

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YES MEMES ARE CHANGING THE WAY WE INTERACT WITH THE WORLD! THE PARTICIPATORY NATURE OF THEM ENGAGES YOUNG PPL WHO ARE DISILLUSIONED WITH THE WORLD BC IT IS U S WHO IS CREATING THE CONTENT, NOT MNCS!! GOVERNMENTS CAN'T KEEP UP WITH HOW EFFECTIVE MEMES ARE!!
also: this form of production is not something most "milennials" will feasibly be able to do in their jobs!!

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"Slogans in nice typefaces won't save the human races," reads a large red poster with yellow and black lettering in Johnston font - the same as on the London Underground - at the Design Museum's new exhibition, Hope to Nope, which opened last week in London. The show traces a ten-year history of graphic design and technology in the context of political messaging; a decade on from the financial crisis, and the wave of civil unrest it helped to spark across the world, the show hinges on showcasing protest and resistance as they become more and more prominent features of our daily landscape.

'Slogans', from artist Oddly Head, went up in London, Bristol, Manchester and Glasgow - its message designed to rouse urbanites from merely touting pretty placards to go beyond the performance of protest, and act. Its hopefulness - and the uncomfortable relationship it betrays with a more classic, contemplative school of graphic design - resonated with the museum curators' rebellious ambitions here, and the battle-cry made by so many of the show's surrounding scraps, placards and images: a fitting tribute to the self-conscious place of graphic design in an age of digitised protest.

Despite this emphasis on defiance, the exhibition's main story is one of rampant polarisation and growing volatility, in tones of increasingly sardonic dejection. Hope to Nope charts a trajectory from the heady days of Obama's first campaign - albeit against a backdrop of unfolding crisis - and Shepard Fairey's iconic pop HOPE poster, to the same image remodelled with a derisive NOPE below the cartoonish face of Donald Trump, his toupee akimbo. That 'nope' was not, in the end, the answer given by the US electorate is just one of the ironies this map throws up. In today's looking glass world, Trump's clownish image has become a kind of avatar for the creeping memeification of our political culture, in all its "Sad!" cynical mirth.

Read next

The show sketches a timeline of the internet's history in the context of protest. It's a shock to remember that it has only been about ten years since the iPhone launched and the first hashtag took root on Twitter, in 2007. In just 13 years, we've seen the launch of Youtube, WhatsApp, Facebook, Twitter, WeChat and Instagram; Facebook has gone from its infancy to having two billion active users; 160,000 people tweeted #OccupyGezi in 2013; by 2017, well over 12 million people have shared experiences of sexual assault using the hashtag #MeToo.

A mark of how fast things change in this wild west: the timeline stops just shy of the Facebook/Cambridge Analytica revelations that have exploded in the past couple of weeks, recording as its last entry Facebook's admission that 120 Russian-backed pages reached 126 million Americans during the 2016 presidential election. The Design Museum curators are hoping to incorporate this latest piece of history - and to include images from a Russian troll farm which automatically aggregates and mass-produces memes in Impact font. Many of them come from a section of the site appropriately called "Demotivators".

Throughout the exhibition there is the recurrent idea that the web is changing the nature of design, accelerating the process of creation, putting it into the hands of ordinary people and allowing any odd image to acquire a life of its own. The speed of our interconnection is ushering in a "weird circular dialogue that happens really, really quickly - so fast that it's impossible to catch up with," says David Shaw, one of three curators behind the show along with Lucienne Roberts and Rebecca Wright. These graphics spread like wildfire - the meaning of the word ' meme ' - and Roberts notes that many of them are "designed with social media in mind," resulting in more conscious and unconscious performativity in what people produce.

More, the web is changing the way we act as political subjects: the sidelong sniggers in which memes traffic are more common not only where memes live - Reddit, Instagram, the internet at large - but in offline cultures too. These days, everybody loves themself a dank meme - pussies grab back wearing pink cat hats. 'We shall overcomb' reads placard after placard. The absolute boy has no time for centrist dads and the Maybot is queen of the melts. Even Hillary Clinton is in time to pun that 'Love trumps hate'. And then there's Trump, the overweening memelord, whose face was recently created out of little else but sliced ham.

Against digital saturation there is also resistance: many of the most striking objects and images in the exhibition broke with network culture almost entirely, seemingly rejecting the internet's intangible world to make physical things with their own design logic. On show are a host of zines from Strike to the Occupied Times; there's a Corbyn t-shirt with a Nike tick, a Black Lives Matter quilt, notes of currency from London's Brixton Pound, pro-Brexit beer-mats from J.D. Wetherspoons, Sour Brexit fizzy drinks. Sitting in a glass box, a 'Make America Great Again' baseball cap with Times New Roman font dissolves the corporate façade of modern politics.

Read next

In one corner of the exhibition is propped a large green heart, with green tissue pasted on a chicken-wire frame. It is one of 24 made for those who died in the Grenfell fire - one for each level of the tower. Sophie Lodge, the artist behind the #24hearts series, employed a similar design to that used in London's symbolic Underground, poignantly subverting the clean lines of that logo, twisting the circle into a heart as though depicting the humanity of those who actually use the tube, and the inhabitants of the tower neglected by the city they called home. Its lettering done in a naïve hand, the heart's design strives to communicate the love of those carrying it, and for that love to be shared as widely as possible - on Facebook, Instagram and Twitter.

This DIY style advances an idea of authenticity based in advertising its separation from online life. "I think for some of these protesters it has more veracity too because they can make it with their own hands... It's not that your banner is effective because it's beautifully designed and nicely type-spaced, and has lovely margins, and Pantone colours - it's because you made it yourself," Shaw says. On show are pamphlets disseminated by those involved in Occupy, and dollar bills they've branded with the enduring slogan, "We are the 99%".

Their "emphasis is on education and do-it-yourself," Shaw says, and shows a "fantastic attitude that the only way to change the system is to make your own system and do your own thing." But then again, as the Occupy slogan-which-was-also-a-hashtag implies, nothing is ever that far from the internet's reaches, and the 'authenticity' offered by so many of the more radical works on show has also been folded right back into internet culture: ugly, scrappy images superseding slick design. Cartoon Pepe the Frog came from a comic and was appropriated by the alt-right in 2015; its artist Matt Furie is currently suing Infowars.

The best of these works went beyond making proclamations to make something new. In recent years, books such as Zeynep Tüfekçi's Twitter and Tear Gas: The Power and Fragility of Networked Protest have told a dual story of how social media is affecting the nature of protest - producing aggregate swells alongside a different kind of social organisation with its eye less on the long-term. This exhibition updates that story, to show how the graphic design of protest in the digital era is subject to constant shudders and modifications - it cannot afford to stick to type and image if it wants to make an impact. As for memes, who doesn't love a good meme - but there is also a worry that they can be "very reductive," to use Roberts' words. "I think the problem is how we get people to engage in politics on a deeper level."
Hope to Nope runs at London's Design Museum until August 12, 2018

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From Gezi Park to Grenfell, memes are changing how we protest

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"Slogans in nice typefaces won't save the human races," reads a large red poster with yellow and black lettering in Johnston font - the same as on the London Underground - at the Design Museum's new exhibition, Hope to Nope, which opened last week in London.

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so not only is it generally wild that people can steal that much money online, but also how it strengthens the idea of being "good at tech" as the ultimate ideal;

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Breaking into a bank doesn't require drilling through 20 inches of reinforced concrete. In fact, you don't even need to enter a vault at all. Towards the end of 2013, ATMs in Ukraine started spitting out free cash to passers-by. Among those filling their pockets were mules waiting for the money to be dispensed.

The ATMs of affected banks - none of which have ever been named - had been targeted by hackers installing malware within the financial institutions' computer systems. Once compromised, the cash machines could be remotely controlled and made to dish out money at will.

One organisation lost $7.3 million from ATM fraud, security company Kaspersky detailed following the attacks in 2015. "There will be hundreds of people [involved]," says Sergey Golovanov, a principal security researcher at the Russian cybersecurity firm. "Dozens of people that are working 27/4, that would be the real scale of the Carbanak group."

The Carbanak cybercrime group, named after one piece of malware it used to access banking systems, is suspected of stealing €1 billion from financial organisations since its early attacks in 2013 and has targeted more than 100 financial institutions in at least 40 countries. The UK, Spain and Russia are among the countries targeted within the last four years.

Golovanov, who was first to publicly detail the group's activities three years ago, likens its work to that of state-sponsored hackers, taking several months to complete its attacks. Kaspersky's 2015 research says spoofing ATMs into dispensing cash is just one way the group has made money.

Carbanak also infiltrated the systems of banks to transfer money into its own accounts and altered databases. It would artificially inflate the amount of money in an account and then transfer this to other accounts. One financial group is claimed to have lost $10 million due to the exploitation of its online banking platform.

Each time a hit happened, there was one thing in common: members of the group were inside the bank's internal systems. "Carbanak [malware] contains an espionage component that allows the attackers to take control of video capabilities on the victim systems," Golovanov's 2015 report said. The surveillance allowed attackers to understand what genuine transactions would look like, making their theft look genuine.

"They will drop millions and these millions will be pushed through the money laundering system," Golovanov says. "And then on to the next target."

Cocaine, tug boats and tip offs: the inside story of the largest drug bust in UK history

As temperatures in Alicante, Spain, hit highs of 18°C on March 6, 2018, around 20 law enforcement officials swooped on a house in the city. Inside they arrested a man they say is the head of the billion Euro Carbanak cybercrime group. He has been named by Spain's Interior Ministry as 'Denis K' and is said to be Ukrainian.

Spanish authorities and Europol announced the arrest last week after what they called a "complex" investigation. The investigation into his alleged activities is continuing with law enforcement examining the computers and devices found in his home.

The hunt for Carbanak's leader involved financial groups that had lost money, the FBI, Moldovan, Belarussian and Taiwanese authorities. In making the arrest, Europol confirmed Kaspersky's 2015 research. "This is something we have been waiting for for a long time," explains Fernando Ruiz, the head of operations at Europol's European Cybercrime Centre (EC3).

Ruiz claims the arrested man was the mastermind at the head of the Carbanak cybercriminals. "We consider this as one of the most important arrests in the last years because this person, arrested in Spain, was the person actually coding the malware," he explains. Europol has also stated the group was developing the malware it used.

"This person was technically excellent, he was able to identify vulnerabilities and code the malware to exploit these vulnerabilities." Ruiz, who helped to coordinate international efforts to track down members of Carbanak, claims. He also believes the group was planning more cyberattacks against financial groups. "There are not many criminals with this knowledge, with this capacity to develop this kind of malware," he says. There was, Ruiz states, "new malware recently tested and recently produced, ready to be deployed."

Legal proceedings against Denis K are ongoing. It is now up to police and prosecutors to prove the allegations they have made against him. So far, Europol has not revealed any public evidence to back-up its claims.

Separately, Spanish police inspector Carlos Yuste told he believes Denis K worked with three other gang members, who didn't know each other and chatted online. Ruiz adds the arrested man was on the radar of Spanish authorities for "quite some time" but it needed international law enforcement to help build a case.

The key to tracking the man down to his Alicante home was through Taiwan and Belarus, Ruiz says. A report from Europol and security company Trend Micro published last year details how both countries saw ATMs dispensing cash to mules.

The report says $2.5m (£1.78m) was stolen from 41 Wincor Nixdorf ATMs operated by First Commercial Bank in Taiwan during July 2016 "without using cash cards or even touching the PIN pads". After the attack arrests were made and malware was found within the bank's system. "These were one of the typical ATM network attacks in Taiwan. They got access to the network in Taiwan and cashed out the money to mules," Ruiz says.

"The police were able to arrest a number of these mules so we started to co-operate with Taiwan to see where this was coming from. This was an important element as this led to a group in Belarus and there we were able to connect this target. We were able to connect Taiwan, Belarus and Spain through the information exchanged with partners."

Europol says "criminal profits" were laundered via cryptocurrencies. "Prepaid cards linked to the cryptocurrency wallets which were used to buy goods such as luxury cars and houses," the international agency said in its statement.

A report in El Mundo, Spain's second-largest newspaper, claims Denis K owned 15,000 bitcoins (currently valued around £84m) at the time of his arrest. Catalan newspaper El Periódico de Catalunya reported that the arrested man lived with his wife and son, drove two BMWs and had jewellery valued at €500,000 within the home. Police did not know what technical equipment may be inside the house so sent an array of digital experts to examine it, Ruiz says.

When a tanker vanishes, all the evidence points to Russia

Carbanak's criminal infrastructure may have been sophisticated but its initial methods of getting inside banks has been reassuringly familiar. Both security firm Kaspersky and Europol say spear-phishing emails were sent to members of staff.

Starting around 2013 legitimate-looking email messages were sent to members of staff inside banking organisations. As is common with spear-phishing campaigns these appear to be sent from trusted senders and included attachments in the form of Word 97-2003 documents or control panel files.

Around the end of 2014, before Kaspersky published its report, two other security companies Group-IB and Fox-IT spotted the crimes of the Carbanak group and noted it was using malware called Anunak. The two firms later said all the companies were looking at the same cybercrimes.

Kaspersky's original report claims the malware contained within the attachments exploited vulnerabilities within Word and Office to open a backdoor called Carbanak. This backdoor, which was based on Carberp malware, allows for "espionage, data exfiltration and to provide remote access to infected machines". From here, Kaspersky says, attackers were within the networks of financial groups and could conduct surveillance on usual activity and then replicate it to steal money.

Once downloaded, the malicious software allowed the criminals to remotely control the victims' infected machines, giving them access to the internal banking network and infecting the servers controlling the ATMs. This provided them with the knowledge they needed to cash out the money.

"We have seen an evolution in how criminals have been targeting the financial networks," Ruiz says. From 2016, it is claimed, the malware used by the Carbanak group was changed. It started to use "tailor-made malware" that was based on the Cobalt Strike penetration testing software. Cobalt Strike is legitimate piece of software that's used to simulate cyberattacks and its modification by Carbanak was used to remotely control PCs.

"It wasn't just one type of malware, it was several types of malware," says Keith Gross, the chair of the European Banking Federation's (EBF) cybersecurity working group. The investigation into Carbanak was the first time the EBF has actively worked with Europol ahead of an arrest being made.

"The mastermind was getting more sophisticated types of malware and improving on the existing types of malware," Gross adds. "I believe there was a treasure trove of information gleaned from his arrest in terms of the equipment seized by Spanish law enforcement. A Pandora's box so to speak."

It's currently unknown exactly how many other people may have been working for the Carbanak group and officials still need to prove to courts that Denis K is guilty of the alleged crimes. Yuste told Bloomberg "the head has been cut off". However, Kaspersky's Golovanov says there may still be some activity from the group. "Right now we see that the infrastructure criminals were using for their robbery is still operational," Golovanov says. "We've predicted there will be less scale and it will be much less easier for them to work."

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Inside the takedown of the alleged €1bn cyber bank robber

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Breaking into a bank doesn't require drilling through 20 inches of reinforced concrete. In fact, you don't even need to enter a vault at all. Towards the end of 2013, ATMs in Ukraine started spitting out free cash to passers-by. Among those filling their pockets were mules waiting for the money to be dispensed.

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why does ""fake news"" exist? because clicks!!

"Social media has exacerbated and monetized fake news but the source of the problem is advertising-subsidized journalism... So long as our attention is up for sale, people with all sorts of motives will pay top dollar."

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The Daily Beast ran a story last week with this lede: "Roseanne Barr and Michael McFaul argued with her on Twitter. BuzzFeed and The New York Times cited her tweets. But Jenna Abrams was the fictional creation of a Russian troll farm." Abrams, the story goes, was a concoction of The Internet Research Agency, the Russian government's troll farm that was first profiled in New York Times Magazine by Adrian Chen in June 2015. During its three-year life span the Abrams account was able to amass close to 70,000 followers on Twitter and was quoted in nearly every major news outlet in America and Europe including The New York Times, The BBC, and France 24.

The Abrams Twitter account was a well of viral content that over-worked listicle writers couldn't help but return to. Once the account had amassed a following the content shifted away from innocuous virality to offensive trolling: saying the civil war wasn't about slavery, mocking Black Lives Matter activists, and jumping on hashtags that were critical of Clinton. "When Abrams joined in with an anti-Clinton hashtag," The Daily Beast reports, " The Washington Post included her tweet in its own coverage. One outlet used an image of a terrorist attack sourced from Abrams' Twitter feed."

The Abrams account, they write, "illustrates how Russian talking points can seep into American mainstream media without even a single dollar spent on advertising." This framing portrays journalists as passive filters that automatically parrot whatever popular Twitter users say. Journalists are supposed to be critical fact-checkers and the last defense against misinformation entering the public sphere. The rate at which false information keeps "seeping" in seems to be growing, and so it is worth asking: are there structural reasons that fake news keeps making its way into reputable news sources?

Jay Rosen is the obvious person to answer this question, and to some degree he did answer it last March when he announced a partnership with the Dutch news site De Correspondent: "if you're doing public service journalism" he wrote, "and trying to optimize for trust, it helps immensely to be free from the business of buying and selling people's attention." Not having commercial sponsors also means, "not straining to find a unique angle into a story that the entire press pack is chewing on, it's easier to avoid clickbait headlines, which undo trust. Not chasing today's splashy story can hurt your traffic, but when you're not selling traffic (because you don't have advertisers) the pain is minimized."

It is frustrating that prominent public radio personalities like Ira Glass are running in the opposite direction. Glass, talking to an AdAge reporter in 2015 confidently stated, "Public radio is ready for capitalism." This is dangerous because much of Russia's disinformation campaign and Trump's home-grown trolling relied on the capitalist attention economy that governs every major media outlet. Breitbart and InfoWars republished Abrams' tweets, but so did The Washington Post and The Times of India. The only thing these news organizations have in common is their advertiser-centered business model.

It's no secret that most staff writers are underpaid and over-worked, and they are the lucky ones. There are thousands of wildly talented freelance writers that spend half their time writing and reporting and the other half chasing down their overdue paychecks. Reporters with no research budget and a huge publishing quota are understandably going to do a bit of Googling, pull a quote from Twitter, and call it a day. Over-worked and under-paid journalists are the weakened immune system that lets viral fake news take over the body politic.

Herman and Chomsky, in their famous book Manufacturing Consent, pointed to the high cost and time-consuming nature of good journalism as one of the five "filters" that discourage critical reporting. Instead of going to the source of the story, journalists go to police departments and corporate PR offices to grab quotes. This is not because they are lazy, but because they lack the time or money to report the story from scratch. PR offices and police departments' spokespeople offer one-stop-shops for an official account of what happened in any given story.

The Yes Men-two artists who, for example, will pose as the spokesperson for Dow Chemical and tell a BBC reporter that they take full responsibility for the Bhopal Disaster - know that news agencies are more likely to report on something if they are handed a media package or are offered access to a talking head from a well-known organization. Their hoaxes have real consequences: sending corporate stocks temporarily tumbling and attracting mainstream attention to ignored environmental disasters.

Twitter affords a similar shortcut to newsworthiness. Putting someone with a high follower count (to say nothing of a blue checkmark) in your story increases the possibility of reciprocal attention: you click my content and I'll click yours. When someone with 70,000 followers says something controversial to their substantial audience, that's worth a shout out in your news story, especially when that story is little more than a survey of what people are talking about. That Twitter user, after seeing a spike in followers and mentions related to the article, will share it themselves sending off a quick, "was included in this thing, haha." This is the mundane, reciprocal manufacturing of attention that feeds micro celebrity and now, apparently, geopolitics. Anything with a decent follower account is low-hanging fruit for finishing a reporter's daily content quota.

What is absolutely maddening is that the demands and responses to the fake news phenomenon have centered on social media and the algorithms that govern their behavior. Some of the solutions out there -cough Verrit cough- are either so absurd that they can only be explained as either the product of cynical opportunists looking to make fact-flavored content, or the result of too many well-connected people not understanding the nature of the problem they are facing. Both seem equally likely. The intent barely matters though, because the result is the same: a more elaborate apparatus to churn out attention-grabbing media for its own sake.

Social media has exacerbated and monetized fake news but the source of the problem is advertising-subsidized journalism. Any proposed solution that does not confront the working conditions of reporters is a band aid on a bullet wound. The problem is systematic, which means any one actor -whether it is Mark Zukerberg or Facebook itself- is neither the culprit nor the possible savior. So long as our attention is up for sale, people with all sorts of motives will pay top dollar.
Image courtesy Free Press

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Want to End Fake News? Stop Subsidizing Journalism with Advertising

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The Daily Beast ran a story last week with this lede: "Roseanne Barr and Michael McFaul argued with her on Twitter. BuzzFeed and The New York Times cited her tweets. But Jenna Abrams was the fictional creation of a Russian troll farm."

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"allowing misuse-related considerations to influence research priorities and norms, and proactively reaching out to relevant actors when harmful applications are foreseeable"

WE NEED TO CRITICALLY CONSIDER ~WHO IS PRODUCING AI ~WHY THEY ARE
in western countries if its by governments, its most likely for military services
for multinational corps, its probably to increase advertising revenue

AI is anyways so expensive WHO holds these resources and HOW to we limit the potential misuse of this kind of tech!

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Image: Shutterstock

When we think about artificial intelligence, we tend to think of the humanized representations of machine learning like Siri or Alexa, but the truth is that AI is all around us, mostly running as a background process. This slow creep of AI into everything from medicine to finance can be hard to appreciate if for no other reason than it looks a lot different than the AI dreamt up by Hollywood in films like Ex Machina or Her. In fact, most 'artificial intelligence' today is quite stupid when compared to a human-a machine learning algorithm might be able to wallop a human at a specific task, such as playing a game of Go, and still struggle at far more mundane tasks like telling a turtle apart from a gun.

Nevertheless, a group of 26 leading AI researchers met in Oxford last February to discuss how superhuman artificial intelligence may be deployed for malicious ends in the future. The result of this two-day conference was a sweeping 100-page report published today that delves into the risks posed by AI in the wrong hands, and strategies for mitigating these risks.

One of the four high-level recommendations made by the working group was that "researchers and engineers in artificial intelligence should take the dual-use nature of their work seriously, allowing misuse-related considerations to influence research priorities and norms, and proactively reaching out to relevant actors when harmful applications are foreseeable."

This recommendation is particularly relevant in light of the recent rise of "deepfakes," a machine learning method mostly used to swap Hollywood actresses' faces onto porn performers' bodies. As first reported by Motherboard's Sam Cole, these deep fakes were made possible by adapting an open source machine learning library called TensorFlow, originally developed by Google engineers. Deepfakes underscores the dual use nature of machine learning tools and also raises the question of who should have access to these tools.

Read More: We Are Truly Fucked: Everyone Is Making AI-Generated Fake Porn Now

Although deepfakes is specifically mentioned in the report, the researchers also highlight the use of similar techniques to manipulate videos of world leaders as a threat to political security, one of the three threat domains considered by the researchers. One need only imagine a fake video of Trump declaring war on North Korea surfacing in Pyongyang and the fallout that would result to understand what is at stake. Moreover, the researchers saw the use of AI to enable unprecedented levels of mass surveillance through data analysis and mass persuasion through targeted propaganda as other areas of political concern.

The other two areas considered to be major risks for malicious AI are digital and physical security. In terms of digital security, the use of AI to carry out cyberattacks will "alleviate the existing tradeoff between the scale and efficiency of the attacks." This might take the form of AI performing labor intensive cyberattacks like phishing at scale, or more sophisticated forms of attacks such as using speech synthesis to impersonate a victim.

In terms of physical AI threats, the researchers looked at the increasing reliance of the physical world on automated systems. As more smart homes and self-driving cars come online, AI could be used to subvert these systems and cause catastrophic damage. Then there's the threat of purposefully made malicious AI systems, such as autonomous weapons or micro-drone swarms.

Some of these scenarios, like plagues of autonomous microdrones, seem pretty far off, while others, such as large scale cyberattacks, autonomous weapons, and video manipulation are already causing problems. In order to combat these threats, and ensure that AI is used to the benefit of humanity, the researchers recommend developing new policy solutions and exploring different "openness models" to mitigate the risks of AI. For example, the researchers suggest that central access licensing models could ensure that AI technologies don't fall into the wrong hands, or instituting some sort of monitoring program to keep tabs on the use of AI resources.

"Current trends emphasize widespread open access to cutting-edge research and development achievements," the report's authors write. "If these trends continue for the next 5 years, we expect the ability of attackers to cause harm with digital and robotic systems to significantly increase."

On the other hand, the researchers recognize that the proliferation of open-source AI technologies will also increasingly attract the attention of policy makers and regulators, who will impose more limitations on these technologies. As for the specific form these policies should take, this will have to be hashed out at local, national and international levels.

"There remain many disagreements between the co-authors of this report, let alone amongst the various expert communities out in the world," the report concludes. "Many of these disagreements will not be resolved until we get more data as the various threats and responses unfold, but this uncertainty and expert disagreement should not paralyze us from taking precautionary action today."

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Top Researchers Write 100-Page Report Warning About AI Threat to Humanity

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Image: Shutterstock When we think about artificial intelligence, we tend to think of the humanized representations of machine learning like Siri or Alexa, but the truth is that AI is all around us, mostly running as a background process.

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WHAT can the public/an individual do in response to this - an effective way of change is always protesting, but would this hypothetical protest get the reach it'd need to even potentially make a change (i.e. 100k+ people)
this is the most worrying part - what can an individual do? deleting facebook does nothing? not to mention, it is still a small elite group of people who are even aware of the issue, and can follow the story! the overall murkiness prevents a strong response - therefore, does it rely on the state to protect us and be stronger in enforcing policy? (yes, in my opinion BUT that would require states to like its people more than it likes capitalism which is a tough sell)

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As Facebook's ongoing crisis over the Cambridge Analytica revelations escalates, a chorus of discontented voices, mostly on Twitter, is growing. "#DeleteFacebook," they murmur, while the really virtuous among us say "If I had a Facebook account I'd delete it, but I don't, so I can't! "

Even WhatsApp co-founder Brian Acton, who sold his company to Facebook in 2014 for £11.4 billion, has added his voice to the murmuring masses. "It is time. #deletefacebook," Acton, who left Facebook last year, wrote in a tweet that has since been retweeted 24,000 times.

Facebook has faced numerous controversies in the past, but this one is hitting it hard. In the three days after the revelations its share price slid by nine per cent, wiping almost £35 billion of the company's valuation, and billions more from Mark Zuckerberg's personal wealth.

But why is this controversy the one that finally seems to have people reaching for - or at least talking about - the "delete my account" button? Facebook has a long history of failing to disclose and discover wrongdoing on its platform, and is often accused of turning a blind eye while it is abused by people seeking to spread hatred, lies or subvert democracy.

The evidence in the Cambridge Analytica case is pretty damning. In 2014, Cambridge Analytica used personal information taken without authorisation from more than 50 million Facebook users to build a system that profiled US voters. In 2015, Facebook found out that this had happened but didn't warn users about it. Eventually, in 2016, it did ask the firm that had originally harvested the information, a company called Global Science Research, to delete the data, but Facebook never actually checked GSR's computers to ensure that it really was deleted.

This is the smoking gun at the centre of the Facebook and Cambridge Analytica story

Shocking though the Cambridge Analytica revelations are, it's just another example of Facebook failing, or refusing, to stop people abusing its platform. It was only after the US Congress pressed Facebook for details about Russian interference in the 2016 election that the social network revealed a cache of 3,000 adverts linked to the Kremlin and intended to sway voters towards Donald Trump and admitted that as many as 150 million Americans may have been exposed to content from Russian's Internet Research Agency. The Department of Justice's indictment against 13 Russians and three companies, released in February, repeatedly details how Russia used Facebook and Instagram to spread divisive adverts around the time of the election.

In the UK, Facebook has been reticent about sharing evidence with a Parliament select committee investigating whether Russia used social media to influence the Brexit vote in the UK. "You have all the information," said Ian Lucas MP during an evidence session in early February. "You won't show it to us." Facebook subsequently wrote to Parliament to say that beyond three Russian-bought adverts, it could find no evidence that Russia used Facebook to interfere with the election.

But are years of dubious practices enough to get people to actually quit Facebook? Aaron Balick, psychoanalyst and author of The Psychodynamics of Social Networking doesn't think so. "People have kind of known what's now all over the press and they haven't left yet, and I don't think that this is going to push them over the edge because I think the convenience of relating over Facebook outweighs the concerns about privacy," he says.

In other words, Facebook is already too useful to too many people. "At this stage Facebook has become integrated into our relational lives," Balick says. "Social media just appeals to those psychological basic drives, to express ourselves and to relate to other people."

When Zuckerberg finally decided to speak out about Cambridge Analytica he was challenged about the #DeleteFacebook movement. The New York Times directly asked him if he'd seen an impact.

"I don't think we've seen a meaningful number of people act on that, but, you know, it's not good," Zuckerberg said. "I think it's a clear signal that this is a major trust issue for people, and I understand that. And whether people delete their app over it or just don't feel good about using Facebook, that's a big issue that I think we have a responsibility to rectify"

Balick thinks that while people are aware that they're giving up their data in order to use Facebook, they don't necessarily see how this links up to bigger, global stories like the Cambridge Analytica saga. When people use Facebook, they're engaging on a really local level - talking to friends, sharing photos of dogs, that kind of thing. "On a daily basis they're just not thinking on a global basis," he says. "And people make judgements based on local experience rather than global experience."

Tech Bro Translator: Zuckerberg's 935-word non-apology apology

Even if people were to leave Facebook, it takes more than deleting your account to completely rid yourself of links to the company. The overall Facebook family of companies is a sprawling web that touches billions of people's lives. Facebook owns Instagram and WhatsApp, as well as the standalone Messenger app. Instagram, which is popular with younger users already turning their backs on Facebook, is edging towards one billion monthly users while Messenger and WhatsApp have already passed the figure. Four out of 2017's most-downloaded iOS apps are all owned by Facebook.

Simply put, leaving Facebook won't necessarily lessen that impact that the platform plays in our lives. Facebook has 2.2 billion users globally, and for many of them, the social platform is synonymous with the internet itself. While some of us have the luxury of cutting Facebook out of our lives, for many it is the easiest way to stay in touch and meet new people, organise protests and develop movements.

Away from its platforms, Facebook has its eye on people too. The company uses a mixture of cookies, buttons and plugins on third-party websites to track non-users as they move around the web, letting businesses better target adverts at individuals. Deleting Facebook accounts won't stop the firm being a powerful data-gathering entity.

Facebook isn't just a corner of the web that we can easily abandon. For billions of people it is the social fabric that ties us together. But we spend too little time thinking about the other bit of Facebook - that vast web of valuable data gathered on and off its platforms that third parties use to try and influence our decisions. Sometimes those decisions are minor - like deciding what pair of shoes to buy - but increasingly, they are decisions that, cumulatively, have a major impact on people's lives, whether they're Facebook users or not.

If Facebook is here to stay - and despite the murmurings of the #DeleteFacebook movement, it looks like it is - then it's time we started asking more questions about that data. About how it's being used and how Facebook is making sure it's not being stolen or abused by malicious actors. Rather than rushing to delete Facebook, perhaps we should start by really getting a handle on what Facebook is, the good bits and the bad bits, and put pressure on the platform to reform its ways once and for all.

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#DeleteFacebook? You'll probably never escape its colossal reach

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As Facebook's ongoing crisis over the Cambridge Analytica revelations escalates, a chorus of discontented voices, mostly on Twitter, is growing. "#DeleteFacebook," they murmur, while the really virtuous among us say "If I had a Facebook account I'd delete it, but I don't, so I can't!

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- govt and tech companies colluding to influence elections?

- tech companies using privacy regs/data mining/algorithms to determine political outcomes? (effect of big data on politics)

**how surveillance capitalism (aka all capitalisms) inherently produce discrimination, but how that is disguised by "scientific accuracy" that algorithms seem to have but its a lie

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" This new form of information capitalism aims to predict and modify human behavior as a means to produce revenue and market control. "

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In the popular discourse, authoritarianism typically stands as liberal capitalism's dramatic antithesis. And nowhere are their purported differences more stark than in their attitudes toward individual privacy. While in the liberal capitalist world every person's home is said to be their castle, in authoritarian regimes, it is just one more state-monitored cage.

Today, however, privacy is disappearing within the walls of advanced capitalist democracies. And multinational corporations, holding aloft the banner of total transparency, are the ones leading the charge.

In 1999, Scott McNealy, then-CEO of Sun Microsystems, famously declared, "You have zero privacy now anyway. Get over it." Google CEO Eric Schmidt warned that "if you have something that you don't want anyone to know, maybe you shouldn't be doing it in the first place." Mark Zuckerberg, the world's sixth richest man, decided that privacy was no longer a social norm, "and so we just went for it," while Alexander Nix, of the data firm Cambridge Analytica - famously employed by both the Brexit and Trump campaigns - brags that his company "profiled the personality of every single adult in the United States of America."

These days, the rhetoric of private capitalists seems indistinguishable from the rhetoric of state tyrants. Their scripts are all mixed up. Their differences have always been exaggerated, if not imagined, but we could once rely on them to at least speak differently. What's changed?

As an economic system founded on the idea of a private sphere - consisting of private individuals who own private property and make private profit in private markets - capitalism is assumed to protect individual privacy. The sanctity of the private realm allegedly ensures maximum freedom for the individual, as producers and consumers are liberated from unwanted interference from the state and nosy neighbors.

Capitalism's detractors have long decried its tendency to hollow out the commons and push everyone into their private bubbles, but its supporters celebrate this atomization. "Civilization," wrote Ayn Rand in 1943, "is the progress toward a society of privacy. The savage's whole existence is public, ruled by the laws of his tribe. Civilization is the process of setting man free from men." From this perspective, capitalism's emphasis on the private sphere and the resultant privacy made it the world's great civilizer.

As early as the 1970s, however, the bond between capitalism and individual privacy was becoming unstuck. In 1977, the right-wing legal jurist Richard Posner put forward his " economic theory of privacy," eventually publishing it in a paper in, aptly, 1984. There, he argued that individual privacy hindered capitalism by interrupting the free flow of information that markets need to be efficient. Posner concluded that "people should not - on economic grounds in any event - have a right to conceal material facts about themselves."

Posner was writing for Chicago Unbound, the law journal at the University of Chicago, the epicenter of the neoliberal storm that was spreading across the world. Milton Friedman was one of Posner's closest colleagues, and Posner himself is often included under the Chicago School umbrella. Posner's capitalist roots - with their endless exaltation of the private individual - made his arguments against individual privacy all the more surprising. The love affair between privacy and capitalism, long taken for granted by dove-eyed liberals, was revealed to be the shallowest of relationships: a marriage of convenience that was no longer convenient.

In the digital age, this relationship has become all the more fractious. A new form of capitalism has emerged on the Internet, variously referred to as informational capitalism, digital capitalism, or surveillance capitalism. Personal information is the lifeblood of the new economy: companies collect their users' data to sell it to advertisers and generate revenue. The more companies know about individuals, the better they can target their advertisements, boost their "conversion rates," and rake in profits.

And make no mistake, there's a lot of money to be made. In the third quarter of 2016, a total of $17.6 billion was spent on digital advertising, a 20 percent rise from the previous year.

Facebook and Google have become a duopoly in this new context, accounting for about half of the total; of the $2.9 billion in growth over the last year, the pair was responsible for a remarkable 99 percent of it. In the process, they have become the two fastest growing corporations in the history of capitalism, with an ability to collect, monitor, and sell data on users in ways other companies can only imagine. Their collective net worth is $800 billion, more than the total GDP of the Netherlands.

Both their business models show that, in informational capitalism, privacy no longer impedes profit: privacy prevents profit. The belief that individuals should be allowed to control their personal information now contradicts capitalism's profit-making process. Far from sheltering private individuals from external interference, as Ayn Rand imagined, companies now want to know individuals as well as they know themselves. Corporations strive for perfect transparency, so that, in the words of Google's chief economist, Hal Varian, the search engine will "know what you want and tell it to you before you ask the question."

We might take solace in the fact that these companies don't carry the force of the state - that if their intention is to target advertisements more effectively and sell data more profitably, it also might redound to the benefit of the user.

Many people enjoy using a service that knows them well and recognizes their personal habits, preferences, and interests. The quality of their experience increases with the amount of personal information they turn over - and who doesn't want better services?

But dangers do exist. Although much of the data that tech firms collect is frivolous, we should be wary of the aggregation effect: taken individually, each piece seems innocuous; taken together, an intimate picture of our person is revealed.

Yet even this does not get at the heart of the problem. The greatest threat lies not so much in what corporations know as in how they use that knowledge. The services they offer are entrancing, replete with conveniences and new possibilities, tailored to our every need. But when we cede so much personal information to corporations, we grant them incredible power and responsibility. Knowledge may mean power, but information often means domination.

And since the first large-scale data collection efforts in the nineteenth century, companies have been using technology to exert massive social control.

In 1880, with a rising population, an expanding territory, and a deepening desire for statistics - combined with a complete lack of technological strategy - the data collected by the United States Census took most of a decade to process. By the time the next census rolled around, in 1890, the processing time had been reduced to three months.

A young American engineer, Herman Hollerith, invented the system that enabled this incredible speed-up. Inspired by train conductors, he used punch cards to automatically tabulate information on a set of standardized traits, from race and gender to literacy levels and religion, across the entire population. The Hollerith Machine, as it came to be known, is now recognized as the first information system that successfully replaced pen and paper. Countries all over the world used it to collect data on their citizens.

In 1911, Hollerith sold his company and the rights to his machine in a merger, forming what is now known as the International Business Machines Corporation (IBM). Under the leadership of Thomas J. Watson, a man revered as the "world's greatest salesman," IBM would own 90 percent of all tabulating machines in the United States. They sent them wherever the money called.

During the 1930s, it called from Adolf Hitler's Third Reich. Under the direction of IBM's German subsidiary, the Hollerith Machine located Jews and facilitated their " processing." The infamous numbers tattooed on the arms of prisoners were IBM identification numbers, matched to their individual place in IBM's punch-card system. The Nazis rewarded Watson for his services in 1937 with the prestigious Order of the Golden Eagle. Although he returned the award in 1940, his company continued to assist Germany throughout the war.

IBM didn't support the Nazis; it simply didn't care. In the same period, it completed a similar project for the United States: rounding up Japanese Americans - more than one hundred thousand of them - for the internment camps on the East Coast.

IBM's nefarious collaborations during World War II may represent an extreme case, but it would be naïve to dismiss them as immaterial. In fact, the company's actions embody a very banal truth: corporations and states regularly have shared interests and work together for mutual gain.

This happens regardless of moral principles. After all, capitalism coexists just as happily with dictatorships (Chile under Pinochet or today's China) as it does with democracies. The capitalist, guided by the great entrepreneurial spirit, sees every new setting as a new set of opportunities. The only question that remains is who is ready to exploit it.

Edward Snowden's mass leak of NSA files in 2013 revealed the active role corporations play in state surveillance. He reported a complete "blurring of public and private boundaries in surveillance activities" with "collaborations and constructive interdependencies between state security authorities and high tech firms."

Facebook, Google, and other websites had become the government's new CCTV cameras but with one big difference: we had not only normalized ourselves to these new surveillance technologies, we actively enjoyed their company.

Behind a façade of user loyalty, tech companies make billions by promising the public one thing and the government the opposite. As Snowden revealed, Microsoft proclaims that they "believe it's important that you have control over who can and cannot access your personal data in the cloud," while working with the American government to provide easier access to that very same data.

This new incarnation of surveillance synthesizes Orwell's dystopia with Aldous Huxley's Brave New World. In Orwell's creation, an authoritarian surveillance state maintains order; in Huxley's, the self-medication of soma, an antidepressant drug that keeps everyone smiling, does the same work. Today, surveillance is carried out less by a Big Brother as by a set of Best Friends: these services remember our birthdays, answer our questions without casting judgment, and suggest films and books we might like. Far from being based on fear, the new surveillance system is fun, caring, and helpful. When Facebook crashed in some US cities during summer 2014, many Americans called 911.

The tech firms assure us that their products center on us, the customers. But this masks not only their own profit motives but also their perfect harmony of interests with the state. Governments allow corporations to systematically collect individual information - no matter what risks or consequences it may present for consumers - because governments receive access to that data in return. Corporations, for their part, hand data over to governments because they receive favorable legislation in return.

This harmony becomes all the more apparent when one examines the revolving door between the state and tech companies. The Center for Responsive Politics recently found that the five biggest tech firms - Apple, Amazon, Google, Facebook, and Microsoft - spent $49 million on lobbying in 2015 alone, more than double the $20 million the five largest banks spent and roughly $3 million more than the five largest oil companies.

During the Obama years, the tech industry embedded itself in Washington. Almost two hundred people who worked for Barack Obama's administration in 2015 were working for Google by the end of 2016, while fifty-eight moved in the opposite direction. Under Obama, Google executives were reported to meet in the White House more than once a week on average.

While Silicon Valley leans Democratic, they've also found favor in the Trump White House. The Silicon Valley billionaire Peter Thiel now serves as one of Trump's key advisers, and one of Trump's first moves after the election was to hold a tech summit at Trump Tower, inviting leaders to a reception that no other industry received. "I'm here to help you folks do well," he promised.

In the 1990s, the Internet seemed to promise an era of new freedom and expanded global connectivity. When Harvard law professor Lawrence Lessig expressed trepidation in 2000, he was widely dismissed. "Left to itself," he warned, "cyberspace will become a perfect tool of control." Few agreed: "Lessig doesn't offer much proof that a Soviet-style loss of privacy and freedom is on its way," sneered one skeptical reviewer.

Seventeen years have passed, and we now have a surveillance apparatus that exceeds anything past authoritarian states could've mustered.

But we should not reduce the dangers of informational capitalism to government surveillance. These tech companies' underlying philosophy represents a threat to freedom in itself. Silicon Valley ideology has saturated cyberspace and is rebuilding the world in its image, likely surpassing anything Lessig could have foreseen.

Tech CEOs celebrate today as "the most measured age in history," equating gathering information with the Enlightenment ideal of knowledge-discovery. Corporations promise us that so long as they have access to everyone's information, they can right all of society's wrongs. This encapsulates the Big Data mindset: solving human problems only requires collecting enough information. With full faith in this ideology, most informational capitalists agree with Google chief economist Varian: any resistance to the loss of privacy will dissipate because "the advantages, in terms of convenience, safety, and services, will be so great."

But this data-driven understanding of progress constricts the individual. Privacy is meant to be a space of creative experimentation, free from judgment and beyond external control. A world without privacy, by contrast, risks a world of complete conformity. Ideally, the individual's private experimentations challenge prevailing norms and ideologies; this friction, the argument goes, pushes society forward. Under informational capitalism, however, what once demanded respect for privacy - progress - now demands its rejection.

Under big-data capitalism, the privacy of the individual is subsumed within an ideology of profit-linked progress. Where liberalism held that restricting freedom of expression is a "peculiar evil, one that is robbing the human race," informational capitalism updates this: the refusal to share personal information robs the human race. To keep some aspects of yourself private now stands in the way of progress.

That Silicon Valley's concept of progress aligns so perfectly with its own profit interests is striking. Not only does this ideology promote technology as the solution to all problems - and who will supply the technology? - but it also makes profit and progress require the exact same resource: more and more personal information. The harmony between progress and profit is not perfect, however, and the seed of this contradiction reveals Silicon Valley's authoritarian aspect most clearly.

While in terms of "progress" these tech companies present themselves as radical pioneers - they move fast and break things, as the mantra goes - when it comes to profit this "radicalness" masks a conflicting desire for complete conformity. As privacy scholar Julie Cohen notes, informational capitalism ultimately wishes to "produce tractable, predictable citizen-consumers whose preferred modes of self-determination play out along predictable and profit-generating trajectories."

To do so, these tech firms establish a dense web of options - as in Spotify's and Netflix's curated recommendations - tailored to a particular version of an individual's identity, "designed to promote consumptive and profit-maximising choices that will systematically disfavour innovations designed to promote other values." As Google's former design ethicist Tristan Harris puts it, "if you control the menu, you control the choices" - and if you control the choices, you control the actions.

Capitalism has always tried to align society's ambitions with its own. With the Internet, its reach becomes almost inescapable. Few, if any, opposing forces still exist. Of the fifteen most visited websites in the world, only one, Wikipedia, does not operate under Silicon Valley's logic. Coupled with the increasing importance of the Internet as a site for human development, its pervasive influence cannot be healthy for a diverse, democratic society. This dynamic only intensifies when two companies, Google and Facebook, virtually control the market.

As a place of self-formation, public discussion, and social organization, the Internet frames our thinking, our knowledge, and our behavior. Today, it is constructed almost exclusively in favor of maximizing profit.

In a mockery of its initial utopian promise, the Internet has become not only a tool of mass surveillance, but also an advanced advertising technology and a means of social control.

If we want to challenge this state of affairs, we should begin by having more meaningful conversations about the Internet we want. It matters too much to remain the sole preserve of corporations.

Data, if it must be collected, should be democratized, not filtered through secret algorithms for private gain. Until informational capitalism's tyrannical control of the Internet is broken, the dangers will only deepen. As with all tyrannies, citizens' lives will become more and more transparent, while the activities of the powerful become ever more opaque.

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In the popular discourse, authoritarianism typically stands as liberal capitalism's dramatic antithesis. And nowhere are their purported differences more stark than in their attitudes toward individual privacy. While in the liberal capitalist world every person's home is said to be their castle, in authoritarian regimes, it is just one more state-monitored cage.

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"Silicon Valley is populated by cutthroat capitalists working to remake society in their own image — what could be more Trump?"
Consider how: much of silicon valley/tech companies are based on capitalism, and what extend they'd go to to promote/cement those values in society? i.e. voting for/supporting trump (or other capitalists w political power)

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Last Wednesday, Donald Trump took a break from tweeting to meet with top executives from Apple, Facebook, Google, Amazon, Microsoft, IBM, and others. Of course, Ivanka, Eric, and Donald Jr joined him at the table. Vampire-curious venture capitalist Peter Thiel organized the summit to help build a bridge between the Trump administration and Silicon Valley, which almost unanimously supported Hillary Clinton.

This meeting was intended as an ice-breaker, the first step toward what both sides are surely hoping will be a mutually beneficial partnership. At the summit, they could feel each other out, share their interests, and explore compatibility. After all, every relationship is a negotiation: How can tax codes be reformed? What trade deals are desired? Who will conduct mass surveillance?

Many of the CEOs who attended had skirmishes with Trump during the campaign. Elon Musk (Tesla) said Trump doesn't "have the sort of character that reflects well on the United States," while Travis Kalanick (Uber) threatened "to move to China if [Trump] wins." But proximity to power has a funny way of changing a person's mind. Hours before the meeting, they both agreed to advise Trump as part of his Strategic and Policy Forum, a group that also includes Jamie Dimon (JP Morgan) and Stephen Schwarzman (Blackstone).

Before the meeting, the tech press largely focused on shaming these executives for entering the Tower of Evil. Pictures of the summit seemed to evoke sympathy for these idealistic innovators, as if Trump had somehow lured them into a trap. The poor souls could only count the seconds until the boardroom doors unlocked, freeing them from the rantings of a madman.

Of course, the reality is much more banal and consequential: billionaires met to express their interests and discuss policy. The meeting was a genial gathering, not a battle between the flaxen-haired fascist and libertarian elite. As Wilbur Ross, billionaire investor and pick for commerce secretary, said afterward, "Both the tech guys and the administration got to know each other a lot better." Indeed, the summit might meet as often as quarterly, according to the Trump transition team.

The executives didn't have to set aside their politics to talk business - their politics align with the new administration. People like Elon Musk and Jeff Bezos might present themselves as bold visionaries, but they have more in common with Trump than their hagiographers would ever admit. Silicon Valley is populated by cutthroat capitalists working to remake society in their own image - what could be more Trump?

Consider IBM, a company with a sordid history of helping governments oppress. During World War II, it played both sides, providing data management for Jewish concentration camps in Germany and Japanese internment camps in America. IBM still helps states track, categorize, and analyze data about entire populations. Earlier this year, it worked with European countries to create an analytic engine that could separate the refugees from the terrorists.

IBM CEO Ginni Rometty - who became Trump's adviser after writing an open letter offering him support and ideas - adamantly believes that we should "embrace predictive analytics" and other data-driven technologies for two reasons: "First, we can," and, second, "because we must. "

Rometty conflates the normative (we must) with the descriptive (we can), expressing a distressingly common position held by technocrats and authoritarians. Under this logic, all actions become self-justifying. As soon as something becomes possible, it also becomes necessary.

IBM says it wants to create a "Smarter Planet." Smarter for whom? For what reason? Do we really want the ghouls from the tech summit to make those choices?

It's not entirely fair to single out IBM; every corporation that sent a representative to the summit participates in surveillance capitalism. At the time of publication, of the nine tech giants asked if they would help build a Muslim registry, only Twitter said it would not. The rest gave no comment.* Maybe this explains why the CEO of Trump's favorite megaphone wasn't invited to the meeting.

In large part, working with Trump will continue business as usual. IBM may have a historical leg up, but it's not hard to imagine other tech companies - willfully or inadvertently - building a database of Muslims, immigrants, or whoever else Trump rails against. Not out of malevolence, but because they were built to make money, not make the world a better place.

In the days after the summit, some attendees finally put out statements saying they will not help build a registry, but this is little comfort when the registry question has already been answered in practice: Facebook and Google already create, organize, and mine personal profiles. Data-brokers already collect and sell access to microdemographic information. Startups, like the unironically named Ethnic Technologies, already claim to accurately divine "individuals' ethnic origins based on their full names, addresses and ZIP codes." In general, Silicon Valley provides an arsenal of products that assist in targeted surveillance, social control, and violence against marginalized and vulnerable groups. These databases exist already; tech companies are now simply making them more efficient and effective.

We can laud the good intentions of individual engineers who pledge to never work on a Muslim registry. But how do their intentions relate to the interests of the powerful corporations they work for? Moreover, the pledge's value means little when those engineers spend their days creating the exact technologies needed for such a database. The primary use may not be wicked, but the devil is in the secondary use.

In a 2013 keynote, Rometty said, "The smarter enterprise . . . will force economic growth and it will force societal progress." As Trump surrounds himself with executives and generals - merging corporate and government power - he's reconfiguring the state as an enterprise. The CEOs who are joining the administration have made billions by rebranding exploitation and oppression as growth and progress, and now they have a partner in Washington who agrees with them.

Update: Since publication, Facebook, Apple, Microsoft, and Google have all stated on the record that they would not help the Trump administration build a national Muslim registry.

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Last Wednesday, Donald Trump took a break from tweeting to meet with top executives from Apple, Facebook, Google, Amazon, Microsoft, IBM, and others. Of course, Ivanka, Eric, and Donald Jr joined him at the table. Vampire-curious venture capitalist Peter Thiel organized the summit to help build a bridge between the Trump administration and Silicon Valley, which almost unanimously supported Hillary Clinton.

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this is so odd lol

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Waterfowl is the new alt on Twitter

In late 2015, David, a Newcastle father of two in his mid-40s who works in the construction industry, decided to get a Twitter account. David wasn't really a social media person - he has a Facebook account he rarely uses other than to "look at pictures of family [events] and my nephews." For the most part, he only uses his desktop computer to manage his finances and watch the odd TV show on the BBC. He'd heard of Twitter before - in newspapers, usually involving a politician saying something stupid or a celebrity accidentally posting a nude. His friends at work also used it to keep up-to-date with the Premier League and their corresponding fantasy soccer leagues.

It was the election of Jeremy Corbyn as leader of the U.K.'s Labour Party - the most left-leaning leader in the country's modern history - in September 2015, that finally did it. David describes himself as a "centrist" who voted for Tony Blair and Gordon Brown before switching to the Conservative Party in 2010. He has a "soft spot" for Labour, but was nervous and worried about Corbyn's victory. "He's a bloody traitor!" he writes over Instant Messenger. "The man is a lunatic, and he hates this country. He'll let anyone in, ban everyone he dislikes - proper communism. How anyone of your generation can support him is beyond all reasonable thinking."

David needed an outlet to vent his frustrations. In his office and at the pub, he couldn't talk about his political fears without being told to shut up by his co-workers and friends. And so, he felt he had no choice but to turn to Twitter.

David originally set up an account with his real name - David is a pseudonym to protect his anonymity - and a low-res image of himself on a beach vacation wearing sunglasses, the same picture he still uses on his Facebook account. But it didn't take long for David to get into fights online. For the most part, he started them, too - mainly by agitating verified left-wing commentators and personalities with right-wing memes, usually either pro-Trump or pro-Brexit. "Things that would get them angry," David recalls. Eventually, his aggressive posts got him later suspended from Twitter.

Unable to be himself, he instead decided to set up an anonymous account based on his favorite animal: A duck.

"My first anonymous account was called @Angryoldduck, which I set up in November 2017. It was really based on the fact that a lot of my childhood memories are about feeding ducks. It reminded me of British culture and identity. Also, ducks are cute so I thought I'd come across as less aggressive and maybe more people would engage with me."

"Alts" - or alternative Twitter accounts - are nothing new. For the most part, they're a way to remain anonymous online, but still participate in fandom or niche subculture. (In some cases, right-wing trolls also use anonymous accounts fronted by anime avatars or Pepe the Frog pictures as a signifier of their political positions on 4chan and Reddit message boards.) But this was the first time I'd ever seen anyone tweet as waterfowl.

"Middle-aged people are more likely to be cautious about what they want to put online, and if you're going to make provocative political opinions or basically say some fucked-up shit, you're probably going to be anonymous," says Katie Notopoulos, a senior technology editor at BuzzFeed News and a co-host of the Internet Explorer podcast.

When I ask Katie why David might have chosen a duck as his alt, she suggests it could just be a form of humor similar to other alt accounts that make up "weird twitter" sub-communities. "It's almost like the early weird Twitter guys, how they all had stupid user handles like @fart, @dogboner and @weehitler. When they got into fights with some political commentator, they could always laugh like, 'HAHA, YOU'RE TWEETING AT A GUY NAMED DOGBONER.'"

"In the same way," she continues, "it's sort of ridiculous to see someone have a heated political argument with a duck - it's like fireproofing yourself from getting owned."

To complicate things, a few weeks into using his new account, David found out - amazingly - that he wasn't the only right-wing leaning duck on Twitter. In fact, he found more than 10 accounts, just based in Britain alone, with names like "Mr_Duck_Esquire," "Ugly Bloody Duck" and "That Bloody Duck." Not to mention, the "Racist Duck," a name that, according to its user, is purely ironic, even if that irony is lost on most.

The ducks posted similar content to David, too: Anti-Corbyn and pro-Brexit articles, videos from right-wing YouTubers and the odd image of a duck from the Duck of the Day Twitter account (all cute duck photos, no politics). "I was curious and wanted to find out more," David says. "So when I first made contact with another duck account, I said hello, and the response I received was just a 'quack.'"

The same thing happens to me when I try to interact with other duck accounts to figure out why this group of middle-aged men gravitate toward the duck as an alt. Some respond to me simply with "quacks," or they warn other duck accounts not to send me "duck pics."

John (again, a pseudonym) was one of the few duck accounts to get back to me to explain the phenomena in more detail. "Part of assuming the duck identity is for anonymity," he says of his three duck accounts (including Mr_Duck_Esquire). "But there's also something libertarian about the duck. A duck sets off in flight. If another duck thinks it's a good idea, it joins, too. Otherwise the first duck just carries on. The same with ideas. I don't care if everyone agrees or not. If they like my ideas, they will embrace it. If they don't, they'll fly off."

I ask John whether part of those "libertarian" values include online harassment, which is often Islamophobic, misogynistic and directly targeting vulnerable groups on Twitter. For instance, in most cases, these attacks targeted trans women with slurs and insulting comments about their appearance. John responds by vowing that he's never personally targeted any individuals and that his comments are mostly about politics and "just out of humor." He admits, though, that he wouldn't make the same remarks using a personal account, or if he met any of the commentators he tweets at in real life.

At the same time, John says that in private, the duck account has helped him talk about issues that are still personal to him, mainly around mental health. "The semi-anonymity allows easier expression to tackle issues that can be quite raw," he says, recalling his battles with self-harm and suicidal thoughts and tendencies. "Talking about my mental health from a persona is helpful because I feel I can talk more. Even during the hard parts, the image of the cute duck will always take the malice out of it."

For other duck accounts, however, assuming the identity is just a way of having conversations online. Steve (also a pseudonym), a 45-year-old father living near Bristol, tweeting under the account @racistduck, tells me that many guys gravitated to ducks simply because of their "silliness." "Who doesn't like ducks? They get fed in parks, waddle and stick their butts in the air," he explains.

At the same time, Steve adds that assuming these identities partially came out of the "assumptions people make when you're a man on Twitter - they assume you'll be aggressive. It tends to be alpha males who are the duck accounts, and it tones down the perceived aggressiveness with a cute duck picture. You can cool down heated debates, on things like immigration and Brexit with humor. This account allows me to do that."

Steve has had several duck accounts that have been suspended and shut down. In fact, his current account is his fourth duck reincarnation. He knows some of his posts can be provocative, which he says is a deliberate effort to maximize his support for "free speech" than it is for any deeply held political or social convictions. But, like David, his continual return to Twitter is for the space to have political conversations he wouldn't be able to have anywhere else. "As a duck," he explains, "people are more reasonable and don't assume my agenda. On this account, it's difficult for people to make judgements about me before we start."

David doesn't post much on Twitter these days. He feels the platform has become too confrontational, even for him. He now spends his time on his duck account lurking, reading more conversations and occasionally speaking to other ducks via DM, where they're more likely to share cute images of ducks, and talk about the minutiae of their lives than right-wing politics. "If we do talk politics," he says, "it'll usually be in the way that we'd imagine ducks would think about our political situation. I think they'd find it bizarre and quite stupid - and probably be thankful they're not humans!"

Hussein Kesvani is MEL 's U.K./Europe editor. He last wrote about the man who coined the term "metrosexual."

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The Conservative Men Who Pretend to be Ducks Online

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In late 2015, David, a Newcastle father of two in his mid-40s who works in the construction industry, decided to get a Twitter account. David wasn't really a social media person - he has a Facebook account he rarely uses other than to "look at pictures of family [events] and my nephews."

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a fun example of FB manipulating what we see FOR THEIR OWN RESEARCH, WITHOUT ANY CONSENT FROM PARTICIPANTS

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Facebook sorry - almost - for secret psychological experiment on users

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Project to influence emotions should have been 'done differently' and company was 'unprepared' for strength of negative reaction

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until 2014 FB was ALLOWED to mine our data and give it to third-party companies so we're willingly handing over all of our personal info! outside of politics, how are advertising/pharma/other companies using our data, which they are now? for trump, we can say "this was used to sway the election" but the argument that ads make us more likely to buy x which may be bad for us CAN BE TWISTED as a "correlation not causation" WHICH WOULD DISCREDIT HOW TERRIBLE IT ALL IS BUT IT IS

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Cambridge Analytica hijacked our online data to help elect Donald Trump. It's an outrage - but it's nothing new.

The Western world has been rocked by news that Cambridge Analytica - the data analytics firm formerly run by Steve Bannon and bankrolled by Trump-funding billionaire Robert Mercer - unethically harvested the data of 50 million Facebook users to target them with ads meant to benefit the Trump campaign. The news prompted declarations of a [...]

The Western world has been rocked by news that Cambridge Analytica - the data analytics firm formerly run by Steve Bannon and bankrolled by Trump-funding billionaire Robert Mercer - unethically harvested the data of 50 million Facebook users to target them with ads meant to benefit the Trump campaign. The news prompted declarations of a [...]

The Western world has been rocked by news that Cambridge Analytica - the data analytics firm formerly run by Steve Bannon and bankrolled by Trump-funding billionaire Robert Mercer - unethically harvested the data of 50 million Facebook users to target them with ads meant to benefit the Trump campaign. The news prompted declarations of a [...]

The Western world has been rocked by news that Cambridge Analytica - the data analytics firm formerly run by Steve Bannon and bankrolled by Trump-funding billionaire Robert Mercer - unethically harvested the data of 50 million Facebook users to target them with ads meant to benefit the Trump campaign. The news prompted declarations of a "data breach," in which users' " stolen data" was "hijacked" by the firm, which was " misusing" personal data for nefarious ends. "We 'broke' Facebook," the whistle-blower involved said, prompting a reporter to ask if that meant the platform had been "hacked."

The Cambridge Analytica story is outrageous, for a variety of reasons. But while we're fuming at this violation, we should extend that anger to the way our online behavior is routinely documented, collected, and used for commercial purposes, and channel it into efforts to at last properly regulate the companies we've simply trusted to be responsible caretakers of what has become one of the most intimate aspects of our daily lives.

To be sure, there are elements unique to the Cambridge Analytica case that raise specific legal and ethical concerns. For one, the company acted in a grossly unethical way by lying to users to access their data, with the help of an app that told users the firm was conducting academic research, rather than doing work for a political campaign. Then there are the potential legal violations: the United States bars the employment of foreigners in political campaigns.

But the distinction between the company's actions and business as usual is really one of degree, rather than a difference in kind.

What Cambridge Analytica did was not actually a "data breach." The data harvesting took place in 2014, when Facebook's terms of service and API allowed third-party apps to collect data on a users' friends, a feature exploited by many thousands of other apps and which the company didn't ban until a year later. As Lorenzo Franceschi-Bicchierai wrote at VICE Motherboard, this means something much worse than a breach: it means this outrageous violation of users' privacy was, until recently, just the way things worked.

But even if Facebook no longer allows companies to collect and use your data just because one of your "friends" happened to get the urge to play a farming simulator, that doesn't mean your data is now safe. In reality, Facebook - and just about every tech company that exists - is continually violating our privacy for the purpose of manipulating us, albeit for commercial purposes.

As we (hopefully) should all know by now, the unimaginably large volume of data Facebook collects about our activities while using its platform - as well as when we're not - is handed over to advertisers, who use it to better target us with ads to sell their products. The breadth of this tracking is staggering, encompassing even the locations you visit and stores you shop in (if you have its mobile app installed), and can detect things as minute as whether you sign up to loyalty programs, add items to shopping carts online, and much more.

But companies can also gain direct access to users' data through Facebook Connect, a single sign-on feature that lets users employ their Facebook profiles on other websites, to post comments, for example. Companies have used this feature to create profiles of users, which document everything from their lifestyles and life stages, to what kind of household they live in and their personalities - identical to the kinds of psychological profiles Cambridge Analytica put together for its own purposes.

The same concerns around ethics and consent raised by the Cambridge Analytica case also surround Facebook's own data collection. Sure, Facebook allows you to turn off some of these features, such as location tracking. But how many Facebook users are actually aware they can do this? How many are even aware they're being tracked in the first place, or how thoroughly Facebook is collecting information about their lives?

And then there are the countless types of data collection that users can't turn off because they come with the Facebook experience. Your choice is either to accept that your activities will be collected and exploited, or leave Facebook. This is hardly an adequate definition of consent.

And the trouble is, it's not just Facebook. This is the case with all tech companies, including Google, Apple, and Microsoft, which do the same kind of invasive data mining - particularly Google, which stores all of our searches, and collates it with the data it gathers through its browser, its email service, and services like Google Docs to build ever more detailed portraits of us. We're not even safe on our browsers, with websites that we visit attaching countless trackers that monitor our browsing behavior, data used by online advertising companies (Facebook, Google, and Twitter are leaders in this type of tracking too). Then there are the consumer data companies that hoover up, analyze, and sell the information we make public on sites like Facebook, Twitter, and LinkedIn.

Some of this is leveraged for political ends. One company created websites and used ads connected to Google search terms to spread inflammatory messages during last year's Kenyan elections, most likely targeting them from data collected through such platforms.

The Cambridge Analytica example isn't even the first time data has been leveraged in US politics. As numerous outlets have now reported, it was the Obama campaign that pioneered the use of such data mining - including efforts to match the viewing habits of millions of cable subscribers to its own list of voters and poll responses - in elections. Carol Davidsen, the 2012 campaign's director of integration of media analytics, boasted that they "were able to ingest the entire social network ... of the US," exploiting the same lax privacy rules that Cambridge Analytica took advantage of in 2014. The only difference was that the users who gave the Obama campaign permission to use their data weren't told it was for academic research.

But should we really limit our outrage to when our data is used for political ends? If we object to the idea of our intimate information being tracked and collected in order to manipulate our behavior, surely the ultimate purpose for which we're being manipulated is a secondary issue.

If so, then the use of our data by the vast majority of tech companies for the purpose of selling us products is just as outrageous. Facebook's "success stories" page touts examples from, among others, pharmaceuticals and financial services. Given their checkered histories, how comfortable are we with, say, drug producers, payday-lending companies, and even major banks using intimate psychological profiles of these platforms' users to target them with products?

And the implications of such data collection don't stop there. Right now, the responsible use of our data is entirely reliant on the ethical scruples of companies like Facebook, Google, and others, which doesn't exactly inspire confidence. And if you truly believe that Cambridge Analytica was able, to borrow a popular phrase, to "hack" the 2016 election and install Trump in the White House, then it's hard to overstate the danger of letting even more massive stores of data build up in the hands of companies like Google and Facebook - or anyone in the future who manages to carry out an actual data breach of their systems.

Scandals like this one - or Facebook's notorious secret psychological experiment on its own users - will keep happening as long as the tech industry's collection and handling of our data is left unregulated. But if the idea of privacy and freedom from corporate and state surveillance means anything, then it means being able to use the internet and platforms like Facebook without fear of having one's activities constantly surveilled, documented, and turned into someone else's property- and, eventually, commodified.

For decades now, tech companies and others working in the murky world of online data harvesting have been given a free ride, allowed to track our online behavior and use the resulting data as they see fit with few rules or restrictions. The anger over the Cambridge Analytica case is encouraging, but it shouldn't stop there. It's time to demand a radical change in how we treat companies like Facebook and Google.

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Cambridge Analytica hijacked our online data to help elect Donald Trump. It's an outrage - but it's nothing new. The Western world has been rocked by news that Cambridge Analytica - the data analytics firm formerly run by Steve Bannon and bankrolled by Trump-funding billionaire Robert Mercer - unethically harvested the data of 50 million Facebook users to target them with ads meant to benefit the Trump campaign.

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Google is making its grandest overture to the news business yet. Alphabet Inc.'s search giant is providing a new suite of tools to help media publishers grow subscriptions, advertising sales and readership - an attempt to resuscitate an industry it helped decimate. And it includes another shot at stamping out fake news.

Under the Google News Initiative, the company pledges to dole out $300-million to support digital journalism globally over the next three years.

"We understand it's a difficult situation for publishers, driven by the technology changes. They're very fundamental; they are disruptive," Philipp Schindler, Google's Chief Business Officer, said in an interview. "But we're really all in."

The new services, announced on Tuesday in New York, touch nearly every aspect of Google's business and are mainly about keeping publishers on Google's cornerstone property: the web. Subscribe with Google, a new feature, gives publishers data and tools to find, retain and charge subscribers. Google takes a cut, and each publisher using that is also less likely to move deeper into mobile apps, where it has less reach. Boosting the audience for premium publishers also helps Google, which powers most of the banner and video ads online.

"The last thing you want as a search engine is to see the open internet become a race to the bottom," Schindler said. "The economics here are pretty clear: If our partners don't grow, we don't grow."

Google's latest initiative coincides with a backlash against the internet giants that are increasingly becoming global gatekeepers of information. Amid criticism for spreading fake news, Facebook Inc. recently cut news organizations from its powerful newsfeed. Traffic tanked for several publishers, many of whom were already dealing with thinning advertising streams. Several have cited Google's mobile publishing product as superior to Facebook's alternative.

While the search giant itself was once labeled a scourge of the media world, some publishing executives today note a clear departure. "Maybe four years ago, I thought they were trying to hurt the industry," Conde Nast Inc. president Bob Sauerberg said of Google.

Now the glossy magazine overseer sees an eager partner. He talks regularly with Schindler and others at Google. In return, Sauerberg said Conde is spending more with Google's ad tools and creating content for YouTube. "We're meeting with their engineers," Sauerberg added. "We never met with their engineers. And their engineers run the company."

Leaders at Google attribute the shift to new leadership. Schindler and Chief Executive Officer Sundar Pichai, who both assumed their roles in late 2015, ushered in a more conciliatory relationship with publishers, said Don Harrison, a longtime executive who oversees partnerships. And he framed Pichai's concern with the state of journalism as a political one.

"He is deeply worried that if those institutions aren't functioning, it has a huge negative impact on democratic societies," Harrison said.

It may help that Schindler, a German-born exec, speaks fluently with some of Google's most consistent critics. Outspoken publishers from News Corp. to Germany's Axel Springer have bitterly complained that Google profits from their journalism. This fall, Google made the unusual move to remove the "first-click free" rule in search that buried paywalled websites. On Tuesday, the company said it will more prominently feature publications people subscribe to in search results, as Bloomberg News reported this month.

Additionally, Google said its search answers will now favor more authoritative outlets for news related queries. So will YouTube, which has been scorched lately for surfacing conspiracy theories. Google is teaming with Harvard University to launch a "Disinformation Lab" to spot fake articles ahead of the mid-term elections.

The tech industry's inability to suppress misinformation has sparked a renewed wave of criticism from publishers. Google set up a similar 150 million-euro ($185-million) fund to support the industry in 2016 in Europe, where it is facing antitrust charges. Rupert Murdoch, News Corp's executive chairman, recently called on Facebook to pay a "carriage fee" for news. Other publishers may be exploring the same option for Google. "'We're not talking about it at the moment, but we like the concept," Sauerberg said.

Google isn't disclosing revenue-sharing terms for its subscription service, but Schindler said publishers get the lion's share. He wouldn't comment directly on Murdoch's proposal. "If publishers are coming in with interesting new concepts, of course we're open to it," he said.

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Google pledges $300-million to aid publishers and fight fake news

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Google is making its grandest overture to the news business yet. Alphabet Inc.'s search giant is providing a new suite of tools to help media publishers grow subscriptions, advertising sales and readership - an attempt to resuscitate an industry it helped decimate. And it includes another shot at stamping out fake news.

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labour spending more than the tories on snapchat!! which makes sense, because snapchat is associated with the YOUTH and the tories need not even bother

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What? The @LibDems appear to have spent almost £3,000 on a Disney cruise at the general election...

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What? The @LibDems appear to have spent almost £3,000 on a Disney cruise at the general election... https://t.co/bBgWPLrH94

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Labour has singled out @AmazonUK in its multinational tax avoidance crackdown, but it spent the most on the firm at the general election - £24k https://t.co/8gVghpNSqe

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What? The @LibDems appear to have spent almost £3,000 on a Disney cruise at the general election... pic.twitter.com/bBgWPLrH94
— Emilio Casalicchio (@e_casalicchio) March 19, 2018

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What? The @LibDems appear to have spent almost £3,000 on a Disney cruise at the general election... https://t.co/bBgWPLrH94

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Labour has singled out @AmazonUK in its multinational tax avoidance crackdown, but it spent the most on the firm at the general election - £24k https://t.co/8gVghpNSqe

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What? The @LibDems appear to have spent almost £3,000 on a Disney cruise at the general election... https://t.co/bBgWPLrH94

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What? The @LibDems appear to have spent almost £3,000 on a Disney cruise at the general election...

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Labour has singled out @AmazonUK in its multinational tax avoidance crackdown, but it spent the most on the firm at the general election - £24k https://t.co/8gVghpNSqe

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who is responsible? uber? the engineers? the woman who died? how does this situation get tried in court - or is it just chalked up to an "error"?

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An autonomous Uber car killed a woman in the street in Arizona, police said, in what appears to be the first reported fatal crash involving a self-driving vehicle and a pedestrian in the US.

Tempe police said the self-driving car was in autonomous mode at the time of the crash and that the vehicle hit a woman, who was walking outside of the crosswalk and later died at a hospital. There was a vehicle operator inside the car at the time of the crash.

Uber said in a statement on Twitter: "Our hearts go out to the victim's family. We are fully cooperating with local authorities in their investigation of this incident." A spokesman declined to comment further on the crash.
Who's driving? Autonomous cars may be entering the most dangerous phase
The company said it was pausing its self-driving car operations in Phoenix, Pittsburgh, San Francisco and Toronto. Dara Khosrowshahi, Uber's CEO, tweeted: "Some incredibly sad news out of Arizona. We're thinking of the victim's family as we work with local law enforcement to understand what happened."

Uber has been testing its self-driving cars in numerous states and temporarily suspended its vehicles in Arizona last year after a crash involving one of its vehicles, a Volvo SUV. When the company first began testing its self-driving cars in California in 2016, the vehicles were caught running red lights, leading to a high-profile dispute between state regulators and the San Francisco-based corporation.

Police identified the victim as 49-year-old Elaine Herzberg and said she was walking outside of the crosswalk with a bicycle when she was hit at around 10pm on Sunday. Images from the scene showed a damaged bike. The 2017 Volvo SUV was traveling at roughly 40 miles an hour, and it did not appear that the car slowed down as it approached the woman, said Tempe sergeant Ronald Elcock.

Elcock said he had watched footage of the collision, which has not been released to the public. Police identified the operator of the car as Rafaela Vasquez, 44, and said she was cooperative and there were no signs of impairment.

The self-driving technology is supposed to detect pedestrians, cyclists and others and prevent crashes.

John M Simpson, privacy and technology project director with Consumer Watchdog, said the collision highlighted the need for tighter regulations of the nascent technology.

"The robot cars cannot accurately predict human behavior, and the real problem comes in the interaction between humans and the robot vehicles," said Simpson, whose advocacy group called for a national moratorium on autonomous car testing in the wake of the deadly collision.

Simpson said he was unaware of any previous fatal crashes involving an autonomous vehicle and a pedestrian.

Tesla Motors was the first to disclose a death involving a self-driving car in 2016 when the sensors of a Model S driving in autopilot mode failed to detect a large white 18-wheel truck and trailer crossing the highway. The car drove full speed under the trailer, causing the collision that killed the 40-year-old behind the wheel in the Tesla.

Earlier this year, California regulators approved the testing of self-driving cars on public roads without human drivers monitoring inside.

"The technology is not ready for it yet, and this just sadly proves it," said Simpson.

In one recent incident, California police officers found a Tesla that was stopped in the middle of a five-lane highway and found a driver asleep behind the wheel. The man said the vehicle was in "autopilot", which is Tesla's semi-autonomous driver assist system, and he was arrested on suspicion of drunk driving.

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An Uber self-driving car travels in Pittsburgh, Pennsylvania. Photograph: Angelo Merendino/AFP/Getty Images

In another recent case, a Tesla car rear-ended a fire truck on a freeway, with the driver again telling the authorities the car was in autopilot mode at the time of the collision.

Michael G Bennett, an Arizona State University associate research professor who studies autonomous cars, said the self-driving vehicles have become ubiquitous around campus and on the streets in Tempe. Often they have operators behind the wheels, but sometimes they are fully autonomous with no human inside.

The fatal collision could spark significant calls for reform and reflections within the industry, he said.

"It may be problematic for the industry, because one of their central arguments for the value of the technology is that it is superior to human drivers," said Bennett, adding that autonomous cars should be able to detect pedestrians and avoid hitting them, even if they aren't in crosswalks: "Every day, pedestrians in cities around the world step outside of the crosswalk."

Rage against the machine: self-driving cars attacked by angry Californians

The governor of Arizona, Doug Ducey, has been a strong proponent of allowing corporations to test the technology in his state, publicly slamming other governments for "over regulation" and in 2016 urging Uber to "ditch California" and launch in his region. In March, he issued new rules and said that more than 600 automated vehicles have driven on public roads in the state.

"Our prayers are with the victim, and our hearts go out to her family," Patrick Ptak, Ducey's spokesman, said in an email to the Guardian, adding, "Public safety is our top priority."

Linda Bailey, the executive director of the National Association of City Transportation Officials (Nacto), said in an interview that there has not been enough regulatory oversight of testing and that some governments are overwhelmed trying to understand autonomous technology and its limitations.

"There's an essential role for the public sector in regulating the safety of these vehicles, which has been largely left to private companies," she said, adding that Nacto supports third-party testing of the vehicles.

Tempe's mayor, Mark Mitchell, defended the city's ongoing support of autonomous vehicles in a statement Monday, saying: "All indications we had in the past show that traffic laws are being obeyed by the companies testing here."

This article was amended on 22 March to correct the name of the Uber safety driver, who police had initially misidentified.

Topics

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Self-driving Uber kills Arizona woman in first fatal crash involving pedestrian

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An autonomous Uber car killed a woman in the street in Arizona, police said, in what appears to be the first reported fatal crash involving a self-driving vehicle and a pedestrian in the US.

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AHHHHHHHH

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The company at the centre of the Facebook data breach boasted of using honey traps, fake news campaigns and operations with ex-spies to swing election campaigns around the world, a new investigation reveals.

Executives from Cambridge Analytica spoke to undercover reporters from Channel 4 News about the dark arts used by the company to help clients, which included entrapping rival candidates in fake bribery stings and hiring prostitutes to seduce them.

In one exchange, the company chief executive, Alexander Nix, is recorded telling reporters: "It sounds a dreadful thing to say, but these are things that don't necessarily need to be true as long as they're believed."

The Channel 4 News investigation, broadcast on Monday, comes two days after the Observer reported Cambridge Analytica had unauthorised access to tens of millions of Facebook profiles in one of the social media company's biggest data breaches.

Profile
Alexander Nix, CEO of Cambridge Analytica
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Name

Alexander James Ashburner Nix

Age

42

Education

Eton, then Manchester University, where he studied history of art

Career

Nix worked as a financial analyst in Mexico and the UK before joining SCL, a strategic communications firm, in 2003. From 2007 he took over the company's elections division, and claims to have worked on more than 40 campaigns globally. Many of SCL's projects are secret, so that may be a low estimate. He set up Cambridge Analytica to work in America, with investment from US hedge fund billionaire Robert Mercer. He has been both hailed as a visionary - featuring on Wired's list of "25 Geniuses who are creating the future of business" - and derided as a snake oil salesman.

Controversies

Cambridge Analytica has come under scrutiny for its role in elections on both sides of the Atlantic, working on Brexit and Donald Trump's election team. It is a key subject in two inquiries in the UK - by the Electoral Commission, into the firm's possible role in the EU referendum, and the Information Commissioner's Office, into data analytics for political purposes - and one in the US, as part of special counsel Robert Mueller's probe into Trump-Russia collusion. The Observer revealed this week that the company had harvested millions of Facebook profiles of US voters, in one of the tech giant's biggest ever data breaches, and used them to build a powerful software program to predict and influence choices at the ballot box. Emma Graham-Harrison

Photograph: The Washington Post

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The company, and Nix, are under pressure from politicians in the US and the UK to explain how it handled the data and what role the information played in its campaigns, if any.

The Information Commissioner Elizabeth Denham criticised Cambridge Analytica for being "unco-operative" with her investigation as she confirmed that her watchdog would apply for a warrant to help her examine the firm's activities.

Cambridge Analytica has sold itself as the ultimate hi-tech consultant, winning votes by using data to pinpoint target groups and design messages that will appeal powerfully to their interests, although it denies using Facebook information in its work.

But in the undercover investigation by Channel 4 News, in association with the Observer, executives claimed to offer a much darker range of services.

In a series of meetings with a reporter posing as a representative of a wealthy Sri Lankan family seeking political influence, Cambridge Analytica executives initially denied the company was in the business of using entrapment techniques.

But Nix later detailed the dirty tricks the company would be prepared to pull behind the scenes to help its clients.

When the reporter asked if Cambridge Analytica could offer investigations into the damaging secrets of rivals, Nix said it worked with former spies from Britain and Israel to look for political dirt. He also volunteered that his team were ready to go further than an investigation.

"Oh, we do a lot more than that," he said over dinner at an exclusive hotel in London. "Deep digging is interesting, but you know equally effective can be just to go and speak to the incumbents and to offer them a deal that's too good to be true and make sure that that's video recorded.

"You know these sort of tactics are very effective, instantly having video evidence of corruption."

Nix suggested one possible scenario, in which the managing director of Cambridge Analytica's political division, Mark Turnbull, would pose as a wealthy developer looking to exchange campaign finance for land. "I'm a master of disguise," Turnbull said.

Another option, Nix suggested, would be to create a sex scandal. "Send some girls around to the candidate's house, we have lots of history of things," he told the reporter. "We could bring some Ukrainians in on holiday with us, you know what I'm saying."

He said these were hypothetical scenarios, but suggested his ideas were based on precedent. "Please don't pay too much attention to what I'm saying, because I'm just giving you examples of what can be done, what has been done."

Any work may have stayed out of the spotlight partly because Cambridge Analytica works hard to cover traces of its operations, Nix said, using a shifting network of names and front groups.

"We're used to operating through different vehicles, in the shadows, and I look forward to building a very long-term and secretive relationship with you," Nix told the source in a first phone call.

Cambridge Analytica sometimes contracts under a different name, so that there are no records of its involvement, Turnbull said. That does not only protect the company, but also makes its work more efficient, he is recorded saying.

"It has to happen without anyone thinking it's propaganda, because the moment you think 'that's propaganda' the next question is: 'Who's put that out?'"

What are the files?

He added: "It may be that we have to contract under a different name ... a different entity, with a different name, so that no record exists with our name attached to this at all."

In a recent project in eastern Europe, the company sent a team but "no one even knew they were there, they were just ghosted in, did the work, ghosted out", Turnbull said.

Covers include the setting up of fake academic projects, sometimes simply going in on tourist visas, as former employees have told the Guardian they did for US elections - apparently employed in violation of Federal law.

Nix also offered details regarding the services of professional ex-spies from Britain and Israel. "We have two projects at the moment, which involve doing deep deep depth research on the opposition and providing source ... really damaging source material, that we can decide how to deploy in the course of the campaign."

Denham told Channel 4 News that she had issued a demand for access to Cambridge Analytica earlier this month. They were given until 6pm on Monday to respond to it, but she said the company had been "unco-operative" with the investigation and that she would be applying to the courts on Tuesday for a warrant. "We need to get in there. We need to look at the databases. We need to look at the servers and understand how data was processed or deleted by Cambridge Analytica. There are a lot of conflicting stories about the data," she said.

Cambridge Analytica said the Channel 4 News investigation contained false claims, factual inaccuracies and substantial mischaracterisations.

It accused Channel 4 of setting out to entrap staff by initiating a conversation about unethical practices. It rejected any suggestion that the company used fake news, honey traps, bribes or entrapment.

It said: "We entirely refute any allegation that Cambridge Anlytica or any of its affiliates use entrapment, bribes or so-called 'honey-traps' for any purpose whatsoever ... Cambridge Analytica does not use untrue material for any purpose."

Of the suggestions they used honey trap techniques, the company said: "Our executives humoured these questions and actively encouraged the prospective client to further disclose his intentions."

In a later statement Cambridge Analytica accused Channel 4 News of attempting to entrap its executives by initiating a conversation about unethical practices, which it insisted the company did not use.

Admitting he misjudged the situation, Nix said: "In playing along with this line of conversation ... we entertained a series of ludicrous hypothetical scenarios. I am aware how this looks ... I deeply regret my role in the meeting and I have already apologised to staff. I should have recognised where the prospective client was taking our conversations and ended the relationship sooner."

On Saturday, Cambridge Analytica denied it had done anything wrong in relation to the handling of Facebook data.

"Cambridge Analytica only receives and uses data that has been obtained legally and fairly. Our robust data protection policies comply with US, international, European Union, and national regulations," it said.
Topics

Cambridge Analytica

The Cambridge Analytica Files

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Cambridge Analytica boasts of dirty tricks to swing elections

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The company at the centre of the Facebook data breach boasted of using honey traps, fake news campaigns and operations with ex-spies to swing election campaigns around the world, a new investigation reveals.

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rihanna using social media to ruin a social media

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After Rihanna instructed her 60,000,000 Instagram followers to delete Snapchat, the company's shares plunged- causing the it to lose about $600,000,000.00 in market cap in a matter of hours.

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After Rihanna instructed her 60,000,000 Instagram followers to delete Snapchat, the company's shares plunged- causing the it to lose about $600,000,000.00 in market cap in a matter of hours. https://t.co/KewHFSaDDZ

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After Rihanna instructed her 60,000,000 Instagram followers to delete Snapchat, the company's shares plunged- causing the it to lose about $600,000,000.00 in market cap in a matter of hours. pic.twitter.com/KewHFSaDDZ
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After Rihanna instructed her 60,000,000 Instagram followers to delete Snapchat, the company's shares plunged- causing the it to lose about $600,000,000.00 in market cap in a matter of hours. https://t.co/KewHFSaDDZ

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After Rihanna instructed her 60,000,000 Instagram followers to delete Snapchat, the company's shares plunged- causing the it to lose about $600,000,000.00 in market cap in a matter of hours. https://t.co/KewHFSaDDZ

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After Rihanna instructed her 60,000,000 Instagram followers to delete Snapchat, the company's shares plunged- causing the it to lose about $600,000,000.00 in market cap in a matter of hours.

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ALGORITHMS DETERMINING VISIBILITY/POLITICS

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It was one of January's most viral videos. Logan Paul, a YouTube celebrity, stumbles across a dead man hanging from a tree. The 22-year-old, who is in a Japanese forest famous as a suicide spot, is visibly shocked, then amused. "Dude, his hands are purple," he says, before turning to his friends and giggling. "You never stand next to a dead guy?"

Paul, who has 16 million mostly teen subscribers to his YouTube channel, removed the video from YouTube 24 hours later amid a furious backlash. It was still long enough for the footage to receive 6m views and a spot on YouTube's coveted list of trending videos.

'Our minds can be hijacked': the tech insiders who fear a smartphone dystopia
The next day, I watched a copy of the video on YouTube. Then I clicked on the "Up next" thumbnails of recommended videos that YouTube showcases on the right-hand side of the video player. This conveyor belt of clips, which auto-play by default, are designed to seduce us to spend more time on Google's video broadcasting platform. I was curious where they might lead.

The answer was a slew of videos of men mocking distraught teenage fans of Logan Paul, followed by CCTV footage of children stealing things and, a few clicks later, a video of children having their teeth pulled out with bizarre, homemade contraptions.

I had cleared my history, deleted my cookies, and opened a private browser to be sure YouTube was not personalising recommendations. This was the algorithm taking me on a journey of its own volition, and it culminated with a video of two boys, aged about five or six, punching and kicking one another.

"I'm going to post it on YouTube," said a teenage girl, who sounded like she might be an older sibling. "Turn around and punch the heck out of that little boy." They scuffled for several minutes until one had knocked the other's tooth out.

There are 1.5 billion YouTube users in the world, which is more than the number of households that own televisions. What they watch is shaped by this algorithm, which skims and ranks billions of videos to identify 20 "up next" clips that are both relevant to a previous video and most likely, statistically speaking, to keep a person hooked on their screen.

Company insiders tell me the algorithm is the single most important engine of YouTube's growth. In one of the few public explanations of how the formula works - an academic paper that sketches the algorithm's deep neural networks, crunching a vast pool of data about videos and the people who watch them - YouTube engineers describe it as one of the "largest scale and most sophisticated industrial recommendation systems in existence".

The algorithm does not appear to be optimising for what is truthful, or balanced, or healthy for democracy

Guillaume Chaslot, an ex-Google engineer

Lately, it has also become one of the most controversial. The algorithm has been found to be promoting conspiracy theories about the Las Vegas mass shooting and incentivising, through recommendations, a thriving subculture that targets children with disturbing content such as cartoons in which the British children's character Peppa Pig eats her father or drinks bleach.

Lewd and violent videos have been algorithmically served up to toddlers watching YouTube Kids, a dedicated app for children. One YouTube creator who was banned from making advertising revenues from his strange videos - which featured his children receiving flu shots, removing earwax, and crying over dead pets - told a reporter he had only been responding to the demands of Google's algorithm. "That's what got us out there and popular," he said. "We learned to fuel it and do whatever it took to please the algorithm."

Google has responded to these controversies in a process akin to Whac-A-Mole: expanding the army of human moderators, removing offensive YouTube videos identified by journalists and de-monetising the channels that create them. But none of those moves has diminished a growing concern that something has gone profoundly awry with the artificial intelligence powering YouTube.

Yet one stone has so far been largely unturned. Much has been written about Facebook and Twitter's impact on politics, but in recent months academics have speculated that YouTube's algorithms may have been instrumental in fuelling disinformation during the 2016 presidential election. "YouTube is the most overlooked story of 2016," Zeynep Tufekci, a widely respected sociologist and technology critic, tweeted back in October. "Its search and recommender algorithms are misinformation engines."

If YouTube's recommendation algorithm really has evolved to promote more disturbing content, how did that happen? And what is it doing to our politics?

'Like reality, but distorted'

Those are not easy questions to answer. Like all big tech companies, YouTube does not allow us to see the algorithms that shape our lives. They are secret formulas, proprietary software, and only select engineers are entrusted to work on the algorithm. Guillaume Chaslot, a 36-year-old French computer programmer with a PhD in artificial intelligence, was one of those engineers.

During the three years he worked at Google, he was placed for several months with a team of YouTube engineers working on the recommendation system.The experience led him to conclude that the priorities YouTube gives its algorithms are dangerously skewed.

"YouTube is something that looks like reality, but it is distorted to make you spend more time online," he tells me when we meet in Berkeley, California. "The recommendation algorithm is not optimising for what is truthful, or balanced, or healthy for democracy."

Chaslot explains that the algorithm never stays the same. It is constantly changing the weight it gives to different signals: the viewing patterns of a user, for example, or the length of time a video is watched before someone clicks away.
Las Vegas survivors furious as YouTube promotes clips calling shooting a hoax
The engineers he worked with were responsible for continuously experimenting with new formulas that would increase advertising revenues by extending the amount of time people watched videos. "Watch time was the priority," he recalls. "Everything else was considered a distraction."

Chaslot was fired by Google in 2013, ostensibly over performance issues. He insists he was let go after agitating for change within the company, using his personal time to team up with like-minded engineers to propose changes that could diversify the content people see.

He was especially worried about the distortions that might result from a simplistic focus on showing people videos they found irresistible, creating filter bubbles, for example, that only show people content that reinforces their existing view of the world. Chaslot said none of his proposed fixes were taken up by his managers. "There are many ways YouTube can change its algorithms to suppress fake news and improve the quality and diversity of videos people see," he says. "I tried to change YouTube from the inside but it didn't work."

YouTube told me that its recommendation system had evolved since Chaslot worked at the company and now "goes beyond optimising for watchtime". The company said that in 2016 it started taking into account user "satisfaction", by using surveys, for example, or looking at how many "likes" a video received, to "ensure people were satisfied with what they were viewing". YouTube added that additional changes had been implemented in 2017 to improve the news content surfaced in searches and recommendations and discourage the promotion of videos containing "inflammatory religious or supremacist" content.

It did not say why Google, which acquired YouTube in 2006, waited over a decade to make those changes. Chaslot believes such changes are mostly cosmetic, and have failed to fundamentally alter some disturbing biases that have evolved in the algorithm. In the summer of 2016, he built a computer program to investigate.

The software Chaslot wrote was designed to provide the world's first window into YouTube's opaque recommendation engine. The program simulates the behaviour of a user who starts on one video and then follows the chain of recommended videos - much as I did after watching the Logan Paul video - tracking data along the way.

It finds videos through a word search, selecting a "seed" video to begin with, and recording several layers of videos that YouTube recommends in the "up next" column. It does so with no viewing history, ensuring the videos being detected are YouTube's generic recommendations, rather than videos personalised to a user. And it repeats the process thousands of times, accumulating layers of data about YouTube recommendations to build up a picture of the algorithm's preferences.

Over the last 18 months, Chaslot has used the program to explore bias in YouTube content promoted during the French, British and German elections, global warming and mass shootings, and published his findings on his website, Algotransparency.org. Each study finds something different, but the research suggests YouTube systematically amplifies videos that are divisive, sensational and conspiratorial.

When his program found a seed video by searching the query "who is Michelle Obama?" and then followed the chain of "up next" suggestions, for example, most of the recommended videos said she "is a man". More than 80% of the YouTube-recommended videos about the pope detected by his program described the Catholic leader as "evil", "satanic", or "the anti-Christ". There were literally millions of videos uploaded to YouTube to satiate the algorithm's appetite for content claiming the earth is flat. "On YouTube, fiction is outperforming reality," Chaslot says.

He believes one of the most shocking examples was detected by his program in the run-up to the 2016 presidential election. As he observed in a short, largely unnoticed blogpost published after Donald Trump was elected, the impact of YouTube's recommendation algorithm was not neutral during the presidential race: it was pushing videos that were, in the main, helpful to Trump and damaging to Hillary Clinton. "It was strange," he explains to me. "Wherever you started, whether it was from a Trump search or a Clinton search, the recommendation algorithm was much more likely to push you in a pro-Trump direction."

Trump won the electoral college as a result of 80,000 votes spread across three swing states. There were more than 150 million YouTube users in the US. The videos contained in Chaslot's database of YouTube-recommended election videos were watched, in total, more than 3bn times before the vote in November 2016.

Even a small bias in the videos would have been significant. "Algorithms that shape the content we see can have a lot of impact, particularly on people who have not made up their mind," says Luciano Floridi, a professor at the University of Oxford's Digital Ethics Lab, who studies the ethics of artificial intelligence. "Gentle, implicit, quiet nudging can over time edge us toward choices we might not have otherwise made."

Promoting conspiracy theories

Chaslot sent me a database of more YouTube-recommended videos his program identified in the three months leading up to the presidential election. It contained more than 8,000 videos - all of them detected by his program appearing "up next" on 12 dates between August and November 2016, after equal numbers of searches for "Trump" and "Clinton".

It was not a comprehensive set of videos and it may not have been a perfectly representative sample. But it was, Chaslot said, a previously unseen dataset of what YouTube was recommending to people interested in content about the candidates - one snapshot, in other words, of the algorithm's preferences.

Jonathan Albright, research director at the Tow Center for Digital Journalism, who reviewed the code used by Chaslot, says it is a relatively straightforward piece of software and a reputable methodology. "This research captured the apparent direction of YouTube's political ecosystem," he says. "That has not been done before."

I spent weeks watching, sorting and categorising the trove of videos with Erin McCormick, an investigative reporter and expert in database analysis. From the start, we were stunned by how many extreme and conspiratorial videos had been recommended, and the fact that almost all of them appeared to be directed against Clinton.

Some of the videos YouTube was recommending were the sort we had expected to see: broadcasts of presidential debates, TV news clips, Saturday Night Live sketches. There were also videos of speeches by the two candidates - although, we found, the database contained far more YouTube-recommended speeches by Trump than Clinton.

But what was most compelling was how often Chaslot's software detected anti-Clinton conspiracy videos appearing "up next" beside other videos.

There were dozens of clips stating Clinton had had a mental breakdown, reporting she had syphilis or Parkinson's disease, accusing her of having secret sexual relationships, including with Yoko Ono. Many were even darker, fabricating the contents of WikiLeaks disclosures to make unfounded claims, accusing Clinton of involvement in murders or connecting her to satanic and paedophilic cults.

One video that Chaslot's data indicated was pushed particularly hard by YouTube's algorithm was a bizarre, one-hour film claiming Trump's rise was predicted in Isaiah 45. Another was entitled: "BREAKING: VIDEO SHOWING BILL CLINTON RAPING 13 YR-OLD WILL PLUNGE RACE INTO CHAOS ANONYMOUS CLAIMS". The recommendation engine appeared to have been particularly helpful to the Alex Jones Channel, which broadcasts far-right conspiracy theories under the Infowars brand.

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The conspiracy theorist and talkshow host Alex Jones. Photograph: Brooks Kraft/Getty Images

There were too many videos in the database for us to watch them all, so we focused on 1,000 of the top-recommended videos. We sifted through them one by one to determine whether the content was likely to have benefited Trump or Clinton. Just over a third of the videos were either unrelated to the election or contained content that was broadly neutral or even-handed. Of the remaining 643 videos, 551 were videos favouring Trump, while only only 92 favoured the Clinton campaign.

The sample we had looked at suggested Chaslot's conclusion was correct: YouTube was six times more likely to recommend videos that aided Trump than his adversary. YouTube presumably never programmed its algorithm to benefit one candidate over another. But based on this evidence, at least, that is exactly what happened.

'Leading people down hateful rabbit holes'

"We have a great deal of respect for the Guardian as a news outlet and institution," a YouTube spokesperson emailed me after I forwarded them our findings. "We strongly disagree, however, with the methodology, data and, most importantly, the conclusions made in their research."

The spokesperson added: "Our search and recommendation systems reflect what people search for, the number of videos available, and the videos people choose to watch on YouTube. That's not a bias towards any particular candidate; that is a reflection of viewer interest."

It was a curious response. YouTube seemed to be saying that its algorithm was a neutral mirror of the desires of the people who use it - if we don't like what it does, we have ourselves to blame. How does YouTube interpret "viewer interest" - and aren't "the videos people choose to watch" influenced by what the company shows them?

Offered the choice, we may instinctively click on a video of a dead man in a Japanese forest, or a fake news clip claiming Bill Clinton raped a 13-year-old. But are those in-the-moment impulses really a reflect of the content we want to be fed?

Tufekci, the sociologist who several months ago warned about the impact YouTube may have had on the election, tells me YouTube's recommendation system has probably figured out that edgy and hateful content is engaging. "This is a bit like an autopilot cafeteria in a school that has figured out children have sweet teeth, and also like fatty and salty foods," she says. "So you make a line offering such food, automatically loading the next plate as soon as the bag of chips or candy in front of the young person has been consumed."

Once that gets normalised, however, what is fractionally more edgy or bizarre becomes, Tufekci says, novel and interesting. "So the food gets higher and higher in sugar, fat and salt - natural human cravings - while the videos recommended and auto-played by YouTube get more and more bizarre or hateful."

But why would a bias toward ever more weird or divisive videos benefit one candidate over another? That depends on the candidates. Trump's campaign was nothing if not weird and divisive. Tufekci points to studies showing that "field of misinformation" largely tilted anti-Clinton before the election. "Fake news providers," she says, "found that fake anti-Clinton material played much better with the pro-Trump base than did fake anti-Trump material with the pro-Clinton base."

She adds: "The question before us is the ethics of leading people down hateful rabbit holes full of misinformation and lies at scale just because it works to increase the time people spend on the site - and it does work."

Tech giants face Congress as showdown over Russia election meddling looms

Tufekci was one of several academics I shared our research with. Philip Howard, a professor at the Oxford Internet Institute, who has studied how disinformation spread during the election, was another. He questions whether a further factor might have been at play. "This is important research because it seems to be the first systematic look into how YouTube may have been manipulated," he says, raising the possibility that the algorithm was gamed as part of the same propaganda campaigns that flourished on Twitter and Facebook.

In testimony to the House intelligence committee, investigating Russian interference in the election, Google's general counsel, Kent Walker, played down the degree to which Moscow's propaganda efforts infiltrated YouTube. The company's internal investigation had only identified 18 YouTube channels and 1,100 videos suspected of being linked to Russia's disinformation campaign, he told the committee in December - and generally the videos had relatively small numbers of views. He added: "We believe that the activity we found was limited because of various safeguards that we had in place in advance of the 2016 election, and the fact that Google's products didn't lend themselves to the kind of micro-targeting or viral dissemination that these actors seemed to prefer."

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General counsels for Twitter, Facebook and Google prepare to testify before the House intelligence committee hearing on Russia's use of social media to influence the election. Photograph: Shawn Thew/EPA

Walker made no mention of YouTube recommendations. Correspondence made public just last week, however, reveals that Senator Mark Warner, the ranking Democrat on the intelligence committee, later wrote to the company about the algorithm, which he said seemed "particularly susceptible to foreign influence". The senator demanded to know what the company was specifically doing to prevent a "malign incursion" of YouTube's recommendation system. Walker, in his written reply, offered few specifics, but said YouTube had "a sophisticated spam and security breach detection system to identify anomalous behavior and malignant incursions".

Tristan Harris, a former Google insider turned tech whistleblower, likes to describe Facebook as a "living, breathing crime scene for what happened in the 2016 election" that federal investigators have no access to. The same might be said of YouTube. About half the videos Chaslot's program detected being recommended during the election have now vanished from YouTube - many of them taken down by their creators. Chaslot has always thought this suspicious. These were videos with titles such as "Must Watch!! Hillary Clinton tried to ban this video", watched millions of times before they disappeared. "Why would someone take down a video that has been viewed millions of times?" he asks.

Quick guide
What you need to know about the Trump-Russia inquiry

How serious are the allegations?

The story of Donald Trump and Russia comes down to this: a sitting president or his campaign is suspected of having coordinated with a foreign country to manipulate a US election. The story could not be bigger, and the stakes for Trump - and the country - could not be higher.

What are the key questions?

Investigators are asking two basic questions: did Trump's presidential campaign collude at any level with Russian operatives to sway the 2016 US presidential election? And did Trump or others break the law to throw investigators off the trail?

What does the country think?

While a majority of the American public now believes that Russia tried to disrupt the US election, opinions about Trump campaign involvement tend to split along partisan lines: 73% of Republicans, but only 13% of Democrats, believe Trump did "nothing wrong" in his dealings with Russia and its president, Vladimir Putin.

What are the implications for Trump?

The affair has the potential to eject Trump from office. Experienced legal observers believe that prosecutors are investigating whether Trump committed an obstruction of justice. Both Richard Nixon and Bill Clinton - the only presidents to face impeachment proceedings in the last century - were accused of obstruction of justice. But Trump's fate is probably up to the voters. Even if strong evidence of wrongdoing by him or his cohort emerged, a Republican congressional majority would probably block any action to remove him from office. (Such an action would be a historical rarity.)

What has happened so far?

Former foreign policy adviser George Papadopolous pleaded guilty to perjury over his contacts with Russians linked to the Kremlin, and the president's former campaign manager Paul Manafort and another aide face charges of money laundering.

When will the inquiry come to an end?

The investigations have an open timeline.

Was this helpful?

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I located a copy of "This Video Will Get Donald Trump Elected", a viral sensation that was watched more than 10m times before it vanished from YouTube. It was a benign-seeming montage of historical footage of Trump, accompanied by soft piano music. But when I played the video in slow motion, I saw that it contained weird flashes of Miley Cyrus licking a mirror. It seemed an amateurish and bizarre attempt at inserting subliminal, sexualised imagery. But it underscored how little oversight we have over anyone who might want to use YouTube to influence public opinion on a vast scale.

I shared the entire database of 8,000 YouTube-recommended videos with John Kelly, the chief executive of the commercial analytics firm Graphika, which has been tracking political disinformation campaigns. He ran the list against his own database of Twitter accounts active during the election, and concluded many of the videos appeared to have been pushed by networks of Twitter sock puppets and bots controlled by pro-Trump digital consultants with "a presumably unsolicited assist" from Russia.

"I don't have smoking-gun proof of who logged in to control those accounts," he says. "But judging from the history of what we've seen those accounts doing before, and the characteristics of how they tweet and interconnect, they are assembled and controlled by someone - someone whose job was to elect Trump."

Chaslot and some of the academics I spoke to felt this social media activity was significant. YouTube's algorithm may have developed its biases organically, but could it also have been nudged into spreading those videos even further? "If a video starts skyrocketing, there's no question YouTube's algorithm is going to start pushing it," Albright says.

YouTube did not deny that social media propaganda might have influenced its recommendations, but played down the likelihood, stressing its system "does not optimise" for traffic from Twitter or Facebook. "It appears as if the Guardian is attempting to shoehorn research, data and their conclusions into a common narrative about the role of technology in last year's election," the spokesperson added. "The reality of how our systems work, however, simply don't support this premise."

After the Senate's correspondence with Google over possible Russian interference with YouTube's recommendation algorithm was made public last week, YouTube sent me a new statement. It emphasised changes it made in 2017 to discourage the recommendation system from promoting some types of problematic content. "We appreciate the Guardian's work to shine a spotlight on this challenging issue," it added. "We know there is more to do here and we're looking forward to making more announcements in the months ahead."

Content creators

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'Fiction is outperforming reality': how YouTube's algorithm distorts truth

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It was one of January's most viral videos. Logan Paul, a YouTube celebrity, stumbles across a dead man hanging from a tree. The 22-year-old, who is in a Japanese forest famous as a suicide spot, is visibly shocked, then amused. "Dude, his hands are purple," he says, before turning to his friends and giggling.

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Hans Ulrich Obrist interviews Ethereum (a cryptocurrency) founder, Vitalik Buterin

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A thing of beauty and permanence in an age of transience. Since 1998.

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politics embedded into tech! and therefore "unquestionable", bc tech is logical/science and that is objective! but it's not!!

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Over the past several decades, politicians and business leaders, technology pundits and the mainstream media, engineers and computer scientists-as well as science fiction and Hollywood films-have repeated a troubling refrain, championing the shift away from the material and toward the virtual, the networked, the digital, the online. It is as if all of life could be reduced to 1s and 0s, rendering it computable.

Apple's recent iPhone X announcement is a perfect example of this. In the opening statement of the film that introduces the newest version of the company's signature product, Apples states, "For more than a decade, our intention has been to create an iPhone that is all display. A physical object that disappears into the experience" (emphasis mine).

This is more than just sophisticated advertising. Rather, it is an affirmation of more than 25 years of design criteria and engineering logic from the field of ubiquitous computing, which originated at Xerox PARC with Mark Weiser's well-known statement that "the most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it."

Weiser's vision set the stage-and, more importantly, shaped the business agenda-for the creation of a world in which hundreds of tiny computers would be embedded into the environment invisibly and seamlessly. Today, it is in design criteria and engineering specifications-such as "invisibility" and "seamlessness," which aim to improve the human experience with technology-that ethical decisions are negotiated.

Whether this disappearance is literal or metaphorical in the case of the iPhone X, the emphasis on dematerialization is significant because it plays such a large role in the animating logic of our time. Such characterizations make it easy to dismiss the material realities of technologies, including the ways in which they are entangled with human bodies, environmental resources, and political economies.

We have been enticed into a world in which computing has faded into the background of everyday life, effectively becoming invisible. At the same time, we have actively concealed the ways in which these networked systems of software, data, technologies, and infrastructures "have politics." And, with promises that computers are impartial, we have removed them from the public eye, making them difficult to expose and critique.

Yet these systems can only be understood as the flawed extensions of human creation. They act on our biases by replicating them and distributing them into the background of everyday life, thereby reinforcing and even exacerbating existing structural inequalities.

Take this example. In late July 2017, the City of Chicago agreed to settle a $38.75 million class-action lawsuit related to its red-light-camera program. Under the settlement, the city will repay drivers who were unfairly ticketed a portion of the cost of their ticket. Over the past five years, the program, ostensibly implemented to make Chicago's intersections safer, has been mired in corruption, bribery, mismanagement, malfunction, and moral wrongdoing. This confluence of factors has resulted in a great deal of negative press about the project.

The red-light-camera program is just one of many examples of such technologies being adopted by cities in their quest to become "smart" and, at the same time, increase revenue. Others include ticketless parking, intelligent traffic management, ride-sharing platforms, wireless networks, sensor-embedded devices, surveillance cameras, predictive policing software, driverless car testbeds, and digital-fabrication facilities.

The company that produced the red-light cameras, Redflex, claims on their website that their technology can "reliably and consistently address negative driving behaviors and effectively enforce traffic laws on roadways and intersections with a history of crashes and incidents." Nothing could be further from the truth. Instead, the cameras were unnecessarily installed at some intersections without a history of problems; they malfunctioned; they issued illegal tickets due to short yellow-lights that were not within federal limits; and they issued tickets after enforcement hours. And, due to existing structural inequalities, these difficulties were more likely to negatively impact poorer and less advantaged city residents.

The controversies surrounding red-light cameras in Chicago make visible the ways in which design criteria and engineering specifications-concepts including safety and efficiency, seamlessness and stickiness, convenience and security-are themselves ways of defining the ethics, values, and politics of our cities and citizens. To be sure, these qualities seem clean, comforting, and cuddly at first glance. They are difficult to argue against.

But, like wolves in sheep's clothing, they gnash their political-economic teeth, and show their insatiable desire to further the goals of neoliberal capitalism. Rather than merely slick marketing, these mundane infrastructures (hardware, software, data, and services) negotiate ethical questions around what kinds of societies we aspire to, what kind of cities we want to live in, what kinds of citizens we can become, who will benefit from these tradeoffs, and who will be left out.

Furthermore, the red-light-camera example should not be understood as a rare exception. Rather, it is business as usual at the intersection of technology and politics. As human and technological systems become more deeply enmeshed and indistinguishable from one another-mutually reinforcing their own possibilities and the failures-we can only expect such examples to become more commonplace.

Networked systems act on our biases by replicating them and distributing them into the background of everyday life, thereby reinforcing and even exacerbating existing structural inequalities.

Rather than letting these systems fade into the background, as advocated by so many science fiction accounts and technologist visions, a deeper engagement with the material realities of digital technologies is necessary. This public participation in understanding, experiencing, and evaluating these technologies will allow for the development of an essential language and literacy around these systems and, in particular, the ways in which they embody our ethics and values. As a result, we will be able to design and use technologies to reinforce principles of equality, fairness, and justice.

How might we make sense of the politics at play in the iPhone's quest to become invisible? Can we meaningfully untangle the issues plaguing Chicago's red-light-camera program? In what ways can we engage with future technologies and ensure that they reflect our values?

Three recent books published by MIT Press-Paul Dourish's The Stuff of Bits, Hamid Ekbia and Bonnie Nardi's Heteromation, and Ed Finn's What Algorithms Want -help to answer these questions, specifically those about the material realities of the technologies that we use (and those that use us) everyday, as well as those that we will design in the future. Each of these three books deals with a different way in which invisibility has come to dominate our technological understanding: Dourish argues that software itself has a distinct materiality that is often overlooked; Finn turns to the history of computing, illustrating a persistent gap between ideas and implementations; while Ekbia and Nardi highlight the important connection between labor and technology. All of these books seek to make visible the hidden politics of technology by overturning the myth of "impartial" code, and excavating the biases and bodies in the machine.

There is no such thing as "just code," writes Finn. There are no immaterial 1s and 0s mediating reality without also being implemented in the material world. Rather, algorithms are always the product of social, technical, and political decisions, negotiations and tradeoffs that occur throughout their development and implementation. And, this is where biases, values, and discrimination disappear into the black box behind the computational curtain.

From racist predictive-policing software to discriminatory algorithmic hiring platforms to the role of social media in the 2016 presidential election and the Equifax breach, it is becoming more and more difficult to ignore the growing evidence that illustrates the ways in which algorithms reflect our biases. Yet we continue to perpetuate mythologies of simplicity, invisibility, and efficiency that present these systems as neutral, logical, and immaterial, insisting that they, in Finn's words, "work according to very different rules from material culture."

In The Stuff of Bits: An Essay on the Materialities of Information, Dourish argues against this dematerialization and the "substitution of bits for atoms," illustrating the ways in which the "the physical world persistently makes itself felt." Drawing on empirical descriptions of what he calls "the materialities of information representation" in the case of software, spreadsheets, databases, internet-routing protocols, and networks, he makes the important argument that bits "are not just bits. Some matter more than others." He explains further:

Some arrangements of bits are more easily manipulable than others. Some are more amenable to one form of processing or another. Some arrangements of bits can be transmitted easily over unreliable networks while others cannot; some can be processed by the applications on our computers, and some cannot; some can fit into limited storage, and some cannot; some can be efficiently processed by parallel computers, and some cannot. Some are designed for concision, some for robustness, and some for interactivity.

In further elaborating on the materiality of information, Dourish develops a rich set of properties and qualities to describe the ways in which the software and its representations can be "created, transmitted, stored, manipulated, and put to use-properties like their heft, size, fragility, and transparency" and qualities including robustness, malleability, speed, error detection, and consistency.

How might we apply Dourish's analysis to the red-light-camera program described above? Dourish argues that the "social and material are entwined," meaning that it is necessary to consider the entire system of technologies in the context of historical, social, political, and economic conditions. The red-light-camera system consists of hardware, software, and services; the software itself includes the ability to "capture, process, protect or enforce the targeted behavior" using sensory devices, business process management software and network integration and monitoring software. Rather than expecting these systems to function invisibly in the background, their breakdowns-whether social or technical-reveal the ways in which it is foolish to put too much trust in the universal claims of technological solutions. Specifically, in this case, rather than enforcing specific behaviors of safe driving, the system created fearful city residents, afraid to drive through certain intersections (sometimes choosing instead to back up, causing unnecessary accidents).

While Dourish acknowledges that "a materialist account can provide a[n] entry point to much broader concerns than simply infrastructures and their configurations, opening up questions of power, policy, and polity in the realm of the digital" (especially in the chapter about internet routing), he does not elaborate significantly in detail on the ways in which the specific examples that he describes reflect the political economy of neoliberal capitalism.

This is where Ekbia and Nardi's book makes an essential contribution in tracing the parallel developments of technology (specifically, computing, beginning with the Jacquard loom in 1801) and the economy, as well as the ways in which they shape one another. In Heteromation, and other Stories of Computing and Capitalism, Ekbia and Nardi analyze the relationship between "two magical phenomena," "the division of labor between humans and machines, and how it is configured and put to use by contemporary capitalism."

Heteromation is the term that Ekbia and Nardi use to describe a "new logic of capital accumulation" in which economic value is extracted from "low-cost or free labor in computer-mediated networks." They argue that this "new division of labor" is often invisible, unrecognized (as "economically valuable"), uncompensated, hidden, and naturalized (as necessary for use and "what it means to be a 'user' of digital technology"). They offer examples from five different kinds of labor, each with its own ways of extracting and obscuring value: communicative labor (social media and "social data"), cognitive labor (crowd-work and sharing economy platforms), creative labor (gaming and design), emotional labor (social robots and care work), and organizing labor (customer reviews, citizen science, and peer production).

More specifically, framing these digital technologies as "responses to the predicaments [negative drivers] and opportunities [positive drivers] of capitalism," their book is concerned with the ways in which economic value is extracted from these activities, the nature of that value, and the reasons why people-individually and collectively-participate in digital labor through these networks in ways that are difficult to refuse.

And, here, we have an important link to Dourish's argument about materiality. Rather than the blunt, cold reality of Foucault's panopticon, Ekbia and Nardi locate digital control in its "light, elegant, delicate, implicit, hidden, continuous, dispersed nature." They note that so many of the ways in which control is exercised in contemporary society is through "nearly invisible digital mechanisms" (emphasis mine).

Ekbia and Nardi's goal is to situate discussions about digitally mediated labor within the history of capitalism, which they argue has been overlooked in many academic disciplines that study technology from a sociological or cultural perspective. For Ekbia and Nardi, labor "is a uniquely human capacity, which accounts for the production of economic value in capitalism."

In What Algorithms Want: Imagination in the Age of Computing, Ed Finn points toward what appears to be an agreement with Dourish's characterization about the material agency of software, stating that the problematic structural metaphors that are commonly used to describe code (such as platforms and architectures) de-personify it and render it as a passive actor. Drawing on Ian Bogost's characterization of the "computational theocracy," Finn compares algorithmic culture to religion, paying great attention to the ways in which our mystical, magical, and mythological beliefs about computation-reified through science fiction novels and films-and the trust that we place in machines often render their architecture and underlying machinery invisible, immaterial, or out of view.

Each of these three books deals with a different way in which invisibility has come to dominate our technological understanding.

Finn locates his analysis of the algorithm within the long Western, Enlightenment, rationalist quest for a universal system of knowledge (one that eventually goes beyond the human), which has been fulfilled through the creation of "a unified vision of the world through clean interfaces and carefully curated data-everything you might want to know, now available as an app." Drawing on the history of computer science, cybernetics, and information theory, as well as linguistic metaphors around magic and the ways in which social and cultural practices coevolve with technology, Finn examines a series of examples including Apple's Siri, Netflix recommendation systems, gamification on Facebook (as well as on Uber and other digital labor platforms), and cryptocurrency.

He argues that these technology companies, which he calls "cultural wrappers" for algorithms, are ultimately "constructing a new epistemological framework of what is knowable and desirable," in ways that will shape the public sphere, the economy, and how value is measured computationally, as well as human subjectivity and what it means to be human.

All three of these books argue for a deeper understanding of and engagement with the materialities of computing-software and the inner workings of computation and networks, economies and labor, and algorithms as culture machines. They expose the consequences of our intimate dependencies on computational technologies and infrastructures, which cross social, cultural, economic, political, and ethical domains. They question the ways in which we are enticed to participate and the mythologies that are perpetuated through the narratives of dematerialization. These imaginaries of immateriality continue to inhibit our ability to fully understand the implications of digital technologies such as the red-light cameras in Chicago. Finally, they make it easier to dismiss the labor and environmental resources that are distributed in these networks.

In my own work over the past 10 years I have observed the ways in which we, as a society, are often complicit in reinforcing the invisibility of technology. As users, we often repeat the touted benefits of a technology, even when our lived experience doesn't reflect those claims. For example, when interviewing precarious freelance workers in the mid-2000s, I often heard of the freedoms that they experienced using Wi-Fi networks to work from cafes, parks, and public spaces. Despite this, many of them worked in the same place everyday or alternated between just one or two places, exhibiting very particular, situated routines. Similarly, in my own personal experience as a user of networked medical devices, I deliberately keep my insulin pump out of view despite writing about myself as a kind of "disabled cyborg" and the ways in which the pump requires constant attention, maintenance, and care that interrupt my everyday life.

It is not enough to merely critique these technological systems. We must actively expose the hidden politics of emerging technologies by finding new ways to study them, visualize them, experience them, and evaluate them long before they are adopted into mainstream use. We must engage directly-both across disciplines and with the broader public-in order to advocate for the values that we espouse and, ultimately, change the shape of the technologies that we will live with in the future.

There are many interventionist and activist approaches that might contribute to a more critical engagement with technology. In one project, with support from the Open Society Foundations, I conducted a participatory design workshop with social and economic justice activists about the future of work and automation. In another project, I was a creator of a visualization on driverless cars that was featured in the New York Times Magazine and speculative videos that were featured in the 2017 Vienna Biennale. By engaging these topics and even collaborating directly with engineers and computer scientists, it is possible to glimpse the ethical ghosts in the machine.

As we near the 30th anniversary of Weiser's vision of ubiquitous computing, it is vital that we resist the lure of invisibility and, instead, make visible the ethics embedded in technology. In so doing, we can insure that our values-transparency, openness, justice, and accountability-are reflected in future systems and societies. "The algorithm offers us salvation," writes Finn, "but only after we accept its terms of service."

Featured image: Martin Nadal, Bitcoin Traces (2017). Source: Ars Electronica / Flickr

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Over the past several decades, politicians and business leaders, technology pundits and the mainstream media, engineers and computer scientists-as well as science fiction and Hollywood films-have repeated a troubling refrain, championing the shift away from the material and toward the virtual, the networked, the digital, the online.

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Top Researchers Outline the Malicious Potential of AI Technology

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image] As Daniel Oberhaus writes for Motherboard, a group of top AI researchers has published a major report about the future potential for AI technology to be used for nefarious purposes, from hacking to surveillance to the takeover of automated systems like the ones that control self-driving cars.

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-jeff bezos owns amazon
-jeff bezos owns the washington post
~what does this say about digital businesses taking up the market over independent booksellers?

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Last Thursday, the Washington Post announced that its new weekly bestsellers list would be calculated with some unconventional data. The calculations will include information from Amazon's reading subscription services, including Prime Reading and Kindle Unlimited. The Post has also begun publishing Amazon's " Most read " list in syndication.

David Naggar, vice president of Amazon, said he was "excited to collaborate with The Washington Post to give book lovers a more comprehensive U.S. bestseller list to help them discover their next great read." And Mitch Rubin, deputy features editor, said, "Readers have long turned to The Post's books coverage for reviews and recommendations from some of the top book critics in the nation. The new Bestsellers lists add to the breadth of our books coverage by giving readers a truer sense of what books are being sold each week."

Neither Naggar nor Rubin, nor anyone else in the press release, took time to mention that the Washington Post is owned by Amazon founder and CEO Jeff Bezos, who bought the paper for $250 million in 2013. The Post does provide a disclosure on its reviews page, which reads:

The Post compiles its bestsellers lists by combining hard cover, paperback and ebook sales data from Nielsen Bookscan and Amazon.com - including qualified borrows of books read through Amazon's digital subscription program. The Post excludes non-narrative books at its sole discretion. Amazon founder and chief executive Jeffrey P. Bezos owns The Post.

Which is relevant, as this appears to be the first time that Bezos has intentionally cross-pollinated his two ventures, though he has quickly imported his own sensibilities into the Post's business model. Since Bezos acquired it, the paper has branched out into platform-building on the Amazon model, developing a suite of fairly obscure technical services - stuff like Heliograf, an " automated storytelling system," and Bradbury, "a streamlined workflow, allowing a single editor to create far more lists in much less time," announced in the same press release, as part of the Post's publishing platform, Arc Publishing.

Amazon Charts launched last year as "a reimagined weekly bestseller list that shares which books are being read the most and which books have sold the most across all formats each week." Along with a general ranking, and links to purchase the books, Amazon Charts occasionally include "fun facts" about a book's performance over a given week. Select books are labelled "Unputdownable" (meaning Kindle and Audible readers finish them faster than similar books) or "All Ears" (meaning the book was listened to more than read in the past week), and sometimes Amazon will provide regional context for a particular book. This week, for example, Amazon let us know that A.J. Finn's The Woman in the Window was the most popular of the Most Read books in New York State.

The only novel element of Charts is the availability of subscription sales data, which has not traditionally been available through other reporting methods like BookScan. But, as Ingrid Lundgrin pointed out in TechCruch last year, these lists are also a window into one of Amazon's huge strategic advantages: the staggering amount of information the company gathers on its customers' purchasing habits. The inclusion of these data streams into the Post 's bestseller lists offers a sleek public example of one way that Amazon is taking advantage of its constant surveillance and its owner's multiple media holdings.

Of course, the Amazon has been playing a variation on this tune for the better part of a decade now: Amazon Alexa, Amazon Web Services, and IMDbPro, for a few, are all powered by Amazon's titanic information storehouses and the infrastructure that was built to manage and organize them. What's surprising and a little unsettling is how seamlessly and quietly Bezos has managed to integrate Amazon services into a nominally independent publication. It's a perfect example of the not-so-slow Amazonification of American culture and commerce.

It's too soon to say exactly what this means for booksellers and publishers. While the Post has not gone so far as to include sales links to Amazon (the Times and USA Today lists do), it's safe to assume that the preponderance of readers will be buying there anyways, in which case Bezos needn't overplay his hand.

But, as is always the case with monopolies, no particular action taken by Amazon or Bezos is that scary or weird, viewed in isolation. Syndicating a bestseller list seems like a pretty normal thing for a retail conglomerate to do, and a newspaper owned by the same guy as said conglomerate seems like an obvious choice of venue. But in context, it's clearly the opening of another front in Bezos's decades-long quest to control absolutely fucking everything.

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Into the Bezosphere: The Washington Post will syndicate Amazon Charts " MobyLives

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Last Thursday, the Washington Post announced that its new weekly bestsellers list would be calculated with some unconventional data. The calculations will include information from Amazon's reading subscription services, including Prime Reading and Kindle Unlimited. The Post has also begun publishing Amazon's "Most read" list in syndication. David Naggar,…

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what is with our generations weird sense of nostalgia!!
nostalgia is the longing for a past which seems less overwhelming/stressful, more innocent etc etc
are young people now turning to nostalgic media bc we have no other control? we're not yearning for the specific time of 10yrs ago, but a time where we didn't have to constantly worry about everything?

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Although the series might have lost its spark in recent years, we're still struggling to stop watching - and in some corners of the internet it's become an obsession that refuses to die.

Although the series might have lost its spark in recent years, we're still struggling to stop watching - and in some corners of the internet it's become an obsession that refuses to die.

When I was about 10 years old, my favourite thing to do on this earth was to eat a microwaved pizza cut into rectangular slices with ketchup and watch an old VHS tape of The Simpsons. Their neon-dipped universe was comforting and hilarious, and even though this video only had the same four grainy episodes, which I played over and over again, it never bored me. Even the familiar theme tune filled me with an easy happiness, like climbing into a freshly laundered bed, or taking a bite of perfectly buttered cheap white toast.

This is not an interesting or remarkable memory. In fact, I would guess that most people who grew up in the '90s and '00s have a similar one. The Simpsons, like Friends, and to a lesser degree like Sex and the City, has been a ubiquitous cultural force for two, maybe three generations. Those who remember a time when British TVs had five channels, when The Simpsons played at 6pm every day just before Hollyoaks, will probably see the American cartoon as a near-constant backdrop to their upbringing. Because even if you didn't watch The Simpsons yourself, their merchandise, their catchphrases, their games, their egg yolk-yellow faces, were everywhere. It was hard to go to a friend's house without seeing Homer bark "D'oh!" out the corner of your eye on someone's blaring TV screen.

In recent years, though, The Simpsons hasn't felt culturally pervasive in quite the same way. Viewers have complained that the animation has lost its charm since the '90s, relying on topical one-liners and excessive adventures rather than the creative absurdity it was loved for in earlier years. As well as that, young people aren't really watching traditional TV anyway, so there isn't that same endless familiarity that comes with consistently consuming one specific show.

That said, The Simpsons is far from dead. It is, in fact, very much alive and well on the internet, just perhaps not in the form it was originally intended. Today, the classic cartoon lives on via sad, relatable memes, surreal Instagram accounts, strange visual collages on YouTube and Tumblrs that post an endless conveyor belt of scene stills.

Scenic Simpsons, an Instagram account that currently has around 302k followers, is one of the most remarkable of these current day appreciations. Spliced together by an anonymous curator, the account posts abstract and beautiful stills from the cartoon, each without characters or context, and each depicting an illustrious landscape, a close-up of house interiors or an abstract snapshot in time. They're colourful, intriguing and very addictive. "All the posts come from series one - 10, which is generally known to real nerds as The Simpsons' golden era," the creator has said in an interview. "They changed the animation style up after that and it just doesn't have the same quality or colouring."

After the success of Scenic Simpsons, other, similar accounts starting popping up, such as Springfield Cuisine and Simpsons Library, each with their own aesthetic focus. It feels weird - appreciating The Simpsons for the way a cartoon moon hangs in a cartoon purple night sky, or how Marge looks beside eggnog, rather than its plot or jokes - but for a generation raised on the thing, it's like peering even closer, from an entirely different angle, through fresh eyes.

This isn't the only way The Simpsons is being channelled online in new, abstract ways. Simpsonwave, a subgenre of music (and I use that term in the loosest possible sense) has been around since the mid-2010s, and essentially constitutes a selection of heavily edited, purple-filtered Simpsons scenes on YouTube with a Vaporwave soundtrack. The result is like smoking a joint and diving into a swimming pool with The Simpsons projected onto the floor. It's ridiculous, sure, but it's also yet another example of how this deeply familiar cartoon has been pushed through so many layers of nostalgia, irony and refreshed appreciation that it's become more than a cartoon; it's an entity, an institution.

Lucien Hughes, the guy who has been credited with Simpsonwave, agrees that Simpsons nostalgia is pervasive and important for a certain generation. " The Simpsons is pretty unique in that it's something that almost everyone born between the late '80s and early '00s grew up watching," he explained in an interview with Pitchfork. "Vaporwave is very much about creating an atmosphere of nostalgia, so I feel The Simpsons just perfectly fits the whole aesthetic."

But really, The Simpsons has seeped into our visual and cultural lexicon in more general, overarching ways than these very specific instances that I've just mentioned. There isn't a day that goes by in which I don't see someone post a still of a Simpson on Instagram under the caption "mood" or see yet another relatable meme account dedicated to the cartoon ( Sad Simpsons Memes is my personal fave) or read people discussing how Lisa Simpson holds a special relationship with ambitious women worldwide or, as in a recent documentary called The Problem With Apu, how the cartoon has often missed the mark when it comes to inclusivity and wokeness.

There are so many Simpsons references scattered across the internet, in fact, that it often feels like a common visual language rather than a niche trend. It's been over 30 years since their first ever episode aired on December 17 1989, and maybe 10 years since a lot of people stopped watching, but The Simpsons has shaped its viewers in ways that are so deeply ingrained, so completely comprehensive, so absolute yet so subtle, that it's hard to articulate its influence in a way that gives it justice. We are, it seems, a generation who will simply never let go.
Follow Daisy Jones on Twitter. Enjoyed this article? Like Huck on Facebook or follow us on Twitter.

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Why is our generation refusing to let go of The Simpsons?

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Although the series might have lost its spark in recent years, we're still struggling to stop watching - and in some corners of the internet it's become an obsession that refuses to die. Although the series might have lost its spark in recent years, we're still struggling to stop watching - and in some corners of the internet it's become an obsession that refuses to die.

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the idea of cgi models is definitely bizarre - but the photographer who "created" her is white? this seems very inappropriate, especially in their descriptions/explanations? there's definitely a wider conversation to be had about how white creatives capitalize on blackness, and use it for their own benefit/fame

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We've become so accustomed to filters and false realities on Instagram that it can become difficult to tell what's even real anymore. We'd like to think we still have a firm grip on reality, but an Instagram model named Shudu has just thrown our entire universe for a loop.

Shudu is an Instagram model with flawless dark skin. Her feed is scattered with various editorial images accompanied by #melanin hashtags. She even was reposted on Fenty Beauty's Instagram account, wearing the lipstick shade Saw-C. Her beauty is so striking and unfathomably perfect that you almost don't want to believe it's real. The thing is, it's not-she's 100 percent CGI.

"Basically Shudu is my creation, she's my art piece that I am working on at moment," London-based photographer Cameron-James Wilson told BAZAAR.com. "She is not a real model unfortunately, but she represents a lot of the real models of today. There's a big kind of movement with dark skin models, so she represents them and is inspired by them."

Wilson was hesitant to confirm or deny Shudu's existence when we spoke with him on the phone this morning. After all, half the fun of creating art this life-like is to make the viewer reconsider their definition of reality. Her intent is not to fool or trick anyone, he says, but rather to be a beacon of inspiring beauty and creativity.

"I use a 3D modeling program. It's like virtual photography, so once I create her, I can kind of pose her in certain ways," Wilson explained. "I am a photographer anyway, so it's just a way of exploring my creativity when I'm not shooting." A single image, like the one seen on Fenty's Instagram, takes several days to create.

Shudu's striking beauty was actually inspired by a Barbie doll, called Princess of South Africa. "Obviously some models like Duckie were definitely big inspirations for her as well," revealed the photographer, who has also shot models like Gigi Hadid and Devon Windsor. It's worth noting that Fenty Beauty, who worked with Duckie on the brand's launch, only reposted the image of Shudu. We reached out for comment about whether or not they know about the model's computer-generated image.

The technology is undeniably cool, but does Wilson feel any heat for creating a black model versus just shooting with a real one? "As a photographer, I work with lots of different people all the time, real people that have inspired her. At the end of the day, it's a way for me to express my creativity-it's not trying to replace anyone. It's only trying to add to the kind of movement that's out there," he clarified. "It's meant to be beautiful art which empowers people. It's not trying to take away an opportunity from anyone or replace anyone. She's trying to complement those people."

Only a handful of people have turned his work into something negative, while most understand his intention, he said. "I am just a creative person, and to me she is what the most beautiful woman in the world would look like."

Shudu isn't the only computer-generated model on Instagram. Miquela, known as @LilMiquela, has 560,000+ followers who follow along as she models new clothes, takes selfies, and sells merch.

In an era where Facetuning and digitally-altered photos are the norm across social platforms, Wilson said he's simply bringing fantasy to reality.

"We live in such a filtered world now, where real is becoming fake. I wanted to create something that is fantasy toward becoming more real, and bringing it completely the other way."

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People Can't Tell If This Fenty Model Is Real Or Fake

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We've become so accustomed to filters and false realities on Instagram that it can become difficult to tell what's even real anymore. We'd like to think we still have a firm grip on reality, but an Instagram model named Shudu has just thrown our entire universe for a loop.

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This fall I went to a three-part class on weaving and coding to learn more about the intersection between materiality and cyberspace. I have no recollection of how I found it, specifically-it was part of one of those insomniac k-holes of Wikipedia entries and Facebook "Events You Might Like." I'd never clicked "Add to Cart" so fast on an event before.

It was part of Pioneer Works' Fact Craft programming, a series of events designed to examine how "facts" are constructed, disseminated, and stored. Other classes included Radical Memes, Rumour Bingo, and The Poetics of Archival Praxis. Weaving to Code stuck out to me because it was a combination of my favorite trades-fashion and technology.

I'm the child of a designer and grew up in engineering summer programs so this kind of pairing feels natural to me, a person who stole from my mother's wardrobe on my way to build a phone. I always wanted to learn more about fashion design but was never given the support to take classes on the subject, so I learned science by being forced. The great irony now is I love science and technology, for what it can do for fashion and identity-but it is only now, as an adult, that I get to explore both worlds at once.

Fashion and technology are constantly paired-see CHROMAT, Diane von Furstenberg's foray into Google Glass, Levi's Commuter Jacquard Jacket which syncs to your phone, and those corny Apple Watches we used to really want. What better way to understand their relationship possibilities than to learn the basic techniques used to create both? I learned a lot about the heritage of technology as feminine labor, about deconstruction and good design, about language as power. You see, we owe the structure of programming to crafts typically assigned to women-women were the first computer programmers. My notes, thematically and summarized:

Right before I started learning how to code I read the academic Carol Cohn's work about the language of nuclear war and how the world of defense technology is populated by men who speak in tongues. I wanted to learn code as a way of understanding them so I could protect myself from them, from what happened to them. I wanted to take this class to see where their worlds and mine-beauty and fashion-intertwine, and to see if there's something beautiful and worth working on in their mutual bond. Cohn's work explained why I felt this compulsion perfectly: "speaking the expert language not only offers distance, a feeling of control, and an alternative focus for one's energies; it also offers escape-escape from thinking of oneself as a victim . . . one goes from being the passive [sic] victim to the competent, wily, powerful purveyor. The enormous destructive effects become extensions of the self, rather than threats to it."

So much about programming seems to be about "safety" and control rather than connection now. And one of the failings of code is that too easily you can escape into the belief that you're in control if you know the language of the system. You can delude yourself into thinking you can run ahead of it. But people continuously build systems without realizing all the ethical implications of what can be done with them-they get away from you. In fashion, your body can't be discounted. You cannot escape the realities of your body, the limitations, the shape of it, the risks it takes and how it reacts to the clothes you put on. Code has no body, can be used by anyone with language of it, but fashion cannot. It will rip, or sag, and you will see the harm even if it is repaired carefully. Clothing is a narrator with limited resilience. In fashion your failings are physical, something I find oddly comforting.

"In fashion, your body can't be discounted."

We were given our own 3D-printed looms the first class and set to work on basic weaving routines. Plenty of people got experimental and weird with their first woven square. I did not. I like to perfect a practice before I go astray. One of the reasons I'm so fond of deconstruction as a fashion movement is that I know the pattern makers behind the most bizarre creations know how to execute their creations perfectly in a classic form-they exploit the limits of the rules and blow past them for surprising results. There's a quote from Ann Demuelemeester that explains this technique pretty perfectly:

"You can meet somebody in one of my jackets and it can all look a bit wrong, but also human and beautiful. Cutting nonchalance into a garment is difficult, because you can't just make an oversized or an asymmetric garment. It will look ugly. Making it look natural is delicate work. If it's too obvious, then it looks fake. Balancing the garment is a painstaking task, because you have to keep in mind how the clothes move."

It's why I'm not very interested in the newer 'avant-garde' designers who make unfinished asymmetrical dresses or absurdist, self-aware commentaries. I'm not at all convinced they actually know how to make their predecessors' work better, and there's a big difference between incompetence and experimentation. There's a difference between failing upwards and operating on a bluff.

So while my classmates make admittedly much more interesting designs than I do, they often stop halfway through and have no idea how to replicate their work or fix particular parts. I might start off my patterns and grid very simply but I'm building, learning the structure and figuring out exactly when and where I have to focus when I see an imperfect knot. I learned how to debug by weaving a fabric swatch. In the second class, we began to teach each other tricks we all learned through stumbling and observing each other's work.

When we were eventually tasked with translating a weaving pattern into a JavaScript code, I ended up making a matrix where the colors kept changing like my favorite duochrome silk, a common material for Eckhaus Latta and Phlemuns. I just kept changing numbers for the processing loop to make the material 'move.'

One of my teachers has done work that showed coding and weaving as sisters in translation. Francesca Rodriguez Sawaya's work translates spoken word into textile by converting audio patterns into weaving designs she then physically wove. She wanted to bring back the human element to textiles that have been lost in automation. She wove cadence and frequency into a pattern; she wove stories into material to hold. I wonder what pattern my favorite Anne Carson poem would end up looking like. I have no doubt designers are poets. Remember the sheer gowns from Ann Demeulemeester? The locks of hair McQueen sewed onto his work? The Junya Watanabe menswear printed with poems? The tags of Hussein Chalayan clothes?

The bridge between material and code isn't Sawaya's work alone, or any of these designers. It's the basis of computer technology itself. This is what we learned the second class. The jacquard loom, you see-the invention our 3D loom was based off of-is also the basis of the matrix of Java. The jacquard loom was the first to store its own information through punch cards strung together used for automatic thread selection. It was the inspiration behind the Analytical Engine invented by Charles Babbage, sometimes known as "the father of computing" for his Difference Engine. He imagined the Analytical Engine as a textile mill; he even had a woven portrait of Jacquard in his studio as he worked on his approach at a computer with the help of his assistant, Ada Lovelace. Ada's research and proposals on the analytical engine were the founding notes on what would much later be used to create the first American computer-IBM's Automatic Sequence Controlled Calculator. The Analytical Engine was never fully built.

After my last class I went to visit the artist Pamela Liou, a former jewelry designer who build her own open source jacquard loom using IC3 chips and a 3D printer. Fun fact: IC3 chips were first used in guided missiles. A closed loop-from weaponry back to clothing looms. When I asked her about her world of fashion and programming, she crystallized a lot of what compelled me to take classes at all:

"I feel like the fashion world and women at large could benefit from the lessons of open source, the idea that we're greater the more we share with each other. I wanted to do the loom because I was really frustrated with my own lack of access to something that I wanted. And it made me think about craft differently. The jacquard loom is sort of the symbol of displacement of craftspeople, but I see it as an opportunity to upchange craft. Machines can be idiosyncratic, they can have personalities, it can be tooled for one specific weird thing and it doesn't have to be the lowest common denominator appliance. It can be meditative for your own state of mind, rather than eking out every ounce of productivity from you. Having an intimate relationship with tools can and should be part of the craft. Many people want more clinical perspectives but this loom is the opposite: it embraces materiality, chaos and eccentricity."

Even if our present feels more and more like a dystopia we can't wake up from, I stubbornly believe in joyful rebellion and collaboration within it, weird deviations from a path we can't seem to stop running down to our mutual doom. I used to be scorned in engineering classes for caring so much about clothes, and no one in fashion circles cared much about tech unless it came with an Apple logo.

Hybridity is the only form of freedom that I can ever see. I still believe that freedom means sharing everything we can give and make each other, whether that's in the form of clothing we can wear or in open sourced code. There's a quote from Sara Ahmed's The Promise of Happiness that is a guiding concept for me, on freedom and possibility: "The future is not given content, it is not the overcoming of misery, nor the future as being happy. The future is what is kept open as the possibility of things not staying as they are."

Arabelle Sicardi is a beauty and fashion writer. They have work in i-D, Allure, TeenVOGUE and more.

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This fall I went to a three-part class on weaving and coding to learn more about the intersection between materiality and cyberspace. I have no recollection of how I found it, specifically-it was part of one of those insomniac k-holes of Wikipedia entries and Facebook "Events You Might Like."

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twitter aka one of the most popular apps in the world has only JUST made a profit?!??

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Social media company makes $91m profit in fourth quarter of 2017 on revenue of $732m

Twitter has posted its first quarterly profit in the company's 12-year history, although a clampdown on fake accounts meant it lost users in the US and overall user growth stalled.

The San Francisco-based social network, which went public five years ago, made a profit of $91m (£65m) in the fourth quarter of 2017, compared with a $167m loss a year earlier, after cutting costs.

It also returned to revenue growth as video ad sales rose, with revenue up 2% year on year to $732m. Twitter's annual loss shrank to $108m from $457m in 2016. It expects to make its first annual profit this year. Shares jumped more than 20% on the news.

However, the site favoured by Donald Trump, celebrities and politicians struggled to increase user numbers, despite the publicity created by the president's frequent tweets. In a letter to shareholders, Twitter said it had stepped up efforts to reduce spam, automated accounts known as bots and fake accounts.

The company had 330 million monthly active users in the quarter, up 4% year on year, but growth stalled compared with the previous quarter. The number was below the 332.5 million expected by Wall Street. A change that Apple made to its Safari web browser reduced the tally by 2 million.

Strictly defined, a Twitter bot is any automated account on the social network. That can be something as simple as automatically tweeting links to news articles - most of the Guardian's social media accounts are technically Twitter bots, for instance - to complex interactions like automatically generating Emoji-based art or automatically replying to climate change deniers with scientific evidence.

But, as with "troll" and "fake news", the strict definition has been forgotten as the term has become one of political conflict. The core of the debate is the accusation that a number of political tweets were sent by "Russian bots", with the intention of subverting political debate, or simply creating chaos generally.

Based on what we know about Russian information warfare, the Twitter accounts run by the country's "troll army", based in a nondescript office building in St Petersburg, are unlikely to be automated at all. Instead, accounts like @SouthLoneStar, which pretended to be a Texan right-winger, were probably run by individuals paid 45-65,000 rubles a month to sow discord in Western politics.

In other ways, they resembled bots - hence the confusion. They rarely tweeted about themselves, sent far more posts than a typical user, and were single-minded in what they shared. People behaving like bots pretending to be people: this is the nature of modern propaganda.

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In the US, where Twitter makes most of its revenue, the number of users dipped to 68 million from 69 million in the third quarter.

The network faces tough competition from bigger rivals such as Facebook, which has 2.1 billion monthly users, along with more recent arrivals including Snapchat and Instagram.

Twitter has introduced measures to tackle abuse and has said that it "cares deeply" about misinformation and its harmful effect on civic discourse.

But Michael Connor, whose Open Mic group recently helped two large Twitter and Facebook shareholders file resolutions asking the companies to take more responsibility for fake news, abuse and hate speech, said Twitter was not doing enough to address these issues.

"They are playing whack-a-mole with these problems," he told AP. "They say they have the problem under control, but they don't know what the problem is exactly."

Twitter's chief executive, Jack Dorsey, has in the past year tweaked the product he co-founded to attract more users. Twitter doubled the number of characters allowed in each tweet in most languages, from 140 to 280. It also signed deals with media companies to live-stream news, sports events and entertainment shows.
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Twitter makes first quarterly profit in its history

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Social media company makes $91m profit in fourth quarter of 2017 on revenue of $732m Twitter has posted its first quarterly profit in the company's 12-year history, although a clampdown on fake accounts meant it lost users in the US and overall user growth stalled.

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Selfies have become the catchall term for digital self-portraits abetted by the explosion of cellphone cameras and photo-editing and sharing services. Every major social media site is overflowing with millions of them. Everyone from the pope to the Obama girls has been spotted in one. In late August, Oxford Dictionaries Online added the term to its lexicon. One of the advertisements for the new Grand Theft Auto V video game features a woman in a bikini taking a photograph of herself with an iPhone. In a recent episode of Showtime's "Homeland," one of the main characters snaps and sends a topless selfie to her boyfriend. Snapchat, a photo-based messaging service, is processing 350 million photos each day, while a recent project on Kickstarter raised $90,000 to develop and sell a small Bluetooth shutter release for smartphones and tablets to help people take photographs of themselves more easily.

It is the perfect preoccupation for our Internet-saturated time, a ready-made platform to record and post our lives where others can see and experience them in tandem with us. And in a way, it signals a new frontier in the evolution in social media.

"People are wrestling with how they appear to the rest of the world," Mr. Thompson said. "Taking a photograph is a way of trying to understand how people see you, who you are and what you look like, and there's nothing wrong with that."

At times, it feels largely performative, another way to polish public-facing images of who we are, or who we'd like to appear to be. Selfies often veer into scandalous or shameless territory - think of Miley Cyrus or Geraldo Rivera - and at their most egregious raise all sorts of questions about vanity, narcissism and our obsession with beauty and body image.

But it's far too simplistic to write off the selfie phenomenon. We are swiftly becoming accustomed to - and perhaps even starting to prefer - online conversations and interactions that revolve around images and photos. They are often more effective at conveying a feeling or reaction than text. Plus, we've become more comfortable seeing our faces on-screen, thanks to services like Snapchat, Skype, Google Hangout and FaceTime, and the exhilarating feeling of connectedness that comes from even the briefest video conversation. Receiving a photo of the face of the person you're talking to brings back the human element of the interaction, which is easily misplaced if the interaction is primarily text-based.

"The idea of the selfie is much more like your face is the caption and you're trying to explain a moment or tell a story," said Frédéric della Faille, the founder and designer of Frontback, a popular new photo-sharing application that lets users take photographs using both front- and rear-facing cameras. "It's much more of a moment and a story than a photo." And more often than not, he added, "It's not about being beautiful."

In other words, it is about showing your friends and family your elation when you're having a good day or opening a dialogue or line of communication using an image the same way you might simply text "hi" or "what's up?"

And selfies strongly suggest that the world we observe through social media is more interesting when people insert themselves into it - a fact that many social media sites like Vine, a video-sharing tool owned by Twitter, have noticed. Dom Hofmann, one of the founders of Vine, said the first iteration of the application didn't let people shoot videos using the front-facing camera, partly because of technical constraints. His co-founder, Rus Yusupov, was in favor of adding the feature to the service, but Mr. Hofmann had concerns that it might denigrate the quality of the content people were sharing through the service.

"Rus felt that it would open up a lot of creative possibilities," said Mr. Hofmann. "But I thought it would be a lot of vanity. I didn't see much value in it."

But after some discussion, and repeated requests from users, the company decided to release the front-camera capability as an update. It turned out that his partner was right. Users loved it, Mr. Hofmann said.

"It wasn't really about vanity at all," he said. "It's not really about how you look. It's about you doing something else, or you in other places. It's a more personal way to share an experience."

The feedback loop that selfies can inspire doesn't hurt, either. As an early Instagram user, I rarely turned the camera on myself. I preferred sharing pictures of sunsets, crazy dance parties and bodega cats to showing off a new haircut or outfit. But over the last year or so, I've watched as all my peers slowly began turning their cameras inward on themselves. It's made my feed more interesting and entertaining. And I'd much rather see my friends' faces as they prepare food than a close-up photo of the finished meals instead. The rare occasion when I feel bold enough to post a full-face frontal, I see spikes in comments and feedback, the kind that pictures of a park or a concert photo rarely get.

In fact, I've even noticed that the occasional selfie appears to nudge some friends who I haven't seen in a while to get in touch via e-mail or text to suggest that we meet for a drink to catch up, as if seeing my face on a screen reminds them it's been awhile since they've see it in real life.

Dr. Pamela Rutledge, director of the nonprofit Media Psychology Research Center, says that's how the human brain works.

"We are hard-wired to respond to faces," she said. "It's unconscious. Our brains process visuals faster, and we are more engaged when we see faces. If you're looking at a whole page of photos, the ones you will notice are the close-ups and selfies."

As for the well-worn assertion that selfies foster vanity and somehow court stalkers, "There are some people who put themselves at a certain amount of risk by exposing too much," Dr. Rutledge said. "But that's not about the selfie. That's about someone who is not making good choices."

Rather than dismissing the trend as a side effect of digital culture or a sad form of exhibitionism, maybe we're better off seeing selfies for what they are at their best - a kind of visual diary, a way to mark our short existence and hold it up to others as proof that we were here. The rest, of course, is open to interpretation.

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Selfies have become the catchall term for digital self-portraits abetted by the explosion of cellphone cameras and photo-editing and sharing services. Every major social media site is overflowing with millions of them. Everyone from the pope to the Obama girls has been spotted in one.

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Let's face it: Facebook is boring. My feed is a steady stream of mundane, predictable updates from former acquaintances and networks I'm no longer connected to. It's the same vacation photos I already saw on Instagram and the same news stories that broke on Twitter two days ago.

So I gave it a massive overhaul.

I've spent the last few weeks joining the strangest, most interesting and unexpected Facebook groups I could find, and they've completely transformed my feed. It's now filled with delightfully absurd jokes and stories I would have never found elsewhere. (I recently opened my app to find screenshots of people posting "I like to fish" on the Walmart Facebook page.)

Welcome to the Facebook underground - a hidden network of meme communities and affinity groups that may just be the future of the social network as we know it. It feels like I've settled in a whole new world - and Facebook is betting that you'll want to travel there, too.

"Weird Facebook" is here to stay - and it's getting political

Weird Facebook, kind of like Weird Twitter, is the unofficial term for offbeat, absurdist, ironic Facebook posts and groups, most of which center on shared memes. "If David Lynch and Yung Lean could project their consciousnesses into social media, it'd be Weird Facebook," Jordan Pedersen wrote for the Daily Dot in 2014.

Then came the rise of Leftbook. This is a relatively new term: It's what people call the politically progressive side of Facebook. There's a strong overlap with Weird Facebook. Most, if not all, of the popular groups I'm in would be considered both Weird Facebook and Leftbook.

Almost all of the groups I've joined make you answer politically charged questions before you're admitted. Even if the group doesn't seem political on its surface, it's likely part of Leftbook.

Almost all of the groups I've joined make you answer politically charged questions before you're admitted.

For example, here's the question form for a page called "That's not Jim, that's Butch the bigot." Questions about gender and reverse racism are meant to weed out old-fashioned beliefs.

Wait, who's Jim? Who's Butch? And what about Bob?

As you get to know Weird Facebook, you'll see these names everywhere. "Butch the bigot," seen above, is a spinoff group from " Please show to Jim ! ! HA ! ! HA ! !," which is specifically for sharing things "normies" post on Facebook. The group has a language of its own, referring affectionately to people who don't quite understand social media as Jims and Jimettes.

The group " That's not Jim, that's Butch the bigot" is for posts that are less awkward and more racist, and " THIS is not Jim,,it's Bob " is for posts that are sexually aggressive.

Got that? Jimette is your aunt who's new to the internet; Butch is your Alex Jones-quoting uncle-in-law; Bob is the creepy dude you graduated from high school with.

In many of the groups I'm in, people share and critique posts from elsewhere on social media. Those include " I don't think that's science," " sounds fake but ok," " it turns out you can just put words in any order you want" and " i feel personally attacked by this relatable content." Others are related to a specific interest, like "," a group for listeners of the podcast of the same name, and " Dogspotting," a place to post photos of dogs you see around.

The best part? Many of these groups are private.

The joy of a closed Facebook group (meaning you have to be approved before joining) is that it feels like a safe space - kind of like the "" phenomenon on Instagram. People are more likely to be their authentic selves, according to several people I spoke with.

Bonnie Grace, who lives in Australia, is a 31-year-old admin for a Facebook group called " Is This How You Flirt?." It's "where people post screenshots of their awkward attempts at online flirting," she told me. "It has grown from about 1,000 to 10,000 members in about a month. It was fascinating to see it change so much and so quickly."

"Groups completely changed my experience of Facebook," Chad Niel, a 33-year-old from Salt Lake City, Utah, said in a phone call. "I think one of the things is that you kind of interact with strangers in a different way than you interact with strangers normally or even on your own personal Facebook page. It's more uninhibited. I wouldn't go around telling random strangers about some anxiety issue that I'm having, but I'll easily tell a random Facebook group." Niel is an admin of "That's not Jim, that's Butch the bigot."

"It's a much broader, more uninhibited way to connect with people," Niel said. "You connect with people at a realer level. ... I think people get to see a side of you that, unfortunately, you don't often project to the world."

Groups are all about authentic connection on an aging network where communication often feels forced and performative. And that's why Facebook recognizes its potential to keep even more users engaged - and make some money, too.

Facebook is investing big in groups

Back in 2014, when Weird Facebook started to thrive, the company wasn't doing much to publicize its strange but popular new batch of groups. Now, Facebook's going all-in.

In June, Facebook held its first Communities Summit in Chicago. At that summit, CEO Mark Zuckerberg made it clear to attendees that the site plans to prioritize groups. It introduced new tools for group administrators and moderators and announced that more than half of Facebook's users are involved in groups. Of course, the company is also figuring out how to monetize the changing network, creating targeted advertising specifically for groups.

Groups are all about authentic connection on an aging network where communication often feels forced and performative.

It may be telling that the simple act of joining a group tends to trigger Facebook's algorithm to feature that group's content so prominently. For me, group posts have replaced virtually everything else.

But the Leftbook and Weird Twitter devotees I talked to didn't seem to notice or be bothered by Facebook's attempt to take groups mainstream. They're just in it for the fun - and maybe to make some friends.

Groups have changed the way people use Facebook

It's not uncommon for people to make friends within Facebook groups that lead to offline relationships.

Joy Hayward, a law student in the U.K., met her current boyfriend in a Facebook group. They haven't met in real life yet, but she's planning to fly to the U.S. to see him in a few months.

It's not all fun and games, though. There can also be serious in-fighting in groups. "While Facebook groups can be a lot of fun, and definitely helped me make a bunch of friends, I've seen people have their lives pretty much ruined over political differences - people harassing them, calling their employers to try and get them fired, messaging their family members, etc.," Hayward said. People have called her names, spread nasty rumors about her and banned her from groups, she said.

Joy Hayward, a law student in the U.K., met her current boyfriend in a Facebook group. They haven't met in real life yet, but she's planning to fly to the U.S. to see him in a few months.

Despite the negativity, it's clear these groups have changed the way people use Facebook, and they don't plan on going back.

"I don't really use Facebook for its intended purpose anymore - I don't post pictures that much or message others," said Whitney Williams, an 18-year-old from Louisiana. Williams is an admin of " and then everyone stood up and clapped. " She continued, "I really just use it for the groups!"

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There's an underground, alternative Facebook that you never knew existed

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Let's face it: Facebook is boring. My feed is a steady stream of mundane, predictable updates from former acquaintances and networks I'm no longer connected to. It's the same vacation photos I already saw on Instagram and the same news stories that broke on Twitter two days ago.