# data[].attributes.attachment_link.readable_text
Uber employees are feeling better about their employer and their own work, according to a new leaked employee survey.

The poll is conducted every six months and this latest one is from October, according to Business Insider, who first reported on the leaked answers to 35 questions the workers answered. The results are favorable/positive, neutral or negative and the responses are compared to those from the previous employee survey.

For example, of the 18,648 Uber employees who participated in the poll, here's the percentage that answered the following questions favorably, according to Business Insider:

I believe that Uber is in a position to succeed over the next two years -- 83 percent

I feel heard by my manager -- 73 percent

I feel secure about my job -- 66 percent

I feel fairly treated -- 63 percent

Uber acts in a socially responsible way -- 63 percent

I feel the work I'm doing is meaningful and impactful -- 63 percent

I have access to the learning and development needed to do my job well -- 60 percent

I feel excited to come to work every day -- 58 percent

I see myself working at Uber in two years' time -- 56 percent

I am able to manage my work stress in a healthy way -- 56 percent

Even if offered a competitive offer or external career opportunity, I would choose to stay at Uber -- 45 percent

I believe my total compensation (base salary, bonuses, benefits, equity) is fair, relative to similar roles at other companies -- 40 percent

More: More: More: After 3 years of price increases, gas is getting cheaper in 2019 7 smart ways to save money, cut expenses from your budget in 2019

I am passionate about Uber's mission -- 77 percent

I feel I can report ethical or compliance violations without fear of retaliation -- 71 percent

I have seen positive culture change take place at Uber over the past six months -- 62 percent

As 2018 winds down, here are some of USA TODAY's favorite video games of the year
All those positive replies were up from the previous survey.

But some questions posed to employees garnered fewer positive responses than they did last time, Business Insider reported:

Uber did not respond to requests for comment.

The company behind the popular ride-hailing app has previously come under fire from employees who feel they aren't paid well enough.
Follow USA TODAY reporter Zlati Meyer on Twitter: @ZlatiMeyer
Also casting a shadow were allegations that Uber was a toxic work environment for women and that some of its aggressive business tactics may have been illegal. Amid that, co-founder and CEO Travis Kalanick resigned in June 2017.

And this summer, Reuters reported that Uber employees of color complained that the company's human resources department head, Liane Hornsey, and her staff ignored reports of racism. She quit abruptly after an investigation.

Uber is poised for an initial public offering that some estimates put as high as $120 billion, placing it in a race with Lyft to be the first ride-hailing company to go public.

# data[].attributes.attachment_link.title
Uber employees' feelings about the company revealed in leaked worker survey

# data[].attributes.attachment_link.description
Uber employees are feeling better about their employer and their own work, according to a new leaked employee survey. The poll is conducted every six months and this latest one is from October, according to Business Insider, who first reported on the leaked answers to 35 questions the workers answered.

# data[].attributes.attachment_link.readable_text
Courtesy of James Farrar

Uber drivers in Europe and the U.S. are fighting for access to their personal data. Whoever wins the lawsuit could get to reframe the terms of the gig economy.

Over two years of driving for Uber, James Farrar logged thousands of miles on the app. Many weeks, he'd work more than 80 hours behind the wheel of his Ford Mondeo, crisscrossing the streets of London deep into the night. Along with passengers, Farrar was collecting data.

During his time in the car, Uber's app recorded where he went, how long he stayed, how much money he made, and how many stars he was given by his passengers. It noted how many rides he accepted and how many he cancelled, mapped where trips started and ended, and how long it took him to wind through traffic to get there as he followed the algorithmic cues nudging him around the city.

Being an Uber driver, Farrar found, did not agree with him: "[L]ife behind the wheel," as he wrote in a recent op-ed for the U.K. Independent, "can become a blur of endless traffic, crushing loneliness, enduring fatigue and relationships strained by absence." And he grew frustrated by the way the app always seemed to be pushing him to accept more rides, while his earnings kept declining. In 2016, he and another London Uber driver, Yaseen Aslam, brought a worker's rights claim against the company, arguing that drivers aren't true independent contractors and should instead be classified under the U.K.'s third employment category of "worker"-entitling them to minimum wage and paid vacation days. Farrar's team won the classification case.

But during the trials, Uber was able to use Farrar's personal data as legal ammunition against him, he said; the company argued that the reason he made under minimum wage some days was because he'd declined several rides, not because he was being fleeced by the app. "I decided then that I needed to see all my data," Farrar told CityLab in an email. "[S]o I could properly assert my rights and eliminate the asymmetry in information power between me and Uber."

Uber appealed, arguing, as it long has, that it merely connects independent entrepreneurs with riders, and that a change in classification would impede drivers' freedom. (A judge said that the wording of Uber's contract, which makes the same claim, contained a "high degree of fiction.") Still, one judge out of three backed the company, and Uber was given permission to bump the trial up to the U.K.'s Supreme Court.

With the support of Ravi Naik, the lawyer who is also representing plaintiffs in data privacy cases against Facebook and Cambridge Analytica, Farrar and three other drivers have bundled their data requests, eking out more information with each challenge. This March, they filed a lawsuit against Uber for withholding some data, which they say is in breach of theEuropean Union's General Data Protection Regulation (GDPR). This law gives E.U. citizens the right to request any and all personal data that a platform retains about them.

Cities are changing fast. Keep up with the CityLab Daily newsletter.

Though he says he's not "anti-Uber," Farrar's labor rights activism has accelerated: In 2017, he helped found and became the chairman of the United Private Hire Drivers branch of the IWGB union, which represents more than a thousand workers for private hire companies. And as of this summer, he has pushed more than 60 other drivers to file similar data claims. Now he's pooling their information online as part of an organization he founded and directs called the Worker Info Exchange. Since Uber arbitrates cases from all its worldwide markets besides North America in Amsterdam, an E.U. country, these GDPR-based claims could be replicated in dozens of countries.

With that aggregate, he wants to determine definitively how much (or little) drivers make for their time-and how an over-supply of temporary drivers has saturated the market with idling cars. "The negative effects of these apps are congestion and poverty, and we need the data to show that," Farrar said.

This tension isn't an entirely new one. Mounting evidence suggests that all kinds of apps, from the Weather Channel to the selfie-filtering Perfect365, have habitually scraped location data from phones and used it to better predict consumer buying habits. And Uber's tight grip on information is part of a long pattern for the ride-hailing titan, which has often tangled with local regulators over its vast trove of trip data. But Farrar believes that whoever gains access to Uber's complete data caches will find something bigger than just tools for better traffic management: It might be the key to creating a more equitable gig economy. And Farrar is prepared to wage a years-long legal battle to ensure that drivers are the ones to get it.

Who's the algorithmic boss?

For ride-hail companies, the hunger for information is clear: Uber uses real-time location data to route drivers more efficiently through the city, and could eventually feed the troves of geographical knowledge to a fleet of self-driving cars. When collected, aggregated and made available to a broad community of drivers, however, it could help them make smarter decisions about how and where to drive. And in the hands of city governments, it could inform transportation and labor policy-making. In New York City, it was detailed trip data that helped them craft the U.S.'s first ride-hail minimum wage, for example, and a cap on ride-hail licenses.

The "Request to Begin" file. Green represents the location of the car at request, orange is the pick-up point, and red the destination. (Courtesy of James Farrar)

There's a variety of trip and payment info already available to drivers through their apps, like when they logged on and off, where they picked up and dropped off drivers, and how much they made per mile versus what Uber made in commission. And not all drivers want (or need) any more than that. "I know when to work [and] how to work, because I've been doing it for four years," said Bill Steigerwald, a former journalist and Uber driver based in Pittsburgh. "I'm not sure if there's anything that Uber could tell me that would help at all. I feel like I know this market better than Uber does."

But from Uber's disclosures so far, Farrar has already found much more: Along with the trip history, he has cumulative GPS data. He also has dispatch data, and details about how "productively" he spent his time on the platform, either waiting for work, traveling to pick up a passenger, or carrying out a fare-paying trip. These last points will prove important, he says, because in its 2016 ruling, the court decided drivers should be considered protected workers from the moment they log in to the platform until the moment they log off.

"Once we win in the Supreme Court-and I believe we will-then the case will be kicked back down to Tribunal level where we and Uber have to calculate what is owed," Farrar wrote in an email. "It is at this point having our own view of the data will be key."

Every trip Farrar has ever taken. (Courtesy James Farrar)

There's still more informationout there, though: Uber hasn't published the GPS data it collects from drivers while they're not completing a trip (so-called "dead time"), or the driver profiles that Farrar thinks Uber culls from customer service interactions and trip history. ("The only profiles we have for drivers are those visible in the driver app and the rider app," an Uber spokeswoman said in an email. "This information is always available to drivers in the partner portal, regardless of GDPR.") The company has held riders' ratings and reviews tightly, too, citing privacy concerns. Drivers are given a recalculated average rating at the end of each day, but they don't have a granular sense of what went wrong, when.

Having the ratings data could support Farrar's case that Uber performance-manages its drivers, he says. Though the Uber spokeswoman said that "[d]rivers are contacted directly if their rating falls below the average for their city so they have a chance to adjust their behavior BEFORE a deactivation," several drivers have reported being deactivating from the platform without clear warning or explanation, or believe they've been sent fewer ride-requests as a result of perceived poor service. If proven, Farrar thinks it could be evidence that drivers are actually controlled by the platform via "algorithmic bosses," as tech ethnographer Alex Rosenblat writes in her book Uberland.

"Uber is trying to avoid any sign that they might be managing people or this might be an employment relationship," said Farrar. "They want to avoid saying they're dismissing you because you're not doing the job right."

Uber says they've released all the data they can and are mandated to. "Our responses have been within the guidelines published by ICO (UK data authority) and we've provided millions of lines of data in response to these requests as well as detailed explanations on why we cannot provide some of the specific data he requested," an Uber spokeswoman told CityLab in an email."[E].g. some of it never existed in the first place and some of it can't be shared without infringing on the rights of other individuals."

(There's disagreement about whether gig workers have the same kind of data-access rights that other users of a digital platform would under GDPR, because the lines between personal information and proprietary business intel are blurred, as The Economist reported this May.)

Even millions of individual data points won't be enough to truly articulate how Uber controls its drivers' movements, says Uberland 's Rosenblat, because the logic of the algorithms that nudge them is always changing and recalibrating.

But for drivers, Farrar says getting a peek under the hood of the Black Box could spark a U.K. labor revolution. What happens when drivers are confronted with how much they're owed in back holiday pay, for example? And for policymakers, Rosenblat says it could give them a clearer understanding of the outcomes of those automated decisions, however dizzying-and a chance to legislate accordingly.

"Right now, so much of this discourse happens in a data vacuum," Rosenblat said of the international debate over gig worker treatment. While Uber and Lyft can selectively deploy their own in-house data to fit narratives they like, she says, politicians and organizers are left clinging to what seem like feelings, or individual's anecdotes.

"Almost everything we get from companies ... [has] been shaped with lawyer's inputs, to make sure that it tells only half the story or a quarter of a story, or only the story an employer wants to tell," said Bill Sokol, a labor lawyer that practices in the Bay Area.

But harder, and more complete, information does exist, as efforts like Farrar's show. It's just locked up.

From the driver's seat

In the U.S., the question of how to classify gig workers has also preoccupied lawmakers. California is currently debating Assembly Bill 5, a controversial piece of legislation sitting in California Senate committees that could redefine ride-hail drivers as full employees. Uber and Lyft, along with some drivers and union leaders, have raised concerns about what the bill might mean for driver flexibility.

But establishing stronger labor protections is not contingent on transforming employment status: After Uber and Lyft went public this spring, and ride-hail drivers organized local and international strikes in response, increasing wages-and wage transparency-has become an urgent priority.

What's different in the U.S. are the mechanisms by which people can gain access to their data. Because the country isn't covered by GDPR, individuals can't make piecemeal data requests like Farrar's. In cases where data has been unearthed, it's generally been in bulk, under pressure from citieslike New York.

Farrar's full GPS data, represented according to speed. Lighter colors denote higher speeds; darker reds are slower. (Courtesy of James Farrar)

Other times, companies have proactively released limited amounts of data, both to justify their expansion and to assist with local initiatives. Uber Movement, a data-sharing partnership between Uber and dozens of cities around the world, launched in 2017; it features visualizations of travel times and traffic speeds, and little else.

But there are also a few U.S. efforts to enhance drivers'-and cities'-ability to collect that information themselves, without having to rely on company disclosures. This year, a consortium of cities banded together to launch an open-source data project called Mobility Data Solutions (MDS), which allows cities to collect their own real-time info on scooter and dockless bike trips. Uber, Lyft, and Bird are supporting a bill to block it, citing fears that the data would not be stored securely. Many transportation experts believe those privacy concerns are valid, as my colleague Laura Bliss reported; others think the companies are acting in their own interest, which is to keep cities in the dark.

The Driver's Seat Cooperative offers another, more personal, solution. The app, which is still in its beta version, allows ride-hail drivers to turn on a Waze-like GPS system that runs in the background while they work, recording their location. That data will then be aggregated, anonymized, and shared with a cooperative made up of participating drivers. Co-founders Matt Schumwinger, a former data consultant, and Hays Witt, a former organizer with the Partnership for Working Families, promise that drivers in the co-op will be able to be compensated for their industry insights, as well: Cities will be able to buy that data, and drivers will share in the revenue.

Witt, like Farrar, wants to use the information to help drivers earn more stable incomes,and cities craft more well-informed policies. "I heard from drivers that one of the key issues was they didn't have good information that they could use to plan their day or make business decisions," he said. "And at the same time, we were hearing from cities and municipalities that they were interested in improving ride-hail both for drivers and in communities they're accountable to, in terms of providing quality efficient equitable transportation, and that they were unable to get the data they needed to do that."

San Francisco is the Driver's Seat Cooperative's first local partner. Data from the group (accessed for free in its beta mode) will help San Francisco's Local Agency Formation Commission (LAFCO) conduct a study on the state of the city's gig economy. The effort is led by Bryan Goebel, LAFCO's executive officer, who spent a stint working for on-demand delivery apps after a career in transportation journalism. "Having struggled with this kind of work over the past year, I was like, well, we don't really have data," he said. "I'm trying to figure out how can we work with companies, how can we amplify the voices of on-demand workers and find some solutions. Data is part of that."

Goebel isn't working towards a specific policy outcome like a city-wide ride-hail minimum wage, though he won't rule it out. He says the goal is to "better understand the geography of on-demand workers ... and provide some additional data on what their days are like." How many hours do they work? How much money do they make? Do they travel by car or by foot or by bike, as Goebel once did, sweating as he crested the San Francisco hills? How has their experience changed over time? Once the study is complete, he'll deliver it, along with a set of recommendations, to the San Francisco Board of Supervisors, who will decide what to do next.

The price of data

Uber and Lyft drivers often talk about ride-hailing work as a game; each day, they chase surges and pursue rewards. Harry Campbell-the blogger, YouTuber, podcaster, and former driver known as The Rideshare Guy -has built a media empire guiding drivers how to work smarter, not harder.

In a way, the gamification of the app makes the tasks feel self-directed, as a recent paper argues. Katie Wells, a postdoctoral research fellow at Georgetown's Kalmanovitz Initiative for Labor and the Working Poor, and co-authors Kafui Attoh of the CUNY School of Labor and Urban Studies and geography professor Declan Cullen interviewed 40 Uber drivers in D.C. for a series of reports on how the on-demand economy affects workers, concluding, among other things, that the nature of the work breeds isolation. (Uber has taken issue with some of their findings for drawing on interviews conducted in 2016, before the company rolled out in-app tipping and an Uber Pro rewards system.)

As gig economy worker and researcher Sarah Mason argues in her Guardian essay, " High score, low pay: why the gig economy loves gamification," Uber also deftly translates that "desire towards the production of profit for the employer." Swap data in for profit-it's easy to do, because one is easily converted into the other-and you have a more comprehensive picture of what driver labor really looks like, according to Wells. Idling, re-routing, and cancelling rides may not make drivers any money under the current system, but it gives Uber valuable info on what routes and times of day drivers prefer.

"[W]e're their guinea pigs now," said Joe, a driver Wells and her co-authors interviewed in 2016, whose name was changed to protect his livelihood. "We're building that data for them, and they have it."

It's challenging to determine how companies should compensate for that extra labor, Wells says, or to say if they even should. What's important is to start recognizing the processes-and the people-behind data collection, especially as the promise of the ultra-optimized Smart City gets closer to reality. "How could it be bad to know more?" said Wells. "The question is, how do we come to know that thing?"

Witt, too, says he's wary of commodifying individual data points, instead stressing the more meta potential of data ownership and production. He wants to compensate drivers for the data they collect through the Driver's Seat Cooperative, but his ultimate goal is to use it in a way that benefits the profession as a whole. "The value in the aggregate is much greater than the sum of its parts," says Witt. "What's really important is that people are thinking about how drivers can share in that value."

Having the ability to shape city policy is one value proposition; gaining the same level of control as a true entrepreneur would is another. Drivers might not feel like guinea pigs if they, too, got to wear the white coats every once in a while.

Recommended

It can also correct for the ways Uber and Lyft already deploy data, which is more strategic. "Platform companies give platform workers views of their own data that are designed to incentivize and spur specific behavior," said Witt. They'll tell drivers how many more rides they'll have to complete before earning a bonus, for example.

These limited disclosures encourage them to stay on the platform longer, and direct them "to work in ways that are inherently isolating and that function to undermine anything approaching collective (whether that action involves a collective appeal for higher wages, or safer working conditions)," as Attoh, Cullen, and Wells write.

But in different hands, data could also break down those silos. For one thing, organizers could use it to strategize about which drivers to bring into their meetings, says Sokol, the labor lawyer. "If you can create an app that actually generates what I would call good evidentiary proof of those who are really employees doing the work on a regular full-time basis, versus those who are simply casual or part-time employees ... you would basically know who is it you're trying to organize," he said.

It could also push both full and part-time drivers to feel engaged enough to act. "The most important power workers have isn't always through the court, but through direct action-through strike and protest organizing," says Farrar. "The data helps unlock that energy."

About the Author

# data[].attributes.attachment_link.title
This Uber Driver Started a Legal Battle That Could Upend the Gig Economy

# data[].attributes.attachment_link.description
Over two years of driving for Uber, James Farrar logged thousands of miles on the app. Many weeks, he'd work more than 80 hours behind the wheel of his Ford Mondeo, crisscrossing the streets of London deep into the night. Along with passengers, Farrar was collecting data.

# data[].attributes.attachment_link.readable_text
Uber is paying $148 million to settle claims over the ride-hailing company's cover-up of a data breach in 2016, when hackers stole personal information of some 25 million customers and drivers in the U.S.

Instead of reporting the stolen data as required by law, Uber paid the hackers $100,000. That was in late 2016; it wasn't until November 2017 that Uber CEO Dara Khosrowshahi revealed that hackers had downloaded the names, email addresses and mobile phone numbers of 57 million Uber users around the world. The figure included 600,000 of the company's drivers, whose names and driver's license numbers were also at risk.

Uber paid the hackers when the company was still run by its former CEO, Travis Kalanick - who resigned in the middle of 2017 in the face of numerous accusations about the burgeoning start-up's culture and ethical practices.

"Uber's decision to cover up this breach was a blatant violation of the public's trust," California Attorney General Xavier Becerra said in announcing the settlement. "The company failed to safeguard user data and notify authorities when it was exposed."

Attorneys general from all 50 states and the District of Columbia filed a lawsuit over the breach. They announced the settlement on Wednesday, saying that in addition to the penalty, Uber agreed to bolster its data security practices and to give quarterly security updates to the states for the next two years.

Uber's chief legal officer, Tony West - who joined the company just as the hacking case was made public - said that paying the settlement was part of Uber's focus on "taking responsibility for past mistakes, learning from them, and moving forward."

When Uber revealed the breach, it said the hackers had targeted data stored on a third-party, cloud-based service and that the information that was exposed did not include trip location history, credit card numbers, bank account numbers, Social Security numbers or dates of birth.

The San Francisco-based company says it contacted the hackers and "obtained assurances" that the downloaded data had been deleted.

As NPR's Yuki Noguchi reports, "By not reporting the breach for a year, regulators say the company left its drivers vulnerable to financial fraud and identity theft. This settlement comes as Uber prepares to sell shares to the public for the first time next year."

As part of its response to the data breach, Uber fired Joe Sullivan, its chief security officer. After the hack became public, Sullivan defended the company's handling of the issue, saying Uber had paid a "bug bounty" to the hacker, rather than a ransom for stolen data. It was part of an ongoing security program and not, Sullivan said, a cover-up. But others, both at the company and at regulatory agencies, disagreed.

Uber is still facing lawsuits from private parties and from some cities over its handling of the 2016 breach.

In July, the Federal Trade Commission began sending checks totaling nearly $20 million to Uber drivers in 19 cities, after finding that they were misled by exaggerated claims of the income they could make. Those payments stem from a separate 2017 settlement.

# data[].attributes.attachment_link.title
Uber Pays $148 Million Over Yearlong Cover-Up Of Data Breach

# data[].attributes.attachment_link.description
Uber is paying $148 million to settle claims over the ride-hailing company's cover-up of a data breach in 2016, when hackers stole personal information of some 25 million customers and drivers in the U.S. Instead of reporting the stolen data as required by law, Uber paid the hackers $100,000.

# data[].attributes.attachment_link.readable_text
An economic and health crisis is exposing how vulnerable Uber workers really are.

Credit... Jan Robert Dünnweller

This article is part of the On Tech newsletter. You can sign up here to receive it weekdays. How we got here:
Many of us have benefited from the convenience of services like Uber and Instacart. But now in an economic and health crisis, their workers are highly vulnerable, and no one has their backs.

Here's how this happened, and who is to blame. Short version: Blame everyone, including ourselves.

In the United States, people who drive or deliver for Uber - and for companies like Lyft, Postmates, DoorDash and more - are hired as contractors not employees. That means the companies aren't required to provide them benefits and protections like health insurance and a minimum wage.

Some people who work for these companies like the flexibility of contract work. But the lack of health insurance, sick pay and other protections for many Americans, including Uber contractors, is stark now.

More people are skipping Uber rides altogether, leaving drivers with little income. And contractors are exposed to health risks when they do drive for Uber or go grocery shopping for Instacart.

Blame Uber:
For years, Uber and its peers delayed a reckoning about its contract work force, which numbers in the millions.

Only recently, as lawsuits and laws questioned whether Uber workers are actually conventional employees, the company and others have stepped up their push for a " third way " to give workers some flexibility of contractor life with some employee-like protections.

Uber, Lyft and other companies are also using this crisis as an opportunity. They helped persuade the U.S. government to extend unemployment benefits to freelancers. That's good for millions of people in financial difficulty, but it also sticks American taxpayers with the bill for worker protections Uber could have provided all along.

Uber also is paying drivers and delivery couriers who can prove they're probably sick and are ordered to isolate themselves. It's not clear how many people are eligible for a payment or have received one.

The company also asked for a temporary legal break so it could offer some worker benefits, without those facts being used against it in court cases seeking to reclassify Uber workers as employees. That's an understandable step to protect Uber's business. It's also gross.

Blame ourselves, and our government:
I started writing this pointing the finger at Uber and other companies that summon contract workers at the tap of a smartphone app. It's not that simple, though.

We have to admit that when Uber, Instacart and Postmates rely on contractors, it benefits us as well as those companies' bottom lines. If these companies instead hired masses of employees with benefits, the services they provide probably wouldn't be as ubiquitous or affordable. Uber might not exist at all outside big cities.

And Uber is far from the only company relying on non-employee workers, in part because it's cheaper to hire and fire them. That exposes the downsides of government decisions in the United States to tie many basic protections to our employer.

I'm not sure companies like Uber can continue to rely on an all-contract work force. That's going to be a huge challenge for Uber. It's also a problem for all of us who enjoyed cheap, handy services that leave workers exposed.
Get this newsletter in your inbox every weekday; A reader, Caroline Ayres, recently asked us for advice on blocking out noise while she's working from home: please sign up here.
I love my family, but with two teenagers, a dog, a cat and a preschool for kids of emergency providers in the downstairs of my building, working from home is a bit of a challenge during coronavirus. My question is: What noise-canceling headphones do I need to buy?

Lauren Dragan from the Wirecutter, a product recommendation site owned by The Times, shared this advice:

Hi, Caroline! The first thing you should know is that noise-canceling headphones - while fantastic for low frequency, sustained sounds like airplane noise - aren't effective on human voices, dog barks or other high-pitched sounds.

What blocks those sounds out is a physical barrier to the sound waves, often referred to as "passive isolation." While some noise-canceling headphones, like the Bose NC 700 or Jabra Elite 85h, also have decent passive isolation, they're often expensive.

The best way to block out kiddo shenanigans is to use isolating earbuds. Nearly any earbud you love (that fits securely) can be upgraded to better block sounds by adding sound isolating foam tips.

If you don't have earbuds already, we'd suggest the Jabra Elite 75t, as they work well for video calls. Or if you want something more affordable, the 1 More Piston Fit BT are a great option.

Another tip is to use white noise (or ocean or rain sounds) via an app to help mask the sound around you. Just be sure to keep your laptop volume below 60 percent to protect your ears.

A final resort, and I'm only half-joking, is to buy wireless earbuds and wear hearing-protection earmuffs over them. Not the most comfortable setup, but man, it's effective. Trust me. I have a 4-year-old.

The iPad is the gadget of the pandemic. Brian X. Chen, the personal tech columnist for The Times, writes that the iPad has transformed from an "other" device to a go-to screen for video calls, cooking tutorials and distraction-free emailing (with an add-on keyboard).

Policing Facebook ain't easy, example infinity. The company says posts encouraging protests against states' pandemic lockdown rules are fine, as long as the protesters abide by states' pandemic lockdown rules, Bloomberg News reported. Drawing the line between free speech and protecting public safety can lead to head-scratching rule-making.

Competitive. Marble. Racing. Watching YouTube videos of marbles steamrolling down tracks or negotiating hurdles (!) is a balm in the absence of human sports, as my colleague Mariel Padilla writes. There are even play-by-play announcers, marble "fans" and a cappella team chants.

Is it bad that I feel jealous of the pizza groundhog? Just munching without a care in the world.

We want to hear from you. Tell us what you think of this newsletter and what else you'd like us to explore. You can reach us at Get this newsletter in your inbox every weekday; please sign up here. ontech@nytimes.com.

# data[].attributes.attachment_link.title
This Pandemic Exposes the Downsides of Cheap Uber Rides

# data[].attributes.attachment_link.description
An economic and health crisis is exposing how vulnerable Uber workers really are. This article is part of the On Tech newsletter. You can sign up here to receive it weekdays. How we got here: Many of us have benefited from the convenience of services like Uber and Instacart.

# data[].attributes.body
This article explains why the sharing economy is detrimental to our society.

# data[].attributes.attachment_link.readable_text
The sharing economy is one of the fastest growing business trends in history, with investors dumping more than $23 billion in venture capital funding since 2010 into startups operating with a share-based model. Because many of these businesses are private, it's impossible to know the actual size of the sharing economy.

However, there are several clues to indicate its massive impact on our society.

Airbnb ($31 million) and Uber ($72 billion) have a combined $103 billion market cap which would rank them as the 38th wealthiest country in the world.

In 2016, 44.8 million U.S. adults used the sharing economy, and it's expected to grow to 86.5 million U.S. users by 2021.

McKinsey estimates that in the U.S. and Europe alone, 162 million people or 20-30 percent of the workforce are providers on sharing platforms.

Trying to define exactly what the sharing economy is would not do the term justice. The sharing economy is an economic principle that is constantly evolving. In the very simplest terms, it's the use of technology to facilitate the exchanged access of goods or services between two or more parties.

It's derived from the notion that mutual parties can share value from an under-utilized skill or asset. This value exchange occurs through a shared marketplace, collaborative platform, or peer-to-peer application.

The sharing model isn't a new concept-as many rural communities thrived off the same idea via bartering. However, thanks to the accessibility of the internet and mobile technology, managing share-based transactions has never been easier.

While most commonly referred to as the sharing economy, this term is an umbrella that encompasses other economic systems such as:

The sharing economy has a history of disrupting traditional business sectors. The lack of overhead and inventory help share-based businesses run lean. The increased efficiencies allow these brands to pass-through value to their customers and supply chain partners.

Traditional industries are being affected by the sharing economy-and many traditional brands will struggle if they do not adapt to the changing landscape.

Uber's ascension in the transportation industry is one of the best examples to illustrate the effect of the sharing economy in a traditional sector. Uber and other ride-sharing services offer an affordable, safe, and convenient alternative to traditional transportation options such as public transit or taxi cabs.

By utilizing an efficient mobile application and network of vetted drivers, Uber satisfies consumers' transportation demands while providing an arguably better user experience than traditional means.

In just New York City alone, there are roughly 4.5 times more Uber drivers than yellow cabs. This has caused the price of owning a taxi cab in New York City to drop from $1 million in 2015 to less than $200,000 today.

Top Sharing Economy Brands in the Transportation Space:

PWC research suggests that 86 percent of U.S. adults familiar with the sharing economy say that it makes life more affordable and 83 percent also agree that the sharing economy is more convenient and efficient than traditional methods.

Affordability, convenience, and efficiency are also three of the most influential factors in a consumer goods purchasing decision. Therefore, it's no surprise that share-based brands are also dominating the consumer goods industry.

eBay is one of the pioneers of the peer-to-peer marketplace. Their innovative platform allows users to buy and sell used or new items through their interface, and have the goods shipped directly to their home. Consumers can browse a variety of products at custom price points, in various conditions, and with different guarantees. This empowers the consumers and provides them with a more affordable, convenient, and efficient way to purchase goods.

Top Sharing Economy Brands in the Consumer Goods Space:

The benefits of the sharing economy are best illustrated in the professional and personal services space. Professional and personal services are defined by work that requires special knowledge, skills, experience, certifications, or training like copywriters, accountants, or plumbers. In relation to the sharing economy, this is also referred to as freelancing, gigs, and other trendy terms equating to short-term labor.

Powerhouses like Fiverr, Upwork, and TaskRabbit create value by providing a fast, friendly, and secure platform on which people or businesses can find contractors for hire. Freelancers can earn extra money sharing their trade skills and expertise-not unlike owners renting access to their home or car owners sharing rides.

Top Sharing Economy Brands in the Professional and Personal Services Space:

The healthcare industry is expected to generate annual revenues of $8.7 trillion by 2020. That likely explains why venture funding for digital health startups increased by 10.2 percent in Q1 of 2018 compared to Q1 of 2017. Although the sharing economy has yet to really take hold in the healthcare industry, many experts suspect it to be the next frontier for collaborative consumption.

The limitations of traditional healthcare systems, expenses and resources, are factors that we've seen mitigated in other industries through share-based methods. From telemedicine to group-consultations, the sharing economy is destined to change the healthcare industry.

For instance, it's estimated that 58 percent of the time, medical equipment sits unused-creating storage and maintenance expenses. Therefore, share-based startups like Cohealo are helping hospitals save money and increase equipment value by developing technology that enables hospitals to share medical equipment with other healthcare facilities.

Top Sharing Economy Brands in the Healthcare Space:

Technology has helped the sharing economy advance to where it is today-and, the trend should only continue as we become more connected digitally. While we've seen how dominant collaborative consumption can be in industries like transportation, consumer goods, and services, many other traditional sectors will soon experience changes because of the sharing economy.

# data[].attributes.attachment_link.title
What Is the Sharing Economy (and How Is it Changing Industries)?

# data[].attributes.attachment_link.description
The sharing economy is one of the fastest growing business trends in history, with investors dumping more than $23 billion in venture capital funding since 2010 into startups operating with a share-based model. Because many of these businesses are private, it's impossible to know the actual size of the sharing economy.

# data[].attributes.body
This talks about why the sharing economy has several consequences.

# data[].attributes.attachment_link.readable_text
June 3, 2016

The leading businesses that are advancing the concept of the "sharing economy" are in many respects no longer insurgents and newcomers. The size and scale of Uber, Airbnb and several other firms now rival, or even surpass, those of some of the world's largest businesses in transportation, hospitality and other sectors. As the economic power of these technology-driven firms grows, there continue to be regulatory and policy skirmishes on every possible front, across cities and towns spanning the United States, Europe and beyond.

While many municipalities and regions have accepted change as inevitable and have been eager to facilitate new efficiencies for consumers - Uber in particular has made a lot of regulatory headway since 2015 - there have been cases, such as in Austin, Tex. in May 2016, where policies have been in effect reversed to block these new forms of commerce. These fights are looking more and more like political campaigns. In any case, a 2015 report from the National League of Cities reviews regulatory policies and patterns across a variety of dimensions, from safety to innovation; a 2016 report from the European Parliament weighs the costs and benefits of non-participation in the sharing economy.

The Economics and Statistics Administration of the U.S. Commerce Department issued a report in June 2016 that attempts to define and map out the contours of this emerging business sector, labeling its participants "digital matching firms." That report defines this sector through the four following characteristics:

They use information technology (IT systems), typically available via web-based platforms, such as mobile "apps" on Internet- enabled devices, to facilitate peer-to-peer transactions.

They rely on user-based rating systems for quality control, ensuring a level of trust between consumers and service providers who have not previously met.

They offer the workers who provide services via digital matching platforms flexibility in deciding their typical working hours.

To the extent that tools and assets are necessary to provide a service, digital matching firms rely on the workers using their own.

The implications of the sharing economy - part of what has also been termed the "gig economy" - have of course been hotly debated in the news media, and the research world has been steadily weighing in with deeper analysis. One central area of argument relates to whether the sharing economy is simply bringing more wage-earning opportunities to more people, or whether its net effect is the displacement of traditionally secure jobs and the creation of a land of part-time, low-paid work. It's a debate that continues to develop and play out, forcing reporters to weigh competing claims that vary in tone from boosterism to warnings of the new economy's "dark side."

While the conclusions about the overall effects of this sector are anything but clear, even as more data pour in, it is worth digging into the available literature and knowing the centers of research debate and lines of argument.

A January 2015 paper co-authored by Princeton's Alan Krueger - the former Chairman of President Barack Obama's Council of Economic Advisers - based on Uber's internal data finds clear benefits for "driver-partners" and notes the new financial opportunities created for tens of thousands of workers. Those conclusions have been critiqued by, for example, the liberal-leaning Center for Economic and Policy Research. In any case, the Krueger paper also argues that "the availability of modern technology, like the Uber app, provides many advantages and lower prices for consumers compared with the traditional taxi cab dispatch system, and this has boosted demand for ride services, which, in turn, has increased total demand for workers with the requisite skills to work as for-hire drivers, potentially raising earnings for all workers with such skills."

There is the distinct danger, on both sides, of overstating the case and the size of effects. A 2014 paper by Annette Bernhardt of University of California, Berkeley, signals a cautionary note about any claims of radical recent change being wrought across the U.S. economy:

[We] all share a strong intuition that the nature of work has fundamentally changed, contributing to the deterioration of labor standards. Yet at least with aggregate national data, it has been hard to find evidence of a strong, unambiguous shift toward nonstandard or contingent forms of work - especially in contrast to the dramatic increase in wage inequality. This is not to say that there have been no changes in the workplace. But as this paper has emphasized, for enforcement agencies and policymakers, it may be more fruitful to focus on specific industries and regions in assessing when and where pernicious forms of nonstandard work have grown, and which groups of workers have been most impacted.

It is also true that the rise of independent workers, and associated job insecurity, long predates the recent rise of the sharing economy, although their percentage of all U.S. workers is expected to grow from about one-third currently to 40% by 2020, according to some estimates.

A 2015 report from the Center for American Progress notes the heated debate in Britain over "zero hours contracts" and charges that highly insecure and contingent employment leads to the exploitation of workers. The report - co-authored by Harvard's Lawrence Summers, a top official in both the Clinton and Obama administrations, and Ed Balls, a British Labour Party MP - notes that "technology has allowed a sharing economy to develop in the United States; many of these jobs offer flexibility to workers, many of whom are working a second job and using it to build income or are parents looking for flexible work schedules. At the same time, when these jobs are the only source of income for workers and they provide no benefits, that leaves workers or the state to pay these costs."

Meanwhile, scholars such as Juliet Schor of Boston College have been examining how workers might regain bargaining power despite an increasingly app-based, decentralized system of distributed labor. "While the for-profit companies may be 'acting badly,'" she writes in an October 2014 essay, "these new technologies of peer-to-peer economic activity are potentially powerful tools for building a social movement centered on genuine practices of sharing and cooperation in the production and consumption of goods and services. But achieving that potential will require democratizing the ownership and governance of the platforms."
Fights over rules and regulations
In October 2014 the New York State Attorney General released a report into Airbnb's operations that concluded that 72% of the site's rentals violated state zoning regulations or other laws. The company's business model is built around allowing people to rent out rooms or entire apartments on a short-term basis, and the report is the latest in a series of ongoing battles Airbnb is engaged in with regulators across the world.

Berlin has banned regular short-term rentals in the most popular parts of the city without prior permission from the authorities. Paris passed a law in February 2014 to allow city inspectors to check rental homes whose owners are suspected of renting them out to visitors illegally. Airbnb has countered with its own reports on the benefits of short-term stays on local housing markets, arguing that the company's service benefits local economies.

Also known as collaborative consumption or peer-to-peer (P2P), the sharing economy challenges traditional notions of private ownership and is instead based on the shared production or consumption of goods and services. Its origins were in not-for-profit initiatives such as Wikipedia (2001) and Couchsurfing and Freecycle (both 2003). Advances in information technology enabled the creation of large-scale bike-share systems (the first was in Lyon, France, in 2005), and these have subsequently expanded to the United States and around the world.

Social media and mobile technology have enabled the latest expansion of the sharing economy and turned it into a big business: Airbnb allows individuals to share their homes, while Lyft and Uber transform private cars into common resources. All these are for-profit services, but they take only a fraction of the fees levied, passing the rest on to the owners: In 2013 it was estimated that revenues passing through the sharing economy into people's wallets exceeded $3.5 billion, up 25% from the previous year. Airbnb has exceeded 10 million guest-stays since its launch and now has more than half a million properties listed. Meanwhile Uber has said that it is doubling its revenue every six months.

As a 2014 article in Harvard Business Review noted, the interests of sharing-economy firms and city governments are often aligned, but failing to engage early on with potential regulators can raise the suspicion that companies are trying to exploit loopholes rather than develop a legitimate business model. For example, courts in Frankfurt recently upheld a national ban on Uber, and the service has been banned in several Canadian cities as well. At the heart of many of these debates is whether Uber is, as it claims, operating as a pure technology company, providing a match-making service to willing participants, or whether it is operating in effect as an unlicensed taxi service, which was the conclusion of Calgary's city council. Moreover, a Massachusetts class-action lawsuit asserts that Uber exploits its drivers, misclassifying them as independent contractors to avoid paying them as employees with the same benefits.

Examples from elsewhere in the world shows such fractious relationships with regulators need not be the norm. In February 2014, Amsterdam became the first city to pass so-called "Airbnb friendly" legislation. A law allowing short-term rentals by permanent San Francisco residents was finalized in October 2014, but requires them to collect city hotel taxes and imposes other restrictions. In London, 1970s regulations limiting short-term stays were scrapped, making it easier for Airbnb and others to operate in the city. The British government has even launched an initiative to make the U.K. the "global centre for [the] sharing economy." Similarly, while some traditional operators have fought sharing start-ups, others have chosen to get in on the game themselves: In 2013 Avis paid half a billion dollars for the car-sharing service Zipcar, and Hertz has started a similar service.

Below are a range of additional academic articles that seek to define, understand and analyze the sharing economy, those who participate and its economic impact.

----------
Latest research
"Owning, Using and Renting: Some Simple Economics of the 'Sharing Economy'"
Horton, John J.; Zeckhauser, Richard J. NBER Working Paper No. 22029, February 2016.

Abstract: "New Internet-based markets enable consumer/owners to rent out their durable goods when not using them. Such markets are modeled to determine ownership, rental rates, quantities, and surplus generated. Both the short run, before consumers can revise their ownership decisions, and the long run, in which they can, are examined to assess how these markets change ownership and consumption. The analysis examines bringing-to-market costs, such as labor costs and transaction costs, and considers the operating platform's pricing problem. A survey of consumers broadly supports the modeling assumptions employed. For example, ownership is determined by individuals' forward-looking assessments of planned usage."

"Does the Sharing Economy Do Any Good?"
Dillahunt, Tawanna, et al. Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion, Pages 197-200, 2016.

Abstract: "Despite the benefits offered by sharing economy, researchers have identified several challenges preventing disadvantaged groups (e.g. low socioeconomic status, un(der)employed and/or users from emerging regions) from receiving the same level of benefits as those from advantaged populations. This panel brings researchers from the sharing economy and mobile crowdsourcing space whose research has identified unique challenges for underserved populations. We consider the opportunities offered by these platforms to disadvantaged communities and examine to what extent these platforms instead may recreate disadvantage, as well as the workarounds communities employ to make these platforms work for them. We examine the opportunities for the CSCW [Computer Supported Cooperative Work] community to address these challenges going forward."

"The Sharing Economy: Reports from Stage One"
Schor, Juliet B. Working paper, Boston College, November 2015.

Abstract: "The sharing economy has generated heated controversy as proponents claim it is bringing efficiency, opportunity and sociability and critics argue it is degrading labor, exacerbating inequality and commodifying daily life. Here we discuss findings from in-depth interviews with providers on three for-profit platforms (Airbnb, Relay Rides and TaskRabbit) and find a mixed picture. Providers are generally pleased with their earning possibilities although there is some evidence that conditions are eroding for providers of general labor services. With respect to sociability and commodification we also find a mixed picture."

"Who Benefits from the 'Sharing' Economy of Airbnb?"
Quattrone, Giovanni, et al. WWW '16 Proceedings of the 25th International Conference on World Wide Web, Pages 1385-1394, 2016.

Abstract: "Sharing economy platforms have become extremely popular in the last few years, and they have changed the way in which we commute, travel, and borrow among many other activities. Despite their popularity among consumers, such companies are poorly regulated. For example, Airbnb, one of the most successful examples of sharing economy platform, is often criticized by regulators and policy makers. While, in theory, municipalities should regulate the emergence of Airbnb through evidence-based policy making, in practice, they engage in a false dichotomy: some municipalities allow the business without imposing any regulation, while others ban it altogether. That is because there is no evidence upon which to draft policies. Here we propose to gather evidence from the Web. After crawling Airbnb data for the entire city of London, we find out where and when Airbnb listings are offered and, by matching such listing information with census and hotel data, we determine the socio-economic conditions of the areas that actually benefit from the hospitality platform. The reality is more nuanced than one would expect, and it has changed over the years. Airbnb demand and offering have changed over time, and traditional regulations have not been able to respond to those changes. That is why, finally, we rely on our data analysis to envision regulations that are responsive to real-time demands, contributing to the emerging idea of 'algorithmic regulation.'"

"Peeking Beneath the Hood of Uber"
Chen, Le, et al. IMC '15 Proceedings of the 2015 ACM Conference on Internet Measurement Conference, Pages 495-508, 2015.

Abstract: "Recently, Uber has emerged as a leader in the "sharing economy". Uber is a "ride sharing" service that matches willing drivers with customers looking for rides. However, unlike other open marketplaces (e.g., AirBnB), Uber is a black-box: they do not provide data about supply or demand, and prices are set dynamically by an opaque "surge pricing" algorithm. The lack of transparency has led to concerns about whether Uber artificially manipulate prices, and whether dynamic prices are fair to customers and drivers. In order to understand the impact of surge pricing on passengers and drivers, we present the first in-depth investigation of Uber. We gathered four weeks of data from Uber by emulating 43 copies of the Uber smartphone app and distributing them throughout downtown San Francisco (SF) and midtown Manhattan. Using our dataset, we are able to characterize the dynamics of Uber in SF and Manhattan, as well as identify key implementation details of Uber's surge price algorithm. Our observations about Uber's surge price algorithm raise important questions about the fairness and transparency of this system."
What is the sharing economy and who participates?
"Avoiding the South Side and the Suburbs: The Geography of Mobile Crowdsourcing Markets"
Jacob Thebault-Spieker; Loren Terveen; Brent Hecht. Urban Environments CSCW 2015, March 14-18, 2015, Vancouver, BC, Canada.

Abstract: "Mobile crowdsourcing markets (e.g., Gigwalk and TaskRabbit) offer crowdworkers tasks situated in the physical world (e.g., checking street signs, running household errands). The geographic nature of these tasks distinguishes these markets from online crowdsourcing markets and raises new, fundamental questions. We carried out a controlled study in the Chicago metropolitan area aimed at addressing two key questions: (1) What geographic factors influence whether a crowdworker will be willing to do a task? (2) What geographic factors influence how much compensation a crowdworker will demand in order to do a task? Quantitative modeling shows that travel distance to the location of the task and the socioeconomic status (SES) of the task area are important factors. Qualitative analysis enriches our modeling, with workers mentioning safety and difficulties getting to a location as key considerations. Our results suggest that lowSES areas are currently less able to take advantage of the benefits of mobile crowdsourcing markets. We discuss the implications of our study for these markets, as well as for 'sharing economy' phenomena like UberX, which have many properties in common with mobile crowdsourcing markets."

"The Sharing Economy: Why People Participate in Collaborative Consumption"
Hamari, Juho; Sjöklint, Mimmi; Ukkonen, Antti. Social Science Research Network, May 2013.

Abstract: "In recent years, [information and communications technologies] have afforded the rise of the so called 'collaborative consumption' (CC) - a form of consumption where people share consumption of goods and services online. CC has been expected to alleviate societal problems such as hyper-consumption, pollution, and poverty by lowering transaction costs related to coordination of economic activities within communities.... The motivation to participate in CC is often regarded as fuelled by the aspirations to do good, but at the same time CC offers participants possible economic benefits. In this paper we investigate the role of these intrinsic and extrinsic motivations in attitudes and participation. The study employs survey data (N=168) and structural equation modeling (SEM-PLS). The results show that, whereas intrinsic motivations strongly predict attitudes, they do not translate as well into usage intentions. Conversely, economic benefits predict use intentions but do not significantly influence attitude. Furthermore, the attitude-behavior gap seems to loom in the consumption behavior related to collaborative consumption; people perceive the activity positively and say good things about it, but they might not still participate in it themselves."

"The Promise of the Sharing Economy among Disadvantaged Communities"
Tawanna R. Dillahunt; Amelia R. Malone. ACM Human Factors in Computing Systems (CHI) 2015, April 18 - 23 2015, Seoul, Republic of Korea. http://dx.doi.org/10.1145/2702123.2702189

Abstract: "The digital-sharing economy presents opportunities for individuals to find temporary employment, generate extra income, increase reciprocity, enhance social interaction, and access resources not otherwise attainable. Although the sharing economy is profitable, little is known about its use among the unemployed or those struggling financially. This paper describes the results of a participatory-design based workshop to investigate the perception and feasibility of finding temporary employment and sharing spare resources using sharing-economy applications. Specifically, this study included 20 individuals seeking employment in a U.S. city suffering economic decline. We identify success factors of the digital-sharing economy to these populations, identify shortcomings and propose mitigation strategies based on prior research related to trust, social capital and theories of collective efficacy. Finally, we contribute new principles that may foster collaborative consumption within this population and identify new concepts for practical employment applications among these populations."

Abstract: "Sharing is a phenomenon as old as humankind, while collaborative consumption and the 'sharing economy' are phenomena born of the Internet age. This paper compares sharing and collaborative consumption and finds that both are growing in popularity today. Examples are given and an assessment is made of the reasons for the current growth in these practices and their implications for businesses still using traditional models of sales and ownership. The old wisdom that we are what we own may need modifying to consider forms of possession and uses that do not involve ownership."

Abstract: "Sharing systems are increasingly challenging sole ownership as the dominant means of obtaining product benefits, making up a market estimated at more than US$100 billion annually in 2010. Consumer options include cell phone minute-sharing plans, frequent-flyer-mile pools, bicycle-sharing programs, and automobile-sharing systems, among many others. However, marketing research has yet to provide a framework for understanding and managing these emergent systems. The authors conceptualize commercial sharing systems within a typology of shared goods. Using three studies, they demonstrate that beyond cost-related benefits of sharing, the perceived risk of scarcity related to sharing is a central determinant of its attractiveness. The results suggest that managers can use perceptions of personal and sharing partners' usage patterns to affect risk perceptions and subsequent propensity to participate in a commercial sharing system."

Abstract: "We examine alternative consumption including collaborative consumption, sharing, and unconsumption (i.e., postconsumption activities such as upcycling, reuse, recycling, etc.) at non-monetary-based private and public sharing events including Really Really Free Markets (RRFMs). These alternative marketplaces (RRFMs) were initially organized by the Anarchist Movement as a form of resistance to the capitalist economic model. However, many consumer groups now utilize this model to stage public sharing events as a means of raising awareness about various issues including sustainability and overconsumption. Participants bring, share, and take goods without any expectation of monetary or other exchange. There is limited research on collaborative consumption and sharing in non-monetary marketplaces. We address this gap by exploring alternative marketplaces, organized by consumers for consumers, utilizing qualitative research methods. Our findings indicate that a sense of community is both a driver of participation and an outcome of these events. Organizers and participants utilize these venues to share knowledge and possessions for various ideological and practical reasons. Our findings also indicate that these events challenge the entrenched notions of exchange and reciprocity. Our research contributes to the literature by highlighting the importance of community, collaboration, and changing consumer mindsets to the success of such sharing efforts."

Abstract: "Sharing economy practices have become increasingly popular in the past years. From swapping systems, network transportation to private kitchens, sharing with strangers appears to be the new urban trend. Although Uber, Airbnb, and other online platforms have democratized the access to a number of services and facilities, multiple concerns have been raised as to the public safety, health and limited liability of these sharing economy practices. In addition, these innovative activities have been contested by professionals offering similar services that claim that sharing economy is opening the door to unfair competition. Regulators are at crossroads: on the one hand, innovation in sharing economy should not be stifled by excessive and outdated regulation; on the other, there is a real need to protect the users of these services from fraud, liability and unskilled service providers. This dilemma is far more complex than it seems since regulators are confronted here with an array of challenging questions: firstly, can these sharing economy practices be qualified as "innovations" worth protecting and encouraging? Secondly, should the regulation of these practices serve the same goals as the existing rules for the equivalent commercial services (e.g. taxi regulations)? Thirdly, how can regulation keep up with the evolving nature of these innovative practices? All these questions, come down to one simple problem: too little is known about the most socially effective ways of consistently regulating and promoting innovation."

Abstract: "This article explores the concept of sharing in three distinct spheres: Web 2.0, whose constitutive activity is sharing (links, photos, status updates, and so on); 'sharing economies' of production and consumption; and intimate interpersonal relationships, in which the therapeutic ethos includes a cultural requirement that we share our emotions. It is argued that a range of distributive and communicative practices - not all of which are entirely new-are converging under the metaphor of sharing. Thus, practices in one sphere are conceptualized in terms of practices from other spheres. What all three spheres of sharing have in common are values such as equality, mutuality, honesty, openness, empathy, and an ethic of care. Moreover, they all challenge prevalent perceptions of the proper boundary between the public and the private."

Abstract: "This essay offers a framework to explain large-scale effective practices of sharing private, excludable goods. It starts with case studies of carpooling and distributed computing as motivating problems. It then suggests a definition for shareable goods as goods that are "lumpy" and "mid-grained" in size, and explains why goods with these characteristics will have systematic overcapacity relative to the requirements of their owners. The Essay next uses comparative transaction costs analysis, focused on information characteristics in particular, combined with an analysis of diversity of motivations, to suggest when social sharing will be better than secondary markets at reallocating this overcapacity to non-owners who require the functionality. The essay concludes with broader observations about the attractiveness of sharing as a modality of economic production as compared to markets and to hierarchies such as firms and government. These observations include a particular emphasis on sharing practices among individuals who are strangers or weakly related; sharing's relationship to technological change; and some implications for contemporary policy choices regarding wireless regulation, intellectual property, and communications network design."
Shared accommodation
Abstract: "The purpose of this study is to examine the role social networking technologies play in the moral economy of alternative tourism. The study takes as its empirical focus the online hospitality exchange network Couchsurfing. Using the concept of 'moral affordances', the analysis outlines the way Couchsurfing's technical systems, software design, and search algorithms enable participants to engage in a moral economy based on the non-commodified provision of accommodation to strangers and personal relations of trust and intimacy. Findings suggest that these affordances are not isolated effects of the technologies themselves, but rather reflect a broader moral landscape in which alternative tourism is performed."

"The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry"
Zervas, Georgios; Proserpio, Davide and Byers, John; Boston U. School of Management Research Paper No. 2013-16, February 2014.

Abstract: "Airbnb is an online community marketplace facilitating short-term rentals ranging from shared accommodations to entire homes that has now contributed more than ten million worldwide bookings to the so-called sharing economy. Our work addresses a central question facing the hospitality industry: to what extent are Airbnb stays serving as substitutes for hotel stays, and what is the impact on the bottom line of affected hotels? Our focus is the state of Texas, where we identify Airbnb's impact by exploiting significant spatiotemporal variation in the patterns of adoption across city-level markets. Using a dataset we collected spanning all Airbnb listings in Texas and a decade-long panel of quarterly tax revenue for all Texas hotels, we develop a nuanced estimate of Airbnb's material impact on hotel revenues. Our baseline estimate is that a 1% increase in Airbnb listings in Texas results in a 0.05% decrease in quarterly hotel revenues, an estimate compounded by Airbnb's rapid growth.... We find that the impacts are distributed unevenly across the industry, with lower-end hotels and hotels not catering to business travelers being the most affected. Finally, by simulating various regulatory interventions informed by current events, such as limiting Airbnb hosts to a single listing, we find only a moderate mitigating impact on hotel revenues."
Shared transport
Extract: "The P2P ride-sharing platforms like Uber and Lyft have opted for a seemingly infinitely scalable, pure, for-profit business model. As these ride-share platforms have no need to hire drivers or acquire vehicles, Uber and Lyft and others like them, rely on the power of social networking to scale their service. As evidenced by their rapid growth and high valuations, it is clear these ride-share companies have achieved some early success in maximizing value to their customers... However, the private ride-share operators, to date have opted to avoid interaction with local governments. As mentioned earlier, this has resulted in significant challenges to the longevity of their business models due to legal action and other threats posed by local governments and taxi operators. We suggest that this can be explained, in part, by the failure to consider more active engagement with local governments from the beginning. While the go-it-alone approach and avoiding local government and regulation has been a historical modus operandi in other sectors (Konefal, 2013), we suggest that shared mobility service providers would be better served by finding ways to collaborate with local governments if they want to achieve long-term viability. Not only would this entail adhering to regulations in areas such as vehicle and driver safety requirements but also seeking to optimize the citizen and environmental goals to achieve active city support. Any direct financial support, or incentives that promote the use of these P2P networks, such as embedding the ride-sharing data into transit applications, could result in a reduction in costs for riders."

Abstract: "Taxi services are a vital part of urban transportation, and a considerable contributor to traffic congestion and air pollution causing substantial adverse effects on human health. Sharing taxi trips is a possible way of reducing the negative impact of taxi services on cities, but this comes at the expense of passenger discomfort quantifiable in terms of a longer travel time. Due to computational challenges, taxi sharing has traditionally been approached on small scales, such as within airport perimeters, or with dynamical ad hoc heuristics. However, a mathematical framework for the systematic understanding of the tradeoff between collective benefits of sharing and individual passenger discomfort is lacking. Here we introduce the notion of shareability network, which allows us to model the collective benefits of sharing as a function of passenger inconvenience, and to efficiently compute optimal sharing strategies on massive datasets. We apply this framework to a dataset of millions of taxi trips taken in New York City, showing that with increasing but still relatively low passenger discomfort, cumulative trip length can be cut by 40% or more. This benefit comes with reductions in service cost, emissions, and with split fares, hinting toward a wide passenger acceptance of such a shared service. Simulation of a realistic online system demonstrates the feasibility of a shareable taxi service in New York City. Shareability as a function of trip density saturates fast, suggesting effectiveness of the taxi sharing system also in cities with much sparser taxi fleets or when willingness to share is low."

Abstract: " Access-based consumption, defined as transactions that can be market mediated but where no transfer of ownership takes place, is becoming increasingly popular, yet it is not well theorized. This study examines the nature of access as it contrasts to ownership and sharing, specifically the consumer-object, consumer-consumer, and consumer-marketer relationships. Six dimensions are identified to distinguish among the range of access-based consumptionscapes: temporality, anonymity, market mediation, consumer involvement, the type of accessed object, and political consumerism. Access-based consumption is examined in the context of car sharing via an interpretive study of Zipcar consumers. Four outcomes of these dimensions in the context of car sharing are identified: lack of identification, varying significance of use and sign value, negative reciprocity resulting in a big-brother model of governance, and a deterrence of brand community. The implications of our findings for understanding the nature of exchange, consumption, and brand community are discussed."

Abstract: "Since the mid-2000s, public bikesharing (also known as "bike hire") has developed and spread into a new form of mobility in cities across the globe. This paper presents an analysis of the recent increase in the number of public bikesharing systems. Bikesharing is the shared use of a bicycle fleet, which is accessible to the public and serves as a form of public transportation. The initial system designs were pioneered in Europe and, after a series of technological innovations, appear to have matured into a system experiencing widespread adoption. There are also signs that the policy of public bikesharing systems is transferable and is being adopted in other contexts outside Europe. In public policy, the technologies that are transferred can be policies, technologies, ideals or systems. This paper seeks to describe the nature of these systems, how they have spread in time and space, how they have matured in different contexts, and why they have been adopted."

Abstract: "This paper begins by providing an overview of bike share programs, followed by a critical examination of the growing body of literature on these programs.... Several consistent themes have emerged within the growing body of research on bike share programs. Firstly, the importance bike share members place on convenience and value for money appears paramount in their motivation to sign up and use these programs. Secondly, and somewhat counter intuitively, scheme members are more likely to own and use private bicycles than nonmembers. Thirdly, users demonstrate a greater reluctance to wear helmets than private bicycle riders and helmets have acted as a deterrent in jurisdictions in which helmets are mandatory. Finally, and perhaps most importantly from a sustainable transport perspective, the majority of scheme users are substituting from sustainable modes of transport rather than the car."
Online ratings and reputation
Absract: "Reciprocity in feedback giving distorts the production and content of reputation information in a market, hampering trust and trade efficiency. Guided by feedback patterns observed on eBay and other platforms, we run laboratory experiments to investigate how reciprocity can be managed by changes in the way feedback information flows through the system, leading to more accurate reputation information, more trust, and more efficient trade. We discuss the implications for theory building and for managing the redesign of market trust systems."

Abstract: "Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive a trust or reputation score, which can assist other parties in deciding whether or not to transact with that party in the future. A natural side effect is that it also provides an incentive for good behaviour, and therefore tends to have a positive effect on market quality. Reputation systems can be called collaborative sanctioning systems to reflect their collaborative nature, and are related to collaborative filtering systems. Reputation systems are already being used in successful commercial online applications. There is also a rapidly growing literature around trust and reputation systems, but unfortunately this activity is not very coherent. The purpose of this article is to give an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions, to analyse the current trends and developments in this area, and to propose a research agenda for trust and reputation systems."
Keywords: research roundup, technology, public bicycle, ride-sharing, ridesharing, bicycle-share systems, transportation, tourism, hotels, bikeshare

# data[].attributes.attachment_link.title
Uber, Airbnb and consequences of the sharing economy: Research roundup - Journalist's Resource

# data[].attributes.attachment_link.description
June 3, 2016 The leading businesses that are advancing the concept of the "sharing economy" are in many respects no longer insurgents and newcomers. The size and scale of Uber, Airbnb and several other firms now rival, or even surpass, those of some of the world's largest businesses in transportation, hospitality and other sectors.

# data[].attributes.attachment_link.readable_text
Uber's impact on cities has been immense over its 10-year history. The ride-hailing app has gone from being a cheaper and easier black car service to a more convenient taxi service, but recently shifted its current orientation toward being a mobility platform with a range of transportation modes to suit the needs of ever more users.

As Uber prepares for its highly anticipated initial public offering - rumored for this spring - there are escalating concerns over the sustainability of its business model and what it's doing to the cities it operates in. Addressing these concerns will be essential to the company's future, but it's still unclear if the company will be able to do so effectively.

As Uber approaches its initial public offering there are escalating concerns over the sustainability of its business model and what it's doing to the cities it operates in.

In February, Uber reported its fourth quarter results, which showed it lost $3.3 billion in fiscal year 2018 once the benefits from the sale of its Southeast Asian operations to Grab are excluded. The company's revenue growth has also significantly slowed. While the loss is an improvement on the $4.5 billion it lost in 2017, it's still huge. Tech companies are known for losing a lot of money when they're getting started, but Uber has lost massive sums since it was founded in 2009. Even Amazon, previously known for not making money, never reported an annual loss of more than $1.4 billion.

And that may not change anytime soon. A 2016 assessment of Uber's financials by transportation consultant Hubert Horan showed that users paid an average of only 41 percent of the actual cost of their rides, as fares were subsidized to undercut competition and gain market share. Further, Uber's initial plan to pursue an Amazon-like growth model didn't translate from e-commerce to transportation. The vast majority - 85 percent - of its costs are driver salaries, who have to pay for their own vehicles - and those expenses don't decline significantly with scale. While these numbers have likely changed a bit since 2016 - Uber has cut driver pay, but angered drivers and increased turnover in the process - there's no reason to believe the picture is significantly different within its ride-hailing service.

Financials aren't Uber's only problems, though; a growing body of research confirms what some urban residents have been saying for a while: ride-hailing apps in general are also wreaking havoc on cities.

Get the think newsletter.

A report out of UC Davis in October 2017 looked at seven major metro areas - Boston, Chicago, Los Angeles, New York, San Francisco, Seattle and Washington, D.C. - and found that between 49 and 61 percent of ride-hailing trips either would not have been made or would have instead been made by taking transit, walking or cycling if Uber or Lyft had not been an option. The researchers also concluded that 91 percent of ride-hailing users had not made any changes to their vehicle ownership status, and when a household did sell a vehicle, it made up for the reduced driving miles by simply taking more ride-hailing trips.
SIGN UP FOR THE THINK WEEKLY NEWSLETTER HERE
That report does not, however, exist in a vacuum. Another study by Boston's Metropolitan Area Planning Council published in February 2018 similarly found that 59 percent of ride-hailing trips in Boston either would not have been made or were replacing trips that had previously been made through transit, cycling, or walking. The San Francisco County Transportation Authority also reported in June 2017 that ride-hailing services represented 5,700 vehicles on the roads during peak weekday hours - 6,500 on Fridays. The services made 12 times the number of taxi trips. On average, that meant a minimum of 170,000 trips and 570,000 miles of travel on a typical San Francisco weekday, mainly concentrated in the densest and most congested parts of the city, which are also the most walkable areas with the best access to public transit and cycling.

While Uber claimed that its service would allow people to get rid of their cars, the research so far hasn't shown this is happening.

So while Uber claimed that its service would allow people to get rid of their cars, the research so far hasn't shown this is happening. Uber also used to claim that by reducing car ownership, it would reduce traffic congestion. Instead, the research suggests Uber often converts transit, cycling and walking into vehicle trips, thus worsening congestion.

There's been concern for some time that Uber was taking users from transit, especially as increased congestion made buses less reliable. In January 2019, researchers at the University of Kentucky released a report that quantified this phenomenon. Looking at 22 major U.S. cities, the researchers estimated that the introduction of ride-hailing services caused an annual decline of 1.29 percent in heavy rail ridership and a 1.7 percent decline in bus ridership. Since this effect accumulates over time, bus ridership in San Francisco would have suffered a 12.7 percent reduction since Uber and Lyft started operating in 2010 if all other factors were stable. That's a staggering figure, especially considering how reducing car trips and increasing transit and cycling will be essential to meeting climate targets.

Faced with a still-unprofitable operating model and growing criticism of the negative urban impacts of its ride-hailing service, Uber has pivoted the company's focus since the March 2018 fatal crash between one of its self-driving test vehicles and a pedestrian. Former CEO Travis Kalanick had positioned self-driving cars as the company's path to profitability: by automating drivers, a significant cost would be eliminated, allowing Uber to finally get in the black. The crash highlighted how long autonomous driving technology will likely take to perfect, blowing the promised profitability timeline.

Kalanick's replacement, Dara Khosrowshahi, has a new vision for Uber's future - one that he hopes will convince investors to allow major losses to continue in order to achieve a larger goal.

Khosrowshahi is set on turning Uber into the "Amazon for transportation," or the dominant digital platform in the transportation space, which has resulted in a shift in focus from the ride-hailing service to Uber's app. Instead of imminent profitability, Khosrowshahi is instead promising investors monopoly, which will eventually allow it to extract rents from other transportation providers that will pay for the long-promised return on investment.

In order to achieve this, Uber has begun expanding its offerings. In April 2018, it bought Jump Bikes, a dockless bike-share service that has since expanded into scooters and which Uber claims is beginning to cannibalize its shorter ride-hail trips. The company has also signed agreements with third-party providers to expand the options in its app, including Lime's scooter-sharing service, Getaround's car-sharing service, Masabi's transit ticketing - to name just a few. It also announced a partnership with Denver's transit agency to allow its services to appear in the Uber app - notably, this news came just a couple of weeks after the University of Kentucky report on Uber's negative effect on transit ridership.

These partnerships are certainly more convenient for Uber users, and could attract more people to its app, increasing its share of the trip-planning market. Uber also takes a cut of the revenue from each trip booked through its app - those are the rents I mentioned - which are low for now, but could increase as its dominance grows. More importantly at this juncture, the third-party services also provide Uber with more data on urban transportation patterns so its trip-planning functions are better than its competitors. More options and a better service will help to attract more users, which makes a great pitch to investors ahead of its IPO.

But government and transit agencies need to consider the implications of allowing Uber to control urban trip-planning. Instead of aiding Uber's platform monopoly ambitions, as Denver did, transit agencies need to think about what's best for their residents. Capitalism can enable innovation, but it rarely prioritizes the greatest social good.

There's no reason why public agencies can't innovate on their own: that's what Berlin is doing with its new Jelbi app, which brings together public transit, bike share, scooters, car-sharing and taxis in a single convenient interface. American cities should be doing the same. The world has enough tech monopolies, and every week seems to bring new revelations about their nefarious behavior. Urban residents deserve better, and public agencies should step up to protect the public interest.

# data[].attributes.attachment_link.title
Opinion | Uber is convenient for city commuters - but bad for cities

# data[].attributes.attachment_link.description
Uber's impact on cities has been immense over its 10-year history. The ride-hailing app has gone from being a cheaper and easier black car service to a more convenient taxi service, but recently shifted its current orientation toward being a mobility platform with a range of transportation modes to suit the needs of ever more users.

# data[].attributes.attachment_link.readable_text
The tradeoffs are far too high for a little more convenience

Over the past ten years, Uber has grown to become a ubiquitous provider of urban transportation. The company has become so popular that some people haven even started using it as a verb.
"Did you drive?" "No, I ubered."
Uber has made getting from A to B easier for a certain group of people - of that there can be no doubt - but it's also had severe consequences for other people who don't have the resources to be frequent uberers. And, personally, I think that should be considered when we decide which service or transportation mode we want to use to get to our destination.

As the headline says, I don't use Uber. I've only been in an Uber vehicle once. I was coming home from a night out with friends in London and one of them requested a ride. When the driver arrived, I thought it would be rude to object, given how he was already there and expecting a fare.

I've never downloaded the Uber app, or signed up for an Uber account. I get annoyed when I see the logo on the windshields of cars, and I can't say my reaction is much different when it's Lyft instead - their PR may make them out to be the anti-Uber, but their business model is nearly identical.

I think we'd all be better off if everyone deleted the app and looked for alternatives. And though I'm talking about Uber, it's really more of a shorthand for all ride-hailing services.

It's time to give them up. Here's why.

Most people should know this by now, but Uber's drivers are not employees, they're contractors, and that comes with a lot of consequences.

Uber and other gig economy companies are frequently pitched as offering freedom from traditional employment, allowing workers to set their own schedules and be their own bosses. But that's not how it works in practice. Sure, drivers can open the app whenever they want, but riders are only requesting rides at particular times, and if drivers ignore those peak periods, the time between rides will be longer and they'll earn less money.

Since drivers are contractors, they also lose all the benefits of an employment contract. Uber drivers have no minimum wage, no vacation pay, no overtime pay, no health benefits, and none of the workplace protections that employees can expect. Their "job" is completely controlled by the platform company and they have no power to negotiate better conditions.

Uber's success has also inspired a whole range of other "Uber-for-X" companies using a similar gig-work, contractor-reliant model, which pushes down wages and working conditions in a whole range of industries. As Alexis C. Madrigal recently put it in The Atlantic, "they've served to make our lives marginally more convenient than they were before," but "the societal tradeoff, when fully calculated, seems as likely to fall in the red as the black."

And it's not just the workers who are suffering.

Uber claimed it would liberate people from their cars and reduce congestion in the process, but it's done nothing of the sort. Since Uber vehicle numbers are not capped in the way that taxis numbers are, ride-hail drivers have flooded city centers across the world, making all traffic slower and any road-based transport more frustrating as a result.

A study of seven major U.S. metro areas from UC Davis showed that 91 percent of ride-hailing users didn't make any changes to their car ownership status, and those that did made up for the reduced miles driven by taking more ride-hail trips. The researchers also found that 49 to 61 percent of all ride-hailing trips wouldn't have been taken or would have used transit, cycling, or walking had ride-hailing not been an option. Another study by the Metropolitan Area Planning Council put that number at 59 percent in Boston.

Those are key figures because they show that Uber, Lyft, and their competitors not only add car trips in urban centers, they also make existing trips less efficient by shifting them from transit or cycling into a car. This process makes traffic congestion worse because it places more vehicles on the road.

That's exactly what has been observed in San Francisco and New York City. The San Francisco Country Transportation Authority estimated that ride-hailing companies added 5,700 vehicles to city streets during weekday peak hours, increasing to 6,500 on Fridays, and that there were fifteen times more ride-hailing vehicles than taxis. That translated to 170,000 additional daily trips and 570,000 additional vehicle miles, and the trips were concentrated in the densest and most transit-oriented areas of the city. Schaller Consulting's report on New York City similarly found that the number of taxi and ride-hailing vehicles had risen 59 percent from 2013 to 2017 - remember taxi numbers are capped - adding over 600 million vehicle miles, which made congestion worse and, by extension, bus services less reliable.

These studies illustrate how Uber is making urban transportation worse for the majority of people in order to make it a bit more convenient for a much smaller group of people - surveys have consistently found ride-hailing users to be more highly educated, whiter, younger, and having higher incomes than the general public. Uber has also claimed it connects people to transit, but a report from the University of Kentucky released in January 2019 found that ride-hailing services reduced rail ridership by 1.29 percent and bus ridership by 1.7 percent annually, meaning that in San Francisco they're responsible for a 12.7 percent decline in bus use. That's terrible for our cities, for less well-off urban residents, and for anyone who wants efficient transportation networks.

Between the negative effects on workers and cities, all to make mobility a bit easier for a small privileged group, I do not believe that Uber - or any other ride-hailing service - is providing a net benefit in urban areas. Uber makes wages, working conditions, and mobility worse for the many just to grant convenience and savings to the few - and that's not something to support.

Where cities have tried to get ride-hailing under control, like in New York City, Uber has challenged the new regulations. Its new business strategy amounts to an attempted monopolization of urban trip-planning that would give it even more power that it has so far used against the public interest.

There is an argument that ride-hailing could work in less densely populated areas, such as suburbs or even rural areas, but those are currently the places where Uber is less likely to operate. As the SFCTA report noted, the vast majority of Uber's trips take place in the densest parts of the city, where its negative effects are amplified. If drivers are already struggling to make a living in urban cores, imagine how impoverished they'd be in places with far fewer users. It's just better to have a small taxi service.

I'm a bit more sympathetic to the safety argument, particularly coming from women who like to have the security of their location always being known and able to be broadcast to a friend or partner while they're in an Uber vehicle. There's a perception that taxis and transit won't always be as safe for women, and rather than ceding safety to Uber, that should place pressure on taxi and transit operators to make services safer for everyone.

Though it's worth noting that where some feel safer in Uber, others are discriminated against. Ride-hailing companies have been severely criticized for their lack of wheelchair-accessible services, and drivers have been known to refuse rides from or even attack black, gay, lesbian, and trans passengers. Uber has also been criticized for its lack of effective background checks which let thousands of criminals drive for the company and resulted in passengers being abused, sexually assaulted, and even raped. Instead of trying to improve its practices, Uber fought stronger background check rules as cities planned to legislate. So much for putting safety first.

In 2017, people took to social media to declare they would #DeleteUber and their followers should do the same. In the past two years, some of Uber's messaging has changed and its business practices have arguably gotten a little better, but it's still a company whose goals do not align with the public good. They've wreaked havoc on worker's rights and city streets selling a false vision of the future of mobility. It's time to put our efforts into improving transit and cycling, and making taxis safer for the rare time we need to hop in a car.

Uber doesn't deserve our trust, nor our support. We can do better.

# data[].attributes.attachment_link.description
The tradeoffs are far too high for a little more convenience Over the past ten years, Uber has grown to become a ubiquitous provider of urban transportation. The company has become so popular that some people haven even started using it as a verb. "Did you drive?" "No, I ubered."

# data[].attributes.attachment_link.readable_text
Lucas Jackson/Reuters

A new analysis by the ride-hailing giants sheds some light on a long-asked question about their congestion impacts on U.S. cities.

After the 2008 economic crash, Americans began driving less. But it didn't last long: In every year since 2013, U.S. drivers have packed on more miles behind the wheel. This rise in vehicle-miles traveled (VMT, in wonk-speak) can be seen and felt in the nation's metropolises. Congestion on major arteries like L.A.'s I-405 or San Francisco's Geary Boulevard is getting worse; pedestrian death counts are reaching record heights; tailpipe emissions are growing thicker.

Also new since the Great Recession-Uber and Lyft. These ride-hailing services stormed into cities in the 2010s with a grand utopian promise: By tapping into America's vast reservoir of idle vehicles, on-demand, app-based rides would reduce the need for personal car ownership and ultimately remove cars from the road.

But now, less than a decade into this experiment, the industry is 'fessing up. Today the ride-hailing giants released a joint analysis showing that their vehicles are responsible for significant portions of VMT in six major urban centers. Still, Uber and Lyft's combined share is still vastly outstripped by personal vehicles. As Chris Pangilinan, Uber's head of global policy for public transportation, wrote in a blog post accompanying the findings, "although TNCs are likely contributing to an increase in congestion, its scale is dwarfed by that of private cars and commercial traffic."

Led by the respected transportation consultancy Fehr & Peers, the analysis provides a high-level view of the combined mileage contributions from Uber and Lyft, as a share of overall VMT, over a recent month in the Boston, Chicago, L.A., San Francisco, Seattle, and Washington, D.C. areas. Results are shown at the level of the larger metropolitan landscape, which includes both the central city and its surrounding suburbs, as well as the level of the core county that contains the city's most concentrated homes and jobs.

Notably absent here: New York City, the largest U.S. market for these "transportation network companies," or TNCs. A Lyft representative said that this was partly because the city is unique in terms of its extremely low rate of car ownership and expansive transit system. Previous research by the independent transportation consultant Bruce Schaller has shown that yellow cabs and TNCs together make up 50 percent or more of traffic in central Manhattan-findings that pushed New York City lawmakers earlier this year to approve congestion fees for drivers entering the downtown core.

(Fehr & Peers)

The new findings show that Uber and Lyft account for just 1-3 percent of total VMT in the larger metropolitan regions surrounding the six cities. But they have a far heavier traffic impact in core urban areas, as the table below shows: In San Francisco County, Uber and Lyft make up as much as 13.4 percent of all vehicle-miles. In Boston, it's 8 percent; in Washington, D.C., it's 7.2 percent.

These numbers suggest that ride-hailing is hitting traffic harder in many cities than previously understood. For example, independent research by the San Francisco County Transportation Authority in 2017 showed that, as of fall 2016, TNCs generated about 6.5 percent of the county's total VMT on weekdays, and 10 percent of weekends. And the agency found that the growth in ride-hailing was already a major contributor to noticeable slow-downs on San Francisco streets.

Cities are changing fast. Keep up with the CityLab Daily newsletter.

Now, the Fehr and Peers memo indicates that TNCs accounted for nearly twice the VMT in San Francisco than the SFCTA had estimated, said Gregory Erhardt, a professor of civil engineering at the University of Kentucky who has researched Uber and Lyft's effects on public transit ridership. That means the services are likely delaying commuters more, too. "This difference may be due to the continued increase in TNC use over the intervening two years," Erhardt said. "With nearly double the TNC VMT, we would expect the effect of TNCs on congestion to be much higher in 2018 than was estimated for 2016 conditions."

Ride-hailing did not seem to have an equally large footprint in all cities. Uber and Lyft posted lower shares of total VMT in L.A., Seattle, and Chicago.

The findings also answer a question that many transportation researchers have been keen to find out: How many TNC miles account for an actual passenger, versus an empty backseat? It might be even fewer than other researchers have guessed. On average, between the six cities, just 54 to 62 percent of the vehicle miles traveled by Lyfts and Ubers were with a rider in tow. A third of these miles involve drivers slogging around in between passengers ("deadheading," in taxi-driver argot); 9 to 10 percent are drivers on their way to a pickup.

There are big questions that go unaddressed here, such as the growth of Uber and Lyft traffic over time (other than the fact that they both started from zero, less than ten years ago), or their influence on riders shifting away from buses and trains. Erhardt would prefer to see the companies divulge more fine-grained information to allow for more independent review. And Schaller questioned some of the data itself, saying that he wouldn't expect L.A. and Seattle to be such outliers.

Even so, these results represent a striking, if perhaps belated, confession from an industry that's had a profound effect on urban life. As Uber and Lyft have grown from unicorn startups to publicly traded juggernauts with millions of daily riders, they have fought to keep their trip data out of the hands of regulators and researchers trying to measure the effects of ride-hailing on transportation networks. What numbers were available have painted an increasingly unflattering picture. Studies from U.C. Davis, the University of Kentucky, DePaul University, and independent researchers in Boston, San Francisco, and New York City have offered evidence that mobility apps contribute to VMT, congestion, and the decline of public transit ridership.

Recommended

Meanwhile, it's become harder for the companies to stand by their original traffic-taming claims. In 2018, Lyft collaborated with the Rocky Mountain Institute, a clean-energy think tank, to produce a study that concluded ride-hailing vehicles were "more efficient" than private cars in several cities. But after vociferous criticism, the claim that was later retracted. "We represented certain conclusions as definitive, when in fact they are not," the Institute wrote. Now, Fehr and Peers write that their analysis should help both Uber and Lyft "form appropriate narratives for both internal and external communication."

But, alongside their big mea culpa, Uber and Lyft are also pointing their fingers elsewhere, and justifiably so. The report calls out private vehicles as the true culprits in overall traffic congestion, accounting for 87 to 99 percent of total VMT in the analyzed regions. Indeed, across the U.S., 75 percent of Americans still drive alone to work.

As such, the ride-hailing companies are positioning their analysis as a way to promote congestion pricing, a policy where drivers pay fees to access high-volume city streets. Recently adopted in lower Manhattan, the model has been proven to reduce traffic in other parts of the world, and Uber and Lyft would love see more U.S. cities adopt it, since it could nudge riders to share trips. "We know other communities are beginning to study congestion pricing as a solution to traffic," writes Anthony Foxx, the former U.S. Secretary of Transportation who is now Lyft's Chief Policy Officer. "This has encouraged us to think more comprehensively about how to best implement congestion pricing."

But for researchers who've spent years seeking the truth about ride-hailing, Uber and Lyft's fresh numbers come as a valuable contribution. "It's great to see them be upfront," said Schaller. "I'm a scrounger for any information I can get my hands on. This is straight from the companies, and it's very useful-it helps advance our understanding."

About the Author

# data[].attributes.attachment_link.title
What Ride-Hailing Is Really Doing to Urban Traffic

# data[].attributes.attachment_link.description
After the 2008 economic crash, Americans began driving less. But it didn't last long: In every year since 2013, U.S. drivers have packed on more miles behind the wheel. This rise in vehicle-miles traveled (VMT, in wonk-speak) can be seen and felt in the nation's metropolises.

# data[].attributes.body
This Article shares why Uber specifically is not beneficial for our society.

# data[].attributes.attachment_link.readable_text
Here's the latest evidence that Uber and Lyft are destroying our world: Students at the University of California Los Angeles are taking an astonishing 11,000 app-based taxi trips every week that begin and end within the boundaries of the campus.

The report in the Daily Bruin revealed anew that Uber, Lyft, Via and the like are massively increasing car trips in many of the most walkable and transit friendly places in U.S.

It comes after a raft of recent studies have found negative effects from Uber and Lyft, such as increased congestion, higher traffic fatalities, huge declines in transit ridership and other negative impacts. It's becoming more and more clear that Uber and Lyft having some pretty pernicious effects on public health and the environment, especially in some of the country's largest cities.

We decided to compile it all into a comprehensive list, and well, you judge for yourself. Here we go:

They increase driving - a lot

The U.C.L.A. trips are an example of what is happening at a much wider scale: A lot more driving.

Uber and Lyft, for example, are providing 90,000 rides a day in Seattle now. That's more than are carried daily by the city's light rail system, the Seattle Times reports.

One study estimated that in cities with the highest Uber and Lyft adoption rates, driving has increased about 3 percent compared to the cities with the lowest. That's an enormous amount of miles.

And transportation consultant Bruce Schaller estimates that the app-based taxis have added 5.7 billion driving miles in the nine major cities they primarily operate. (For comparison, in their first year of deployment across the U.S., e-scooters operated by private tech firms carried between 60-80 million trips.)

By the end of this year, Schaller has estimated all taxi ridership will surpass the number of trips made on buses the U.S.

The promise of companies such as Uber and Lyft was that they would "free" city dwellers to sell their cars or not acquire them in the first place. And car ownership has declined among higher wage earners.

But a University of Chicago study found the presence of Uber and Lyft in cities actually increases new vehicle registrations. That's because the companies encourage lower-income people to purchase cars, even advertising in some markets how people should put that new car to use - as an Uber.

They spend half their time 'deadheading'

For every mile a Uber or Lyft car drives with a passenger, it cruises as many miles - if not more - without a passenger, a practice known in the industry as "deadheading." Estimates of total deadheading time vary from 30 percent to as much as 60 percent.

Uber and Lyft's policies make this worse by encouraging drivers to constantly circle to reduce wait times for users, according to John Barrios, the researcher at the University of Chicago, who has studied Uber and Lyft.

They operate in transit-friendly areas

Transit systems around the nation are losing riders to Uber and Lyft, which suggests that the companies are merely showing the need to beef up transit service across the country.

But if you drill down, something else is at work because Uber and Lyft primarily operate in areas that are best served by transit. For example in Seattle, about half the rides taken in Uber and Lyft originate in just four neighborhoods: downtown, Belltown, South Lake Union and Capitol Hill, according to David Gutman at the Seattle Times. These are some of the city's most walkable and transit-friendly areas.

Moreover, according to Schaller, about 70 percent of Uber and Lyft trips take place in just nine American cities: Boston, Chicago, Los Angeles, Miami, New York, Philadelphia, San Francisco, Seattle and Washington, D.C.

Meanwhile, traditional taxi service, Schaller estimates, still serves more total trips in suburban and rural areas than the Ubers and Lyfts.

Why would Uber and Lyft use be so high in dense, transit-rich areas? Studies aren't conclusive, but on average, Uber and Lyft riders, not surprisingly, skew rich and skew young.

In the top nine cities for Uber and Lyft people with incomes above $200,000 are by far the most likely to use the service. Lower-income people without cars in some less urban markets do use Uber and Lyft, but their use is dwarfed by those with high incomes, Schaller finds.

They mostly replace biking, walking or transit trips

In an ideal world, Uber and Lyft would be making good on their promise to reduce private car ownership because city dwellers would feel more comfortable selling their cars, thanks to the presence of Uber and Lyft.

But the data shows that Uber and Lyft mostly "free" people from walking and transit.

A survey of 944 Uber and Lyft riders by the Metropolitan Area Planning Council in Boston last year, found that 42 percent of riders would have taken transit if the services hadn't been available. Another 12 percent (like those U.C.L.A students and their 11,000 on-campus taxi rides per week) said they would have biked or walked their journey. Another 5 percent would have just avoided the trip altogether.

Only about 17 percent - less than one in five - said they would have made the journey in a private car otherwise. (The remainder said they would have used a traditional taxi.)

Uber and Lyft just aren't competitive price-wise with private car ownership, Schaller said, except in areas with expensive parking. Even with Uberpool and other shared services - which account for a small share of total business, Schaller says - Uber and Lyft increase car miles on urban streets. For each mile of driving removed, they add about 2.6 miles, he estimates.

They hurt transit

Uber and Lyft are just crushing transit service in the U.S. A recent study estimated, for example, they had reduced bus ridership in San Francisco, for example, 12 percent since 2010 - or about 1.7 percent annually. And each year the services are offered, the effect grows, researcher Gregory Erhardt found.

Every person lured from a bus or a train into a Lyft or Uber adds congestion to the streets and emissions to the air. Even in cities that have made tremendous investments in transit - like Seattle which is investing another $50 billion in light rail - Uber and Lyft ridership recently surpassed light rail ridership.

Transit agencies simply cannot complete with private chauffeur service which is subsidized at below real costs by venture capitalists. And maybe that's the point.

Erhardt, for example, estimated that San Francisco would have had to increase transit service 25 percent overall just to neutralize the effect of Uber and Lyft.

Worse is the tale of two cities effect: Relatively well off people in Ubers congesting the streets of Manhattan and San Francisco slow down buses full of relatively low-income people. By giving people who can afford it escape from the subway, Uber and Lyft also reduce social interaction between people of different classes and lead to a more stratified society.

They reduce political support for transit

As an added kick in the shins, Uber and Lyft degrade political support for transit. If relatively well-to-do people can hop in an Uber or a Lyft every time the bus or train is late, the political imperative to address the problem is reduced. The wealthier people substituting Uber and Lyft for transit trips have disproportionate political influence.

Cities are already capitulating. Last week, Denver partnered with Uber in a last-ditch effort to win back some riders who had jumped to the app.

In addition, right-wing ideologues have argued that Uber and Lyft make transit investment unnecessary.

They increase traffic fatalities

The University of Chicago study mentioned earlier estimated that Uber and Lyft increased traffic fatalities last year by an astonishing 1,100 - an enormous human toll. The study also found, surprisingly, that Uber and Lyft have no effect on drunk driving.

In addition, Uber and Lyft require basically no safety training for their drivers at all. In fact, the presence of these companies has motivated cities like Toronto to eliminate safety training requirements the city previous required for taxi drivers, in order to ostensibly level the playing field.

They hoard their data

One qualification with this list: Much of the information we have about Lyft and Uber is imperfect. The two companies make it difficult to study the social impacts of their activities because they jealously guard their data.

Last year, when Barrios released a study showing a lot of negative impacts from Uber and Lyft, Lyft corporate attacked the study calling it "deeply flawed."

But Barrios had to use Google search numbers to estimate Uber and Lyft penetration in certain markets because even academic researchers don't have access to Uber and Lyft's raw trip data. If Uber and Lyft are honest in their denials, releasing their data could help disprove it. But so far, they have mostly refused.

Oh, and one more thing...

These are just the transportation related drawbacks. To say nothing of these companies treatment of their employees, or the behavior of their top management or their huge financial losses.

# data[].attributes.attachment_link.title
All the Bad Things About Uber and Lyft In One Simple List

# data[].attributes.attachment_link.description
Here's the latest evidence that Uber and Lyft are destroying our world: Students at the University of California Los Angeles are taking an astonishing 11,000 app-based taxi trips every week that begin and end within the boundaries of the campus.

# data[].attributes.attachment_link.readable_text
Contributed Photo / DoorDash/contributed

One sunny day last summer I noticed my teenage daughter and her friends, while relaxing poolside in our suburban backyard, placing food delivery orders via their smartphones.

I assumed they were just calling in a to-go order and that one of them would go pick it up. I was surprised to see, however, less than an hour later a rather unkempt vehicle pull into my driveway and a smiling, but harried, young African American woman walk up with a DoorDash hot bag to deliver the food to the much-younger-than-her kids in my backyard.

I felt uncomfortable with the whole scene and thought about it on and off for months afterward - trying to understand what specifically about the event made me uneasy. I had to give it that length of time because I knew if I said (or posted) anything immediately, it would probably get misconstrued by my friends, neighbors and family as elitist or even racist.

Rest assured, my issue was not about my perception of a beat-up old Honda driven by a black woman showing up in my admittedly privileged gated community - in fact, quite the contrary.

The issue is about socioeconomics and classism, very much like what I saw and grew up around in Mumbai, India, as a child.

American venture capitalists and their host of cheerleaders, from investors to media, to the very startups themselves, beat a steady drum of how all such endeavors are a healthy sign of entrepreneurial innovation. They convince us that this is technology at its finest and our young college graduates are being hired to engineer "global solutions" - that this type of "disruption" is good.

When it comes to many aspects of the "sharing" or "peer-to-peer" economies (the euphemisms applied by esteemed analysts and investors), this sort of enterprise is really nothing new. The apps and digital tools that support it may be new, and the new generation of American users may be new to the concept, but anyone who has spent time in countries with enormous wage disparity will tell you these services are not innovative.

They are, in fact, the signs of emerging oppression and growing social stratification. These app-based services are virtual canaries in the coal mine of a country that is foundering and struggling to make meaningful work for its young people.

Forty years ago in India, there were no apps, yet you could have just about any food or service at your doorstep in minutes. A whistle or catcall from the apartment balcony, a quick shout to your house servant, a hand gesture to the man with a basket on his head, and you had a hot lunch, car service, shave or even currency exchange at your door.

This sort of personalized service still exists in India today (a reason many app-based similars haven't taken off there) and is far more efficient and integral to Indian society than the novelty it provides in the United States. But in India, there are no corporate behemoths or T-shirt-wearing Sand Hill Road billionaires with their hands in the pockets of the on-the-ground workers. It is self-employment and small business at its most basic level: survival.

Countries such as India, China, the Philippines and many others in the East have always had that elusive "scale" that venture capitalists are constantly chirping about when it comes to the "sharing" economy. The reason is simple - the haves can afford to pay the have-nots for the convenience of having their hair cut or earwax removed on their porch. (Yes, those are real and actual services.) With a market size of billions, scale happens quickly.

The difference, however, between food delivery in Mumbai and San Francisco is that in India it is the uneducated and impoverished class who have realized serving the wealthier is their only hope for survival and upward mobility. It is one step up from begging, two steps up from perishing - which there is plenty of in India as well.

There is a big gap between launching new business ventures and necessity - the entrepreneur is trying to dream, while the poor man serving out of need is trying to wake up from his nightmare. There are, and have been, billions of people in India and other developing nations who served and continue to serve in undignified occupations merely for the hope their children will not have to follow in their footsteps.

In America, and the American form of capitalism, we are led to believe, through flashy apps and crafty logos, that Uber, DoorDash, Postmates and so many more "peer" services are the seedlings of the entrepreneur and the progress of society. Yet look closely at those who are actually performing the service - they are simply trying to avoid the rapid descent into the impoverished class. Most Uber drivers will tell you they also drive for Lyft and participate in other delivery-based services. They will also tell you that this is not a job they do for fun or virtue, but simply as a means to make ends meet.

I have met immigrants with equivalent to an M.D. who are now resigned to earning some algorithmic percentage of whatever surge value a Silicon Valley startup has charged to the beneficiary of the service. Unlike those underdeveloped nations, here the service provider doesn't even set his own price, let alone handle his own transaction. You are last in line to get paid for a job you never dreamed about.

What is certain is that everyone using these services would never wish for their children to pursue such livelihoods.

And it is also certain that we all nod in agreement, while attending our respective churches and temples, when told that it is the rich who should serve the poor, that the fortunate should bring food to the less fortunate.

While we probably are fast creating a new super-subclass of worker in America, we shouldn't feel sorry for those workers. Except in the most extreme circumstances of famine and illness, the world's poor are, in fact, much happier and stronger from having faced adversity than the privileged they serve.

They know how to live below their means, work harder, cook their own food, and do more with less in all aspects. It is the users of these divisive services and apps who ought to be worried. Americans stopped slowing down to cook their own meals nearly 75 years ago. Fast food became the rare treat, then the norm, and now is no longer fast enough - it must arrive with the swipe of a finger.

And for what? So our young minds can spend more time working and consuming - building "scale" - with disregard to health, nature and self-sufficiency. The Roman philosopher Seneca, even in A.D. 14, wrote about the man so wealthy and served that he had to ask his servant whether he was standing or sitting.

Perhaps what America really needs to invest in is a new type of VC, as in Virtue Consciousness.

Chirag Asaravala lives in Alamo. To comment, submit your letter to the editor at SFChronicle.com/letters.

# data[].attributes.attachment_link.title
Is 'sharing economy' tech prowess - or oppression?

# data[].attributes.attachment_link.description
One sunny day last summer I noticed my teenage daughter and her friends, while relaxing poolside in our suburban backyard, placing food delivery orders via their smartphones. I assumed they were just calling in a to-go order and that one of them would go pick it up.

# data[].attributes.attachment_link.readable_text
In 2015, when Lazarus Liu moved home to China after studying logistics in the United Kingdom for three years, he quickly noticed that something had changed: Everyone paid for everything with their phones. At McDonald's, the convenience store, even at mom-and-pop restaurants, his friends in Shanghai used mobile payments. Cash, Liu could see, had been largely replaced by two smartphone apps: Alipay and WeChat Pay. One day, at a vegetable market, he watched a woman his mother's age pull out her phone to pay for her groceries. He decided to sign up.

To get an Alipay ID, Liu had to enter his cell phone number and scan his national ID card. He did so reflexively. Alipay had built a reputation for reliability, and compared to going to a bank managed with slothlike indifference and zero attention to customer service, signing up for Alipay was almost fun. With just a few clicks he was in. Alipay's slogan summed up the experience: "Trust makes it simple."

Alipay turned out to be so convenient that Liu began using it multiple times a day, starting first thing in the morning, when he ordered breakfast through a food delivery app. He realized that he could pay for parking through Alipay's My Car feature, so he added his driver's license and license plate numbers, as well as the engine number of his Audi. He started making his car insurance payments with the app. He booked doctors' appointments there, skipping the chaotic lines for which Chinese hospitals are famous. He added friends in Alipay's built-in social network. When Liu went on vacation with his fiancée (now his wife) to Thailand, they paid at restaurants and bought trinkets with Alipay. He stored whatever money was left over, which wasn't much once the vacation and car were paid for, in an Alipay money market account. He could have paid his electricity, gas, and internet bills in Alipay's City Service section. Like many young Chinese who had become enamored of the mobile payment services offered by Alipay and WeChat, Liu stopped bringing his wallet when he left the house.

If you live in the United States, you are by now accustomed to relinquishing your data to corporations. Credit card companies know when you run up bar tabs or buy sex toys. Facebook knows if you like Tasty cooking videos or Breitbart News. Uber knows where you go and how you behave en route. But Alipay knows all of these things about its users and more. Owned by Ant Financial, an affiliate of the massive Alibaba corporation, Alipay is sometimes called a super app. Its main competitor, WeChat, belongs to the social and gaming giant Tencent. Alipay and WeChat are less like individual apps than entire ecosystems. Whenever Liu opened Alipay on his phone, he saw a neat grid of icons that vaguely resembled the home screen on his Samsung. Some of the icons were themselves full-blown third-party apps. If he wanted to, he could access Airbnb, Uber, or Uber's Chinese rival Didi, entirely from inside Alipay. It was as if Amazon had swallowed eBay, Apple News, Groupon, American Express, Citibank, and YouTube-and could siphon up data from all of them.

One day a new icon appeared on Liu's Alipay home screen. It was labeled Zhima Credit (or Sesame Credit). The name, like that of Alipay's parent company, evoked the story of Ali Baba and the 40 thieves, in which the words open sesame magically unseal a cave full of treasure. When Liu touched the icon, he was greeted by an image of the Earth. "Zhima Credit is the embodiment of personal credit," the text underneath read. "It uses big data to conduct an objective assessment. The higher the score, the better your credit." Further down was a button that read, in clean white characters, "Start my credit journey." He tapped.

In 1956 an electrical engineer named Bill Fair and a mathematician named Earl Isaac started a small tech company out of a San Francisco apartment. They named it Fair, Isaac and Co., but the business eventually came to be known, for short, as FICO. Their chief innovation was using computer-driven statistical analysis to translate people's personal details and financial history into a simple score, predicting how likely they were to pay back loans. Before FICO, credit bureaus relied in part on gossip culled from people's landlords, neighbors, and local grocers. Applicants' race could be counted against them, as could messiness, poor morals, and "effeminate gestures." Algorithmic scoring, Fair and Isaac argued, was a more equitable, scientific alternative to this unfair reality. FICO's approach eventually caught on among the credit bureaus-TransUnion, Experian, and Equifax-and in 1989 FICO introduced the credit score we know today, enabling millions of Americans to take out mortgages and rack up credit card bills.

During the past 30 years, by contrast, China has grown to become the world's second largest economy without much of a functioning credit system at all. The People's Bank of China, the country's central banking regulator, maintains records on millions of consumers, but they often contain little or no information. Until recently, it was difficult to get a credit card with any bank other than your own. Consumers mainly used cash. As housing prices spiked, this became increasingly untenable. "Now you need two suitcases to buy a house, not just one," says Zennon Kapron, who heads the financial tech consultancy Kapronasia. Still, efforts to establish a reliable credit system foundered because China lacked a third-party credit scoring entity. What it did have by the end of 2011 were 356 million smartphone users.

On the screen was a button that read, "Start my credit journey." Liu tapped.

That year, Ant Financial launched a version of Alipay with a built-in scanner for reading QR codes-square, machine-readable labels that can hold over 100 times more information than a standard bar code. (WeChat Pay, which launched in 2013, has a similar built-in scanner.) Scanning a QR code can bring you to a website, or pull up an app, or connect you to a person's social media profile. Codes started showing up on graves (scan to learn more about the deceased) and the shirts of waiters (scan to tip). Beggars printed out QR codes and set them out on the street. The codes linked the online and offline realms on a scale not seen anywhere else in the world. That first year with the QR scanner, Alipay mobile payments reached nearly $70 billion.

In 2013, Ant Financial executives retreated to the mountains outside Hangzhou to discuss creating a slew of new products; one of them was Zhima Credit. The executives realized that they could use the data-collecting powers of Alipay to calculate a credit score based on an individual's activities. "It was a very natural process," says You Xi, a Chinese business reporter who detailed this pivotal meeting in a recent book, Ant Financial. "If you have payment data, you can assess the credit of a person." And so the tech company began the process of creating a score that would be "credit for everything in your life," as You explains it.

Ant Financial wasn't the only entity keen on using data to measure people's worth. Coincidentally or not, in 2014 the Chinese government announced it was developing what it called a system of "social credit." In 2014, the State Council, China's governing cabinet, publicly called for the establishment of a nationwide tracking system to rate the reputations of individuals, businesses, and even government officials. The aim is for every Chinese citizen to be trailed by a file compiling data from public and private sources by 2020, and for those files to be searchable by fingerprints and other biometric characteristics. The State Council calls it a "credit system that covers the whole society."

For the Chinese Communist Party, social credit is an attempt at a softer, more invisible authoritarianism. The goal is to nudge people toward behaviors ranging from energy conservation to obedience to the Party. Samantha Hoffman, a consultant with the International Institute for Strategic Studies in London who is researching social credit, says that the government wants to preempt instability that might threaten the Party. "That's why social credit ideally requires both coercive aspects and nicer aspects, like providing social services and solving real problems. It's all under the same Orwellian umbrella."

In 2015 Ant Financial was one of eight tech companies granted approval from the People's Bank of China to develop their own private credit scoring platforms. Zhima Credit appeared in the Alipay app shortly after that. The service tracks your behavior on the app to arrive at a score between 350 and 950, and offers perks and rewards to those with good scores. Zhima Credit's algorithm considers not only whether you repay your bills but also what you buy, what degrees you hold, and the scores of your friends. Like Fair and Isaac decades earlier, Ant Financial executives talked publicly about how a data-driven approach would open up the financial system to people who had been locked out, like students and rural Chinese. For the more than 200 million Alipay users who have opted in to Zhima Credit, the sell is clear: Your data will magically open doors for you.

Participating in Zhima Credit is voluntary, and it's unclear whether or how signing up for it could affect an individual's rating in the government system. Ant Financial declined to let me interview anyone from the company, but did provide a statement from Hu Tao, the general manager of Zhima Credit. "Zhima Credit is dedicated to creating trust in a commercial setting and independent of any government-initiated social credit system," the statement reads. "Zhima Credit does not share user scores or underlying data with any third party including the government without the user's prior consent."

The service "will ensure that the bad people in society don't have a place to go."

Ant Financial did state, however, in a 2015 press release that the company plans "to help build a social integrity system." And the company has already cooperated with the Chinese government in one important way: It has integrated a blacklist of more than 6 million people who have defaulted on court fines into Zhima Credit's database. According to Xinhua, the state news agency, this union of big tech and big government has helped courts punish more than 1.21 million defaulters, who opened their Zhima Credit one day to find their scores plunging.

The State Council has signaled that under the national social credit system people will be penalized for the crime of spreading online rumors, among other offenses, and that those deemed "seriously untrustworthy" can expect to receive substandard services. Ant Financial appears to be aiming for a society divided along moral lines as well. As Lucy Peng, the company's chief executive, was quoted as saying in Ant Financial, Zhima Credit "will ensure that the bad people in society don't have a place to go, while good people can move freely and without obstruction."

I lived in China for the better part of a decade but left in 2014, before mobile payments had fully taken hold. Today $5.5 trillion in mobile payments are made every year in China. (In contrast, the US mobile payments market in 2016 was worth roughly $112 billion.) When I returned for a visit in August, I was determined to be a part of the new cashless China. So I signed up for Alipay and Zhima Credit a few hours after emerging bleary-eyed from the plane. Because I lacked a transaction history, I immediately faced what felt like an embarrassing judgment: a score of 550.

On my first day in Shanghai, I opened Zhima Credit to scan a yellow bike that I found parked at an angle on the sidewalk. China's bike-sharing culture had, like mobile payments, emerged out of nowhere, and Shanghai's streets were littered with brightly colored bikes, deposited wherever the riders pleased. A scan of a bike's QR code revealed a four-digit number that unlocked the back wheel, and a ride across town cost roughly 15 cents. Because of my middling score, however, I had to pay a $30 deposit before I could scan my first bike. Nor could I get deposit-free hotel stays or GoPro rentals, or free umbrella rentals. I belonged to the digital underclass.

In China, anxiety about pianzi, or swindlers, runs deep. How do I know you're not a pianzi? is a question people often ask when salespeople call on the phone or repairmen show up at the door. While my score likely didn't put me in the ranks of pianzi, one promise of Zhima Credit was identifying those who were. Companies can buy risk assessments for users that detail whether they have paid their rent or utilities or appear on the court blacklist. For businesses, such products are billed as time-savers. On the site Tencent Video, I stumbled across an ad for Zhima Credit in which a businessman scrutinizes strangers as he rides the subway. "Everybody looks like a pianzi," he despairs. His employees, trying to guard against shady customers, cover the office conference room walls with photos of lowlifes and criminals. But then-tada!-the boss discovers Zhima Credit, and all of their problems are solved. The staff celebrate by tearing the photos off the wall.

"If your friends are all high-score people, it's good for you. If you have some bad-credit people as friends, it's not nice."

For those with good behavior, Zhima Credit offers perks through cooperation agreements that Ant Financial has signed with hundreds of companies and institutions. Shenzhou Zuche, a car rental company, allows people with credit scores over 650 to rent a car without a deposit. In exchange for this vetting, Shenzhou Zuche shares data, so that if a Zhima Credit user crashes one of the rental company's cars and refuses to pay up, that detail is fed back into his or her credit score. For a while people with scores over 750 could even skip the security check line at Beijing Capital Airport.

Two years after signing up for Zhima Credit, Lazarus Liu was trending up to that number. I met Liu, who is 27 and works at a large corporation, one Saturday afternoon at a mall in central Shanghai, outside a Forever 21. He wore a black shirt, black sneakers, and black Air Jordan shorts, and his face was framed by a fresh fade, with a jolt of black hair that flopped to one side. We walked to a Starbucks filled with young people hunched over their phones, sipping peach iced teas and green tea Frappuccinos. Liu claimed the last open table.

Liu told me that he chose his English name, Lazarus, after converting to Catholicism three years ago, but that his religion was mostly a private affair. He saw his Zhima Credit score the same way; it revealed something about him, but he kept those insights mostly to himself. He rarely checked his score-it just lurked in the background of the Alipay app on his Samsung-and because it was good, he didn't have to. After starting at 600 out of a possible 950 points, he had reached 722, a score that entitled him to favorable terms on loans and apartment rentals, as well as showcasing on several dating apps should he and his wife ever split up. With a few dozen more points, he could get a streamlined visa to Luxembourg, not that he was planning such a trip.

As Liu amassed a favorable transaction and payment history on Alipay, his score naturally improved. But it could go down if he neglected to pay a traffic fine, for example. And the privileges that come with a high score might someday be revoked for behaviors that have nothing to do with consumer etiquette. In June 2015, as 9.4 million Chinese teenagers took the grueling national college entrance examination, Hu Tao, the Zhima Credit general manager, told reporters that Ant Financial hoped to obtain a list of students who cheated, so that the fraud could become a blight on their Zhima Credit records. "There should be consequences for dishonest behavior," she avowed. The good were moving without obstruction. A threat hung over the rest.

Alipay knows that at 1 pm on the afternoon of August 26, I rented an Ofo brand bike outside Shanghai's former French Concession and rode north, parking it across from Jing'an Temple. It knows that at 1:24 pm I bought a snack in the mall next to the temple. It knows that afterward I got in a Didi car bound for a neighborhood to the northwest. It knows that at 3:11 pm I disembarked and entered a supermarket, and it knows (because Alibaba owns the supermarket, which accepts only Alipay at checkout) that at 3:36 pm I bought bananas, cheese, and crackers. It knows that I then got in a taxi, and that I arrived at my destination at 4:01 pm. It knows the identification number of the taxi that drove me there. It knows that at 4:19 pm I paid $8 for an Amazon delivery. For three sweet hours-one of which I spent in the swimming pool-it does not know my whereabouts. Then it knows that I rented another Ofo bike outside a hotel in central Shanghai, cycled 10 minutes, and at 7:11 pm parked it outside a popular restaurant. Because Ant Financial is a strategic investor in Ofo, Alipay might know the route I took.

The algorithm behind my Zhima Credit score is a corporate secret. Ant Financial officially lists five broad categories of information that feed into the score, but the company provides only the barest of details about how these ingredients are cooked together. Like any conventional credit scoring system, Zhima Credit monitors my spending history and whether I have repaid my loans. But elsewhere the algorithm veers into voodoo, or worse. A category called Connections considers the credit of my contacts in Alipay's social network. Characteristics takes into consideration what kind of car I drive, where I work, and where I went to school. A category called Behavior, meanwhile, scrutinizes the nuances of my consumer life, zeroing in on actions that purportedly correlate with good credit. Shortly after Zhima Credit's launch, the company's technology director, Li Yingyun, told the Chinese magazine Caixin that spending behavior like buying diapers, say, could boost one's score, while playing videogames for hours on end could lower it. Online speculation held that donating to charity, presumably through Alipay's built-in donation service, was good. But I'm not sure whether the $3 I gave for feeding brown bear cubs qualifies me as a philanthropist or a cheapskate.

I began to check my score obsessively, but because scores are only reevaluated monthly, the number didn't budge. Each time I opened the app, I encountered an alarming orange screen. In the foreground was a gauge in the shape of a half-circle, with a dial showing that I had reached only a quarter of my potential. An article on the portal Sohu.com explained that my score put me in the category of "common folk." The page read: "Cultural level is not high. Retired or nearly retired." In China, where many elderly lost out on years of education during the Cultural Revolution, this was not a compliment. According to Sohu, only 5 percent of the population had scores worse than mine.

To see if I could do anything to pull my score up, I took a taxi one morning to a chic open-air shopping center outside Shanghai's city center to meet with Chen Chen, a 30-year-old illustrator. Chen told a mutual friend on WeChat that she had an "excellent" rating on Zhima Credit, and I wanted to ask her counsel. We bought coffee and walked to an outdoor seating area. Chen wore a button-down shirt open over a white T-shirt and skinny jeans. Her hair was bleached to a straw yellow, and a line of sparkly eye shadow was swept under each eye. On Zhima Credit she clocked in at 710, and her background color was a calming sky blue.

She explained how to boost my score. "They will check what kind of friends you have," she said. "If your friends are all high-score people, it's good for you. If you have some bad-credit people as friends, it's not nice." After signing up for Alipay, I sent friend requests to all of my phone contacts. Only six people accepted. One of my new Alipay friends was a man I used to tutor in English and probably my wealthiest friend in Shanghai. He owned several businesses, a fleet of cars, and a spacious villa in a posh neighborhood. But another was my old tailor, who lived with her family in a single room in a dilapidated house, with piles of cloth obscuring the thin windows. Did the tailor's impact on my score cancel out the businessman's? And was I dragging both of them down?

Chen said she knew the scores of her close friends but not those of acquaintances or work colleagues. There are chat rooms where people with decent scores seek out other high scorers, presumably to boost their ratings. But in general, people simply make assumptions about which contacts have good credit and which are better left unfriended. Users like Chen hadn't yet taken the step of shutting low scorers like me out of their network, she assured me. Zhima Credit was still fairly new, and an acquaintance's low score might still be charitably explained, she said: "Maybe they just haven't used it long enough."

To understand the allure that social engineering holds for Chinese leaders, you have to go back decades, to long before apps and big data. In the years after the 1949 Communist Revolution, the government assigned everyone to local work units, which became the locus of surveillance and control. Individuals spied on their neighbors while also doing everything they could to avoid black marks on their own dang'an, or government files. But maintaining the system required massive state effort and oversight. As economic reforms in the 1980s led millions of people to leave their villages and migrate to cities, the work unit system fell apart. Migration also had a secondary effect: Cities filled up with strangers and pianzi.

It didn't take long for the central government to start thinking about gamifying good behavior. Leaders realized that "if we are going to have a market system that is supposed to be self-guiding, we also need to have self-guiding credit systems," says Rogier Creemers, a scholar of Chinese law at the Leiden Institute for Area Studies in the Netherlands. In the late 1990s, a working group at a Chinese Academy of Sciences institute developed the basic concepts behind the social credit system. But the technology wasn't advanced enough to support the Communist Party's broader political designs.

Nearly a decade ago, I spent a few weeks in Suining, a mostly rural county in Jiangsu province, near Shanghai. Back then, local governance was not subtle. When officials decided to clamp down on people running red lights, they urged citizens to take pictures of offenders, whose images would later be featured on the local television channel.

Then, in 2010, Suining became one of the first areas in China to pilot a social credit system. Officials there began assessing residents on a range of criteria, including education level, online behavior, and how well they followed traffic laws. Each of Suining's 1.1 million citizens older than 14 started out with 1,000 points, and points were added or deducted based on behavior. Taking care of elderly family members earned you 50 points. Helping the poor merited 10 points. Helping the poor in a way that was reported by the media: 15. A drunk driving conviction meant the loss of 50 points, as did bribing an official. After the points were tallied up, citizens were assigned grades of A, B, C, or D. Grade A citizens would be given priority for school admissions and employment, while D citizens would be denied licenses, permits, and access to some social services.

The Suining system was rudimentary, and it briefly sparked a national debate over what criteria should be included in a social credit score. But it provided a testing ground for what could work nationally. And however crude the letter grades were, they were less crude than what they replaced. Social credit in Suining was accompanied by a shift to subtler government messaging.

Since the Suining pilot, dozens of cities have developed their own systems. The power of technology had caught up. Eventually, these systems will be integrated into the nationwide government social credit system, which entails a significant logistical headache. To aid in the task, the government has enlisted Baidu, a big tech company, to help develop the social credit database by the 2020 deadline.

The Chinese tech companies have, in their way, helped to shift the Party's attitude toward digital technologies. When the internet first came to China, bursting into people's lives in the form of blogs and chat rooms, the Party saw it as a threat. Here was a place where people might speak their minds, join together, dissent. Leaders responded to these impulses through censorship and other aggressive tactics. But companies like Ant Financial have shown just how useful digital technologies can be in gathering and deploying information. Instead of merely reacting to content by banning search terms or shutting down websites, the government now collaborates with the private sector on facial and voice recognition technologies, along with artificial intelligence research.

In 2015, a few months after Zhima Credit debuted, Alibaba founder Jack Ma and 14 other executives traveled to the US with President Xi Jinping for his first state visit. Ma, along with leaders at Tencent and Baidu, also sits on the board of the Internet Society of China, a quasi-governmental organization under the direction of the Party.

This strategic nexus is a delicate one, though. In recent months Chinese regulators have taken steps to exert more control over tech companies. Last August, the People's Bank of China ordered mobile and online payment companies to connect to a central government clearinghouse, giving regulators access to transaction data. Two months later, The Wall Street Journal reported that Chinese internet regulators were considering taking a 1 percent stake in the major tech companies.

The dial showed that I had reached only a quarter of my potential. My score put me in the category of "Common Folk."

One possible scenario for a social credit partnership is that the central bank will oversee the development of a broader metric, like a FICO score, while letting companies like Ant Financial collect data to feed into that score. Whatever its eventual structure, the larger social credit system "will definitely be under the government's control," says You Xi, the reporter who wrote the book about Ant Financial. "The government doesn't want this very important infrastructure of the people's credit in one big company's hands."

Chinese people who have been branded untrustworthy are getting the first glimpse of what a unified system might mean. One day last May, Liu Hu, a 42-year-old journalist, opened a travel app to book a flight. But when he entered his name and national ID number, the app informed him that the transaction wouldn't go through because he was on the Supreme People's Court blacklist. This list-literally, the List of Dishonest People-is the same one that is integrated into Zhima Credit. In 2015 Liu had been sued for defamation by the subject of a story he'd written, and a court had ordered him to pay $1,350. He paid the fine, and even photographed the bank transfer slip and messaged the photo to the judge in the case. Perplexed as to why he was still on the list, he contacted the judge and learned that, while transferring his fine, he had entered the wrong account number. He hurried to transfer the money again, following up to make sure the court had received it. This time the judge did not reply.

Although Liu hadn't signed up for Zhima Credit, the blacklist caught up with him in other ways. He became, effectively, a second-class citizen. He was banned from most forms of travel; he could only book the lowest classes of seat on the slowest trains. He could not buy certain consumer goods or stay at luxury hotels, and he was ineligible for large bank loans. Worse still, the blacklist was public. Liu had already spent a year in jail once before on charges of "fabricating and spreading rumors" after reporting on the shady dealings of a vice-mayor of Chongqing. The memory of imprisonment left him stoic about this new, more invisible punishment. At least he was still with his wife and daughter.

Still, Liu took to his blog to stir up sympathy and convince the judge to take him off the list. As of October he was still on it. "There is almost no oversight of the court executors" who maintain the blacklist, he told me. "There are many mistakes in implementation that go uncorrected." If Liu had a Zhima Credit score, his troubles would have been compounded by other worries. The way Zhima Credit is designed, being blacklisted sends you on a rapid downward spiral. First your score drops. Then your friends hear you are on the blacklist and, fearful that their scores might be affected, quietly drop you as a contact. The algorithm notices, and your score plummets further.

Soon after I returned to the US from my visit to China, Equifax, the US credit-reporting agency, announced that it had been hacked. The breach exposed the credit records of some 145 million people. Like many Americans, I got a quick and hard lesson. My credit card number had been stolen a few weeks earlier, but because I had been traveling overseas I hadn't bothered to freeze my credit. When I tried to do so after the hack, I found that an already difficult process had become nearly impossible. Equifax's site was only partly operational, and its phone lines were jammed. Desperate, I signed up for a credit-monitoring service called Credit Karma, which, in exchange for the very same information that I was trying to protect, showed me my score with two of the three major bureaus.

These numbers were communicated to me through a credit gauge similar to Zhima Credit's, down to the color coding of scores. I learned that my credit score had dipped by a few dozen points. There were four or five attempts to take out credit in my name that I didn't recognize.

Most Americans have dozens of scores, and most of them are held by companies that give us no chance to opt out.

Now I had two tracking systems scoring me, on opposite sides of the globe. But these were only the scores that I knew about. Most Americans have dozens of scores, many of them drawn from behavioral and demographic metrics similar to those used by Zhima Credit, and most of them held by companies that give us no chance to opt out. Others we enter into voluntarily. The US government can't legally compel me to participate in some massive data-driven social experiment, but I give up my data to private companies every day. I trust these corporations enough to participate in their vast scoring experiments. I post my thoughts and feelings on Facebook and leave long trails of purchases on Amazon and eBay. I rate others in Airbnb and Uber and care a little too much about how others rate me. There is not yet a great American super app, and the scores compiled by data brokers are mainly used to better target ads, not to exert social control. But through a process called identity resolution, data aggregators can use the clues I leave behind to merge my data from various sources.

Do you take antidepressants? Frequently return clothes to retailers? Write your name in all caps when filling out online forms? Data brokers collect all of this information and more. As in China, you may even be penalized for who your friends are. In 2012, Facebook patented a method of credit assessment that could consider the credit scores of people in your network. The patent describes a tool that arrives at an average credit score for your friends and rejects a loan application if that average is below a certain minimum. The company has since revised its platform policies to prohibit outside lenders from using Facebook data to determine credit eligibility. The company could still decide to get into the credit business itself, though. ("We often seek patents for technology we never implement, and patents should not be taken as an indication of future plans," a Facebook spokesperson said in response to questions about the credit patent.) "You could imagine a future where people are watching to see if their friends' credit is dropping and then dropping their friends if that affects them," says Frank Pasquale, a big-data expert at University of Maryland Carey School of Law. "That's terrifying."

Often, data brokers are flat-out wrong. The data broker Acxiom, which provides some information about what it collects on a site called AboutTheData.com, has me pegged as a single woman with a high school education and a "likely Las Vegas gambler," when in fact I'm married, have a master's degree, and have never even bought a lottery ticket. But it is impossible to challenge these assessments, since we're never told that they exist. I know more about Zhima Credit's algorithm than I do about how US data brokers rate me. This is, as Pasquale points out in his book The Black Box Society, essentially a "one-way mirror."

After I left China, I checked back in with Lazarus Liu on WeChat. He sent me a screenshot of his Zhima Credit score, which had increased by eight points since we met. His screen read "Fantastic," and the font had shifted to soft italics.

We talked about a new facial recognition feature called Smile to Pay that Ant Financial had introduced at a concept restaurant in Hangzhou owned by KFC. The walls of the restaurant were adorned with gigantic white phones. To order, you simply tapped a picture of what you wanted and then showed the phone your face, typing in your cell phone number to confirm payment. First smartphones had eliminated the need for a wallet; now Smile to Pay eliminated the need for a phone. All you needed was your face.

Liu wasn't eager to try Smile to Pay. The "government affairs" page on Zhima Credit's website suggests that Ant Financial partners with local governments throughout China to use its facial recognition capabilities, but that wasn't what made Liu uneasy. While studying abroad, he had played around with Android's Face Unlock feature. His roommate, who shared his square jaw, had been able to unlock his phone a few times. "I feel that it could be unsafe," he messaged me. "I would want to see that it's the real thing." He wrote real thing in English, for emphasis.

While chatting with Liu, I, too, had opened up Zhima Credit. My score had increased by four points. "You still have room to improve," the app informed me delicately. But next to my new score, 554, was a small green arrow. I was on my way up.

Mara Hvistendahl (@marahvistendahl) is a national fellow at New America and a contributing correspondent at Science.
This article appears in the January issue. Subscribe now.

Styling by Nicole Schneider; On-set styling by Cristina Facund

# data[].attributes.attachment_link.title
In China, a Three-Digit Score Could Dictate Your Place in Society

# data[].attributes.attachment_link.description
In 2015, when Lazarus Liu moved home to China after studying logistics in the United Kingdom for three years, he quickly noticed that something had changed: Everyone paid for everything with their phones. At McDonald's, the convenience store, even at mom-and-pop restaurants, his friends in Shanghai used mobile payments.

# data[].attributes.attachment_link.readable_text
Uber will not treat its California drivers as employees, the ride-hail company's head lawyer said Wednesday, despite a new law designed to do just that. The law would create a more stringent test to separate independent contractors from full-time employees. The company's argument rests on a premise that's been a cornerstone since its early days: that Uber is a technology company, not a transportation one.

The California law, called Assembly Bill 5, reaffirms a 2018 California Supreme Court decision that established a three-part test to separate independent contractors from employees, who are eligible for minimum wage, health care benefits, workers' compensation, and other protections. A worker is only an independent contractor if she is not under the control or direction of the company while she's working; if her work is "outside the usual course" of the company's business; and if she is "customarily engaged" in the same kind of work that she does for the company. This three-part test is already in limited use in Massachusetts and New York.

Stay in the know with our Transportation newsletter. Sign up here!

Uber has reason to be worried about the new law, which is awaiting the signature of Governor Gavin Newsom. Analysts with Barclays have estimated that the law would cost Uber $3,625 per California driver, or about $500 million a year. A former Uber executive told The Information that the company's costs would rise by 20 percent if it were forced to reclassify its workers worldwide. The company reported a $5 billion loss last quarter.

Uber Chief Legal Officer Tony West acknowledged that the new test is stringent, but argued that Uber would not have to reclassify its drivers when the law takes effect in January 2020. "Just because the test is hard doesn't mean we will not be able to pass it," West said Wednesday.

West said proving that Uber drivers are performing work "outside the usual course" of the company's business will be its highest legal hurdle. But in a blog post, the lawyer pointed to one place the company has been able to pass the test: Vermont, where Department of Labor officials wrote in a 2017 bulletin that the "usual course of [Uber]'s business is the provision of a technology platform to its drivers, in exchange for a service fee." In other words: Uber's customers are drivers, not riders. Uber just builds the platform that connects independent business owners with a client base.

Elsewhere, though, courts have had little patience for this argument. In California, one federal judge called it "fatally flawed," arguing the company is "no more a 'technology company' than Yellow Cab is a 'technology company' because it uses CB radios to dispatch taxi cabs."

"It seems very clear that Uber is a transportation company, not a technology company, despite the fact that it uses an impressively powerful piece of technology to offer transportation services," says Benjamin Sachs, a professor who teaches labor law at Harvard Law School.

"It seems very clear that Uber is a transportation company, not a technology company."

Benjamin Sachs, Harvard Law School

William Gould, a professor emeritus at Stanford Law School and a former chair of the National Labor Relations Board, says Uber is unmistakably acting as an employer under the rules of the new California test. "Uber is deciding who's suitable to do this work for it, what their wages are to be, what the fare is, and the percentage of the fare the worker will get," he says. "The emperor has no clothes."

Another element of the new law will undoubtedly also keep Uber lawyers busy. An amendment added late in the legislative process gives the state attorney general or the city attorney of any large California city the power to sue companies to comply with the law. As San Francisco city attorney Dennis Herrera-who seems eager to get involved in the legal fight- pointed out Tuesday, "the state doesn't necessarily have the resources to handle every case."

# data[].attributes.attachment_link.title
Why Uber Thinks It Can Still Call Its Drivers Contractors

# data[].attributes.attachment_link.description
Uber will not treat its California drivers as employees, the ride-hail company's head lawyer said Wednesday, despite a new law designed to do just that. The law would create a more stringent test to separate independent contractors from full-time employees.

# data[].attributes.attachment_link.readable_text
Uber's a huge company. Coming from nowhere, it helped rip up and rewrite the rules for intra-city transit. The company, along with Lyft in the United States, have written themselves and their ride sharing business model into culture.

But while Uber is famous for huge growth, towering revenues, and enormous fundraising, something that most don't know is that Uber loses money. A lot of it.

So much, in fact, that its IPO timing is a question mark, its eventual valuation a mystery, and there have been nagging concerns throughout Uber's recent life as to whether it can ever make money. Or if it can while supporting its more exotic operations ( Uber Eats loses money, self-driving cars aren't cheap, and what's this about helicopters?).

So, today, we're going to explain how Uber loses money. After all, the company is famous for being asset-light. By that we mean that Uber's non-employee drives own their cars, and pay for their own gas, and cover most insurance costs.

If Uber isn't operating a huge fleet of cars, how can it possibly lose money? Let's find out.

Losses

Today we're looking at Uber's second quarter 2018 numbers. If you want to follow along at home, we're leaning on this compilation of Uber figures put together by the Wall Street Journal.

Why focus on the the company's second quarter? Because we have yet to see Uber's third quarter figures, and the company's first quarter was impacted by one-time corporate divestments. More simply, the money that Uber got for divesting certain operations makes its first quarter look better than it was.

So, for the second quarter, how much money did Uber lose? Let's find out:

Uber's Q2'2018 adjusted EBITDA (a very relaxed profit metric that doesn't count all costs): -$614 million.

Uber's Q2'2018 non-GAAP profit (the company's net loss, not including the cost of share-based compensation): -$870 million.

Uber's Q2'2018 net loss (the company's profit or loss, inclusive of all costs): -$891 million.

In Uber's case, the stricter the profit metric (the more costs the profit metric takes into account), the worse its quarterly loss. That makes sense!

What you should take away from the above is that no matter which profit metric we decide on, be it net loss or adjusted EBITDA, Uber loses a pile of money each quarter.

How

Now that we understand that Uber does lose money, we want to know how it manages the task.

To understand, we'll start with fares and work our way through the company's costs. So up first? Gross bookings, or the value of all rides on Uber's platform. In the second quarter of 2018, Uber's gross bookings totaled $12 billion. That's a lot of money!

However, Uber doesn't get to keep most of it. In fact, a lot of things need to come out of gross bookings before we can figure out Uber's own revenue. The largest gross bookings cost is what Uber drivers make. In the second quarter, $8.2 billion of the $12 billion in bookings Uber pulled in went to drivers.

Uber also spent $142 million on promotions in the second quarter, paid drivers another $427 million in incentives, spent $27 million on refunds, and paid $411 million in taxes and the like. All told, according to the Wall Street Journal chart, Uber's $12 billion of gross bookings included $9.2 billion in so-called "contra-revenue" expenses.

Now we can figure out Uber's real second quarter revenue: $12 billion (gross bookings) minus $9.2 billion (contra-revenue expenses) equals $2.8 billion in net revenue for Uber. This is the money it takes in the door, from which we'll deduct Uber's cost of revenue (what it costs to deliver product), its operating costs (salaries, office space), and other expenses to determine where all the money went. (Recall that we are trying to understand why Uber loses money; there is no profit at the bottom of this well.)

So Uber has $2.8 billion in Q2 revenue to spend on itself. Its cost of revenue came to $1.3 billion, leaving $1.5 billion in gross profit for the company to use to pay for its operating costs (for more on income statements, check out this post).

Are Uber's operating costs greater than its gross profit? Here are the ridesharing company's costs from its business operations:

So does that chart of costs sum to more than its gross profit of $1.5 billion? Yes. Uber's operating costs come to a total of $2.2 billion. And as Uber's costs are $700 million greater than its available gross profit, it loses money.

In English, the money that Uber collects from fares isn't enough to pay for its revenue and operating costs; therefore, Uber loses money each quarter.

How much money the company loses depends on how you count costs and if you take into account non-cash costs (such as stock compensation). But, by every possible "real" profit metric, Uber is deeply unprofitable.

And that's simply due to it having a higher cost base than it does revenue generating capacity. Now you know!
Editorial note: The original version of this post was more a loose series of notes. I decided to make it clearer and better. This is the improved version.

# data[].attributes.attachment_link.description
Uber's a huge company. Coming from nowhere, it helped rip up and rewrite the rules for intra-city transit. The company, along with Lyft in the United States, have written themselves and their ride sharing business model into culture. But while Uber is famous for huge growth, towering revenues, and enormous fundraising, something that most don't know is that Uber loses money.