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1. Should AI be allowed to make decisions for humans? Why or why not?

2. How does literature explore the danger of giving machines too much power?

3. Who is responsible when AI makes a mistake: the machine, the creator of the technology, or the user?

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1. How have science fiction writers shaped our understanding of artificial intelligence?

2. What do early AI stories reveal about human hopes and fears about technology?

3. How has the concept of AI evolved from fiction to reality, and where do they still overlap?

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This is an accessible intro that breaks down what AI is and how it shows up in our lives. Great for students who are just getting started with the topic.

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What is Artificial Intelligence?

To understand artificial intelligence, or AI, you need to understand what intelligence means. You might think that it means being smart. But intelligence is far more than doing well on tests.

Intelligence is complicated. Scientists who study intelligence still have many questions to answer. Are animals intelligent? Do you inherit intelligence from your parents? Does the size of your brain have anything to do with intelligence?

Scientists don't agree on what intelligence means. And they can't agree on what artificial intelligence means either. Some education organizations have created their own definitions though. AI4All describes AI as "a branch of computer science that allows computers to make predictions and decisions to solve problems."

This backgrounder will help you understand more about AI.

General and Narrow Artificial Intelligence

There are two main kinds of artificial intelligence - general and narrow. It is important to understand the difference between them.

Artificial General Intelligence

The goal of Artificial general intelligence (AGI), or general AI, is to be equal to human intelligence. Many robotic engineers have managed to create human-like robots, but they don't have intelligence equal to humans yet. And experts don't think it will exist any time soon.

General AI is what you usually see in books and movies that take place in a dystopian future. Some examples of this are the Terminator and the movies. You might think this is a pretty new idea. But artists have been imagining the possible uses - and misuses - of AI for a long time.

Mary Shelley was one of the first authors to imagine what might happen if you gave a non-living thing intelligence. Her novel, Frankenstein, was published in 1818. Some people who study the novel call Dr. Frankenstein's creature superintelligent. Superintelligent is a word to describe AI that is more advanced than the smartest humans.

Some scientists try to understand human intelligence so they can help develop general AI. They use digital models to copy human behaviours. They try to understand things like how we learn, or how creativity works. Recently, scientists who study the human brain and scientists who study AI have made progress by getting ideas from each other.

Artificial Narrow Intelligence

Artificial narrow intelligence (ANI) is AI we can experience right now. Sometimes this is also called weak AI. This type of AI means machines can take actions and make decisions automatically in certain situations. Self-driving cars, virtual assistants and personalized audio and video recommendations are examples of narrow AI.

Did you know?

In AI, the word "machine" can mean anything from the software used online or in a mobile app, to a humanoid robot. There aren't many humanoid robots, but they sure are impressive!

A Brief History of Artificial intelligence

John McCarthy and Marvin Minsky first used the phrase "artificial intelligence" in 1955. Then they thought that general AI would be possible in a few years. But the technology needed to research AI was very expensive. AI research has sped up recently because scientists have been able to use machine learning. Machine learning is much faster than computer programming by humans.

Machine Learning

Machine learning (ML) is a smaller part of AI. It includes various tools and methods that allow machines to learn without humans programming them. Humans input large amounts of data into an ML system. Then they give the system a desired output. The ML system tries to find the relationship between the two. The machine then produces a specific algorithm from the given output and input.

For example, social media platforms use recommendation systems. These systems choose what content to show you. The input data includes your browsing history, your likes and your friends' preferences. It also includes your personal information like age and gender. The desired output is the time you spend on that platform. The longer you spend there, the more money a social media company can make by advertising to you. So the machine's job is to find out what content will make you stay. ​​​​

Did you know?
An algorithm is a series of ordered, logical and clear rules or instructions needed to solve a problem or achieve a goal.

Here are just a few of the major milestones in artificial intelligence:

1956
The phrase Artificial Intelligence was first published by computer scientists John McCarthy and Marvin Minsky.

2011
IBM's Watson computer wins at the TV game show Jeopardy. This proved it could understand complex human language, because questions included word play.

2017
CIFAR leads the development of a Pan-Canadian Artificial Intelligence Strategy, the world's first national AI strategy.

Did you know?

The HAL 9000 computer in the movie 2001: A Space Odyssey was based on experts' opinions about artificial intelligence in 1968.

AI Begins With Math

Data has a story to tell. If you know how to look for it! In the past, people have looked for patterns and trends in data. When there is a lot of data, this can be difficult. But computers can speed up the process.

Computers can do the calculations needed to make mathematical models. They can also create visualizations of data. Visualizations are different ways to represent data, like charts and graphs. People can see patterns and trends more easily in visualizations.

Why do we want to find patterns and trends? One reason is to make predictions. Predictive models help humans make decisions in areas like medicine and the environment.

So how much data is out there? Short answer - a lot! People collect a lot of data because of the internet and other communication tools. This is often called "Big Data." Scientists have had to invent bigger and bigger computing systems to process all this data. Cloud computing is a good example. It was developed because regular computers could not handle the amount of data they received. Machine learning systems were also needed to help us learn from the data.

All this data means that the relationship between humans and computers has changed. In the past, humans used computers to help organize and represent data. But humans had to make sense of it. Now, machines are figuring out how to understand and explain vast amounts of data. And humans are helping them. Computers can't do everything themselves. There are many skills they don't have, like thinking ahead and combining different ideas.

Optimizing the Human-Computer Relationship

"Human in the loop" machine learning is a way to combine machine and human strengths. A Computer's strength is its computing speed. Humans will never be able to compute as fast as computers. Human strengths include creativity and critical thinking. Humans have the ability to look at a problem from different points of view.

This means humans have many important roles besides building AI tools. For example, a human engineer can participate in testing an airplane's safety mechanism. Human resources experts can study an AI hiring tool to look for possible biases. And medical experts can help make sure an AI tool is accurate for all patients.

Did you know?

Bias can happen when data used in AI does not reflect reality. For example, a set of medical data needs to represent the characteristics of a population. These include things like age, gender and ethnicity. If it does not, then this data can't be used to make predictions for the whole population.

Artificial Intelligence Opportunities

AI is a great tool. It can help us find solutions to many problems. This is true in any area where we use data, which is almost everywhere! These are just a few of the ways AI can help us reach some of the United Nations Sustainable Development Goals (SDGs).

SDG 3 - Good Health and Well-being

Some of the most successful ML and AI applications are in the field of medicine. AI and machine learning are being used in research, like fighting cancer or searching for vaccines. Some doctors use AI diagnostic tools to help identify illnesses faster. They can also use AI tools to take notes, analyze their discussions with patients, and enter information directly into medical record systems.

AI can help improve human health in many other areas too. It can analyse social media posts for signs of mental illness. It can also reduce injuries on construction sites, and much more!

SDG 1 - No poverty and SDG 2 - No Hunger

AI tools can be used by governments to find ways to reduce poverty and hunger. For example, they can help farmers detect pests, diseases and poor nutrition in plants. Or they can help to reduce food waste. AI can also be used to help predict and respond to natural disasters, or find out where poverty is happening using satellite images.

SDG 13 Climate Action, SDG 14 Life Below Water and SDG 15 Life on Land

AI can provide much-needed tools to help us protect the environment and fight climate change. AI can use satellite images and data analysis to help scientists identify trends and work on solutions. For example, AI can be used to identify where forest fires could happen, before they start. It can also be used to understand and protect endangered species. Scientists can even combine robotics and AI visual recognition systems to create a robot to help protect ecosystems from invasive species.

Did you know?

The Association for Computing Machinery A.M. Turing Award is sometimes called "the Nobel prize of computer science". In 2018, the award went to three Canadian researchers. Their innovative work on neural networks will help computers learn even faster! Soon after their win, the Canadian government helped fund new hubs for AI development in Quebec, Ontario and Alberta.

Artificial Intelligence Concerns

Should we be afraid that artificial intelligence might develop beyond human intelligence? Or that it could become a threat to humans? Experts have been debating these issues for a long time. Some people only see AI's potential for innovation and problem-solving. Some people, like Elon Musk and Bill Gates, think that AI could be dangerous. They think humans should be very careful about how they develop and use it. That's why scientists and governments are working together to create regulations for AI. These rules will make sure people develop AI applications with human needs and well-being in mind.

Superintelligence

Some scientists are concerned about the speed of AI development. Computers are now so fast that superintelligence is a real possibility. Superintelligence is the idea that machine "brains" could someday be better than human brains in general intelligence.

"Humans, limited by slow biological evolution, couldn't compete and would be superseded by A.I."
Professor Stephen Hawking in a 2014 interview with BBC

But many other scientists think Artificial General Intelligence will not be developed any time soon. They also think there are many other problems we need to think about first.

Job Displacement

AI is already changing the job market. Robots controlled by AI are doing many things that humans used to do. People are worried that they will be replaced by machines.

During the industrial revolution, people worried about the same thing. New factories made many manual jobs obsolete. But factories also created millions of new jobs.

Some experts predict that AI will make some jobs obsolete, but it will also create more jobs. Some of them call this the fourth industrial revolution. This change will affect jobs that involve manual labour. But it will also affect office jobs where people make routine decisions. These tasks can be automated with AI systems.

Ethical considerations

The number of new artificial intelligence technologies has exploded in recent years. AI can offer many advantages, but it can also create problems. Because AI is developing so quickly, many problems are only discovered when a technology is already in use. Also, many governments have not developed regulations for AI.

This is why the United Nations Educational, Scientific and Cultural Organization (UNESCO) started AI: Towards a Humanistic Approach. The goal of this project is to look at the many ethical concerns in AI and help governments make sure AI serves their people in a fair and just way.

Equity, Diversity and Inclusion

When AI is applied to a human population, equity, diversity and inclusion (EDI) issues can arise. If the dataset used does not represent the entire population, AI tools can produce questionable results.

For example, police organizations in the United States use AI facial recognition tools. But this leads to many people from visible minorities being wrongfully arrested. This is because AI systems are not good at identifying people who do not have white skin.

There are also EDI issues to think about when we consider the opportunities created by AI. Governments need to make sure all of their citizens have equal access to job opportunities. One way to do this is to help all students learn about AI in school. Also, AI already plays a role in our daily lives. So, it's important for all students to learn about it so they can become informed citizens.

Transparency

It is very important to understand how AI systems work. This is called AI explainability. Explainability is about being able to understand how an AI system gets its results. The firms that create AI systems want to protect their intellectual property. And sometimes AI algorithms are so complex that it's almost impossible to understand the processes involved. This is a problem when people want to understand the decision-making process, or figure out how biases arise. This is called the black box effect. Scientists around the world are studying it to find solutions.

Experts also worry about who controls the research efforts, funding and discoveries in AI. Right now, a few private companies are responsible for most AI research and progress. Some people think all this power should be distributed among more organizations.

Liability

Liability is the legal responsibility of a person or organization in a conflict. But what happens when AI is involved? If a self-driving car is in an accident, who is responsible? The driver, the company that developed the software, or the AI engineer?

In conclusion...

The field of AI is especially important for young people. Its impact on their lives will only increase. But becoming more familiar with AI does not have to mean taking computer science classes. You can learn about AI in many different ways.

To make sure Canadian youth are prepared for a future with AI, they are encouraged to:

develop awareness of its presence and recognize when it is used

understand the potential of AI so they can use it to solve problems

understand the limitations and ethical implications of AI so they can make sure that future developments integrate these considerations into design and monitoring

reflect on the impact AI development could have on their own agency and think about how it could affect their education paths and career choices

become informed citizens who can be involved in the responsible use of AI in many fields

We may not know exactly what the future holds, but we can be pretty sure that AI will play an important role. And many scientists in Canada are working hard to figure out how humans and machines can build a better world together. Will you join them?

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Learn about the fast-moving field of artificial intelligence and what it can mean for students.

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In this foundational sci-fi story, a robot develops its own belief system and basically tells humans they’re wrong. It gets students thinking about what happens when machines don’t follow the rules we expect them to.

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Machine Learning: How Artificial Intelligence Learns by ReadyAI (Picturebook)

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Machine Learning: How Artificial Intelligence Learns by ReadyAI (Picturebook)

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This cute picturebook helps younger students understand how machines learn. It's perfect for introducing AI concepts without overwhelming students.

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Machine Learning: How Artificial Intelligence Learns (Fun Picture Book for K-2, AI+ME Series, Big Idea 3)

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Is your child interested in sci-fi, robots, or video games? Is your kid fascinated by smart home assistants and the prospect of self-driving cars? Time to turn that enthusiasm into action and engage with the exciting world of artificial intelligence! AI+Me is a series designed to introduce the…

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The Last Curiosity by Lucy Tan (Short Story)

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The Last Curiosity by Lucy Tan (Short Story)

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This story imagines a future where AI remains even after humanity fades, providing commentary on the richness of the human experience.

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This dystopian classic is basically a warning about what happens when we stop thinking for ourselves.

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A new recording of Ray Bradbury's timeless classic Fahrenheit 451 narrated by Penn Badgley!

Nearly seventy years after its original publication, Ray Bradbury's internationally acclaimed novel Fahrenheit 451 stands as a classic of world literature set in a bleak, dystopian future. Today its message has grown more relevant than ever before.

Guy Montag is a fireman. His job is to destroy the most illegal of commodities, the printed book, along with the houses in which they are hidden. Montag never questions the destruction and ruin his actions produce, returning each day to his bland life and wife, Mildred, who spends all day with her television "family." But when he meets an eccentric young neighbor, Clarisse, who introduces him to a past where people didn't live in fear and to a present where one sees the world through the ideas in books instead of the mindless chatter of television, Montag begins to question everything he has ever known.

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Amazon.com: Fahrenheit 451: A Novel (Audible Audio Edition): Ray Bradbury, Penn Badgley, Simon & Schuster Audio: Books

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Technology Haiku by John P. Curtin (Poem)

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Technology Haiku by John P. Curtin (Poem)

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A succint and pithy poem that encapsulates a larger understanding of how technology shapes our world.

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1. What are the hidden environmental costs of creating and running artificial intelligence?

2. Can AI be part of the solution to climate change? Or is it part of the problem?

3. How do authors warn us about the price of progress?

4. What responsibility do developers and users have for the environmental impact of the tech they use?

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1. Who benefits from AI use?

2. How can AI support human creativity instead of replacing it?

3. When does a tool become too powerful to control?

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A short explainer that makes the process of how AI learns feel approachable for visual learners.

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A quick walkthrough of how AI has developed over time, from early dreams to today’s reality. Helpful for providing context before diving deep.

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[SUPPORTIVE TEXT 1] Teen and Young Adult Perspectives on Generative AI

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[SUPPORTIVE TEXT 1] Teen and Young Adult Perspectives on Generative AI

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Real thoughts from real teens about using AI in their lives and classrooms. It feels authentic and sparks great conversation.

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[SUPPORTIVE TEXT 2] How can we tell whether we are talking to a computer or a person?

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[SUPPORTIVE TEXT 2] How can we tell whether we are talking to a computer or a person?

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Explains the famous idea of whether a machine can "pass" as human. Really useful for asking bigger questions about identity and deception.

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1. Students will create two timelines (digital or physical) that shows the history and evolution of AI- one from actual history, and one fictional one from one of the pieces of literature we read (Fahrenheit 451, Reason, or The Last Curiosity). It should includes quotes from the text as well as visuals.

2. Students will create a podcast episode with a partner where they discuss how one of the sci-fi authors would feel about the state of technology, specifically AI advancements, today. How accurate were their predictions?

3. Students will write a 3 stanza haiku cycle, inspired by Curtin's "Technology Haiku" to respond to one or more of the inquiry questions. Each verse should be paired with a visual symbol (produced either digitally or with physical material).

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The Perfect Match by Ken Liu (Short Story)

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The Perfect Match by Ken Liu (Short Story)

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In this story, an AI assistant controls every part of your life. Perfect for discussing privacy, freedom, and control.

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Sai woke to the rousing first movement of Vivaldi's violin concerto in C minor, "Il Sospetto."

He lay still for a minute, letting the music wash over him like a gentle Pacific breeze. The room brightened as the blinds gradually opened to the sunlight. Tilly had woken him right at the end of a light sleep cycle, the optimal time. He felt great: refreshed, optimistic, ready to jump out of bed.

Which is what he did next. "Tilly, that's an inspired choice for a wake-up song."

"Of course," Tilly spoke from the camera/speaker in the nightstand. "Who knows your tastes and moods better than I?" The voice, though electronic, was affectionate and playful.

Sai went into the shower.

"Remember to wear the new shoes today," Tilly now spoke to him from the camera/speaker in the ceiling.

"Why?"

"You have a date after work."

"Oh, the new girl. Shoot, what's her name? I know you told me-"

"I'll bring you up to speed after work. I'm sure you'll like her. The compatibility index is very high. I think you'll be in love for at least six months."

Sai looked forward to the date. Tilly had also introduced him to his last girlfriend, and that relationship had been wonderful. The break up afterwards was awful, of course, but it helped that Tilly had guided him through it. He felt that he had matured emotionally, and after a month on his own, was ready to start a new relationship.

But first he still had to get through the workday. "What do you recommend for breakfast this morning?"

"You are scheduled to attend the kickoff meeting for the Davis case at eleven, which means you'll get a lunch paid for by the firm. I suggest you go light on the breakfast, maybe just a banana."

Sai was excited. All the paralegals at Chapman Singh Stevens & Rios lived for client lunches, made by the firm's own executive chef. "Do I have time to make my own coffee?"

"You do. Traffic is light this morning. But I suggest you go to this new smoothie place along the way instead-I can get you a coupon code."

"But I really want coffee."

"Trust me, you'll love the smoothie."

Sai smiled as he turned off the shower. "Okay, Tilly. You always know best."

***

Although it was another pleasant and sunny morning in Las Aldamas, California-68 degrees Fahrenheit-Sai's neighbor Jenny was wearing a thick winter coat, ski goggles, and a long, dark scarf that covered her hair and the rest of her face.

"I thought I told you I didn't want that thing installed," she said as he stepped out of his apartment. Her voice was garbled through some kind of electronic filter. In response to his questioning look, she gestured to the camera over Sai's door.

Talking to Jenny was like talking to one of his grandmother's friends who refused to use Centillion email or get a ShareAll account because they were afraid of having "the computer" know "all their business"-except that as far as he could tell, Jenny was his age. She had grown up a digital native, but somehow had missed the ethos of sharing.

"Jenny, I'm not going to argue with you. I have a right to install anything I want over my door. And I want Tilly to keep an eye on my door when I'm away. Apartment 308 was just burglarized last week."

"But your camera will record visitors to my place, too, because we share this hallway."

"So?"

"I don't want Tilly to have any of my social graph."

Sai rolled his eyes. "What do you have to hide?"

"That's not the point-"

"Yeah, yeah, civil liberties, freedom, privacy, blah blah blah . . . "

Sai was sick of arguing with people like Jenny. He had made the same point countless times: Centillion is not some big scary government. It's a private company, whose motto happens to be "Make things better!" Just because you want to live in the dark ages doesn't mean the rest of us shouldn't enjoy the benefits of ubiquitous computing.

He dodged around her bulky frame to get to the stairs.

"Tilly doesn't just tell you what you want," Jenny shouted. "She tells you what to think. Do you even know what you really want any more?"

Sai paused for a moment.

"Do you?" she pressed.
What a ridiculous question. Just the kind of pseudo-intellectual anti-technology rant that people like her mistake for profundity.
He kept on walking.

"Freak," he muttered, expecting Tilly to chime in from his phone earpiece with some joke to cheer him up.

But Tilly said nothing.

***

Having Tilly around was like having the world's best assistant:

- "Hey Tilly, do you remember where I kept that Wyoming filing with the weird company name and the F merger from maybe six months ago?"

- "Hey Tilly, can you get me a form for Section 131 Articles? Make sure it's a form that associates working with Singh use."

- "Hey Tilly, memorize these pages. Assign them these tags: 'Chapman,' 'favors buyer,' 'only use if associate is nice to me.'"

***

For a while, Chapman Singh had resisted the idea of allowing employees to bring Tilly into the office, preferring their proprietary corporate AI system. But it proved too difficult to force employees to keep their personal calendars and recommendations rigidly separate from work ones, and once the partners started to violate the rules and use Tilly for work, IT had to support them.

And Centillion had then pledged that they would encrypt all corporate-derived information in a secure manner and never use it for competitive purposes-only to give better recommendations to employees of Chapman Singh. After all, the mission statement of Centillion was to "arrange the world's information to ennoble the human race," and what could be more ennobling than making work more efficient, more productive, more pleasant?

As Sai enjoyed his lunch, he felt very lucky. He couldn't even imagine what drudgery work would have been like before Tilly came along.

***

After work, Tilly guided Sai to the flower shop-of course Tilly had a coupon-and then, on the way to the restaurant, she filled Sai in on his date, Ellen: educational background, ShareAll profile, reviews by previous boyfriends/girlfriends, interests, likes, dislikes, and of course, pictures-dozens of photos recognized and gathered by Tilly from around the Net.

Sai smiled. As usual, Tilly was right: Ellen was exactly his type.

It was a truism that what a man wouldn't tell his best friend, he'd happily search for on Centillion. Tilly knew all about what kind of women Sai found attractive, having observed the pictures and videos he perused late at night while engaging the Just-For-Me mode in his browser.

And, of course, Tilly would know Ellen just as well as she knew him, so Sai knew that he would be exactly Ellen's type, too.

As predicted, it turned out they were into the same books, the same movies, the same music. They had compatible ideas about how hard one should work. They laughed at each other's jokes. They fed off each other's energy.

Sai marveled at Tilly's accomplishment. Four billion women on Earth, and Tilly seemed to have found the perfect match for him. It was just like hitting the "I Trust You" button on Centillion search back in the early days and how it knew just the right web page to take you to.

Sai could feel himself falling in love, and he could tell that Ellen wanted to ask him to come home with her.

Although everything had gone exceedingly well, if he was being completely honest with himself, it wasn't quite as exciting and lovely as he had expected. Everything was indeed going smoothly, but maybe just a tad too smoothly. It was as if they already knew everything there was to know about each other. There were no surprises, no thrill of finding the truly new.

In other words, the date was a bit boring.

As Sai's mind wandered, there was a lull in the conversation. They smiled at each other and just tried to enjoy the silence.

In that moment, Tilly's voice burst into his earpiece, "You might want to ask her if she likes contemporary Japanese desserts. I know just the place."

Sai realized that though he hadn't been aware of it until just then, he did suddenly have a craving for something sweet and delicate.

Tilly doesn't just tell you what you want. She tells you what to think.

Sai paused.
Do you even know what you really want any more?
He tried to sort out his feelings. Did Tilly just figure out what he hadn't even known he wanted? Or did she put the thought into his head?

The way Tilly filled in that lull . . . it was as if Tilly didn't trust that he would be able to manage the date on his own, as if Tilly thought he wouldn't know what to say or do if she didn't jump in.

Sai suddenly felt irritated. The moment had been ruined.
I'm being treated like a child.
"I know you'll like it. I have a coupon."

"Tilly," he said, "please stop monitoring and terminate auto-suggestions."

"Are you sure? Gaps in sharing can cause your profile to be incomplete-"

"Yes, please cease."

With a beep, Tilly turned herself off.

Ellen stared at him, eyes and mouth wide open in shock.

"Why did you do that?"

"I wanted to talk to you alone, just the two of us." Sai smiled. "It's nice sometimes to just be ourselves, without Tilly, don't you think?"

Ellen looked confused. "But you know that the more Tilly knows, the more helpful she can be. Don't you want to be sure we don't make silly mistakes on a first date? We're both busy, and Tilly-"

"I know what Tilly can do. But-"

Ellen held up a hand, silencing him. She tilted her head, listening to her headset.

"I have the perfect idea," Ellen said. "There's this new club, and I know Tilly can get us a coupon."

Sai shook his head, annoyed. "Let's try to think of something to do without Tilly. Would you please turn her off?"

Ellen's face was unreadable for a moment.

"I think I should head home," she said. "Early workday tomorrow." She looked away.

"Did Tilly tell you to say that?"

She said nothing and avoided looking into his eyes.

"I had a great time," Sai added quickly. "Would you like to go out again?"

Ellen paid half the bill and did not ask him to walk her home.

***

"You're being very antisocial tonight," Tilly said.

"I'm not antisocial. I just didn't like how you were interfering with everything."

"I have every confidence you would have enjoyed the rest of the date had you followed my advice."

Sai drove on in silence.

"I sense a lot of aggression in you. How about some kickboxing? You haven't gone in a while, and there's a 24-hour gym coming up. Take a right here."

Sai drove straight on.

"What's wrong?"

"I don't feel like spending more money."

"You know I have a coupon."

"What exactly do you have against me saving my money?"

"Your savings rate is right on target. I simply want to make sure you're sticking to your regimen for consumption of leisure. If you over-save, you'll later regret that you didn't make the most of your youth. I've plotted the optimum amount of consumption you should engage in daily."

"Tilly, I just want to go home and sleep. Can you shut yourself off for the rest of the night?"

"You know that in order to make the best life recommendations, I need to have complete knowledge of you. If you shut me out of parts of your life, my recommendations won't be as accurate-"

Sai reached into his pocket and turned off the phone. The earpiece went silent.

***

When Sai got home, he saw that the light over the stairs leading up to his apartment had gone out, and several dark shapes skulked around the bottom.

"Who's there?"

Several of the shadows scattered, but one came toward him: Jenny.

"You're back early."

He almost didn't recognize her; this was the first time he'd heard her voice without the electronic filter she normally used. It sounded surprisingly . . . happy.

Sai was taken aback. "How did you know I was back early? You stalking me?"

Jenny rolled her eyes. "Why would I need to stalk you? Your phone automatically checks in and out of everywhere you go with a status message based on your mood. It's all on your ShareAll lifecast for anyone to see."

He stared at her. In the faint glow from the streetlights he could see that she wasn't wearing her thick winter coat or ski goggles or scarf. Instead, she was in shorts and a loose white t-shirt. Her black hair had been dyed white in streaks. In fact, she looked very pretty, if a bit nerdy.

"What, surprised that I do know how to use a computer?"

"It's just that you usually seem so . . ."

"Paranoid? Crazy? Say what's on your mind. I won't be offended."

"Where's your coat and goggles? I've never even seen you without them."

"Oh, I taped over your door camera so my friends could come for a visit tonight, so I'm not wearing them. I'm sorry-"

"You did what?"

"-and I came out here to meet you because I saw that you turned off Tilly, not once, but twice. I'm guessing you're finally ready for the truth."

***

Stepping into Jenny's apartment was like stepping into the middle of a fishing net.

The ceiling, floor, and walls were all covered with a fine metal mesh, which glinted like liquid silver in the flickering light from the many large, hi-definition computer monitors stacked on top of each other around the room, apparently the only sources of illumination.

Besides the monitors, the only other visible furniture appeared to be bookshelves-full of books (the paper kind, strangely enough). A few upside-down, ancient milk crates covered with cushions served as chairs.

Sai had been feeling restless, had wanted to do something strange. But he now regretted his decision to accept her invitation to come in. She was indeed eccentric, perhaps too much so.

Jenny closed the door and reached up and plucked the earpiece out of Sai's ear. Then she held out her hand. "Give me your phone."

"Why? It's already off."

Jenny's hand didn't move. Reluctantly, Sai took out his phone and gave it to her.

She looked at it contemptuously. "No removable battery. Just what you'd expect of a Centillion phone. They should call these things tracking devices, not phones. You can never be sure they're really off." She slipped the phone inside a thick pouch, sealed it, and dropped it on the desk.

"Okay, now that your phone is acoustically and electromagnetically shielded, we can talk. The mesh on the walls basically makes my apartment into a Faraday cage, so cellular signals can't get through. But I don't feel comfortable around a Centillion phone until I can put a few layers of shielding around it."

"I'm just going to say it. You are nuts. You think Centillion spies on you? Their privacy policy is the best in the business. Every bit of information they gather has to be given up by the user voluntarily, and it's all used to make the user's life better-"

Jenny tilted her head and looked at him with a smirk until he stopped talking.

"If that's all true, why did you turn Tilly off tonight? Why did you agree to come up here with me?"

Sai wasn't sure he himself knew the answers.

"Look at you. You've agreed to have cameras observe your every move, to have every thought, word, interaction recorded in some distant data center so that algorithms could be run over them, mining them for data that marketers pay for.

"Now you've got nothing left that's private, nothing that's yours and yours alone. Centillion owns all of you. You don't even know who you are any more. You buy what Centillion wants you to buy; you read what Centillion suggests you read; you date who Centillion thinks you should date. But are you really happy?"

"That's an outdated way to look at it. Everything Tilly suggests to me has been scientifically proven to fit my taste profile, to be something I'd like."

"You mean some advertiser paid Centillion to pitch it at you."

"That's the point of advertising, isn't it? To match desire with satisfaction. There are thousands of products in this world that would have been perfect for me, but I might never have known about them. Just like there's a perfect girl out there for me, but I might never have met her. What's wrong with listening to Tilly so that the perfect product finds the perfect consumer, the perfect girl finds the perfect boy?"

Jenny chuckled. "I love how you're so good at rationalizing your state. I ask you again: If life with Tilly is so wonderful, why did you turn her off tonight?"

"I can't explain it," Sai said. He shook his head. "This is a mistake. I think I'll head home."

"Wait. Let me show you a few things about your beloved Tilly first," Jenny said. She went to the desk and started typing, bringing up a series of documents on a monitor. She talked as Sai tried to scan them and get their gist.

"Years ago, they caught Centillion's traffic-monitoring cars sniffing all the wireless traffic from home networks on the streets they drove through. Centillion also used to override the security settings on your machine and track your browsing habits before they shifted to an opt-in monitoring policy designed to provide better 'recommendations.' Do you think they've really changed? They hunger for data about you-the more the better-and damned if they care about how they get it."

Sai flicked through the documents skeptically. "If this is all true, why hasn't anyone brought it up in the news?"

Jenny laughed. "First, everything Centillion did was arguably legal. The wireless transmissions were floating in public space, for example, so there was no violation of privacy. And the end user agreement could be read to allow everything Centillion did to 'make things better' for you. Second, these days, how do you get your news except through Centillion? If Centillion doesn't want you to see something, you won't."

"So how did you find these documents?"

"My machine is connected to a network built on top of the Net, one that Centillion can't see inside. Basically, we rely on a virus that turns people's computers into relaying stations for us, and everything is encrypted and bounced around so that Centillion can't see our traffic."

Sai shook his head. "You're really one of those tinfoil-hat conspiracy theorists. You make Centillion sound like some evil repressive government. But it's just a company trying to make some money."

Jenny shook her head. "Surveillance is surveillance. I can never understand why some people think it matters whether it's the government doing it to you or a company. These days, Centillion is bigger than governments. Remember, it managed to topple three countries' governments just because they dared to ban Centillion within their borders."

"Those were repressive places-"

"Oh, right, and you live in the land of the free. You think Centillion was trying to promote freedom? They wanted to be able to get in there and monitor everyone and urge them to all consume more so that Centillion could make more money."

"But that's just business. It's not the same thing as evil."

"You say that, but that's only because you don't know what the world really looks like any more, now that it's been remade in Centillion's image."

***

Although Jenny's car was heavily shielded like her apartment, as she and Sai drove, she whispered anyway, as if she were afraid that their conversation would be overheard by people walking by on the sidewalk.

"I can't believe how decrepit this place looks," Sai said as she parked the car by the side of the street. The surface of the road was pockmarked with potholes and the houses around them in ill repair. A few had been abandoned and were falling apart. In the distance they could hear the fading sound of a police siren. This was not a part of Las Aldamas that Sai had ever been to.

"It wasn't like this even ten years ago."

"What happened?"

"Centillion noticed a certain tendency for people-some people, not all-to self-segregate by race when it came to where they wanted to live. The company tried to serve this need by prioritizing different real estate listings to searchers based on their race. Nothing illegal about what they were doing, since they were just satisfying a need and desire in their users. They weren't hiding any listings, just pushing them far down the list, and in any event, you couldn't ever pick apart their algorithm and prove that they were looking at race when it was just one out of hundreds of factors in their magical ranking formula.

"After a while, the process began to snowball, and the segregation got worse and worse. It became easier for the politicians to gerrymander districts based on race. And so here we are. Guess who got stuck in these parts of the town?"

Sai took a deep breath. "I had no idea."

"If you ask Centillion, they'll say that their algorithms just reflected and replicated the desire to self-segregate in some of their users, and that Centillion wasn't in the business of policing thoughts. Oh, they'd claim that they were actually increasing freedom by giving people just what they wanted. They'd neglect to mention that they were profiting off of it through real estate commissions, of course."

"I can't believe no one ever says anything about this."

"You're forgetting again that everything you know now comes filtered through Centillion. Whenever you do a search, whenever you hear a news digest, it's been curated by Centillion to fit what it thinks you want to hear. Someone upset by the news isn't going to buy anything sold by the advertisers, so Centillion adjusts things to make it all okay.

"It's like we're all living in Oz's Emerald City. Centillion puts these thick green goggles over our eyes and we all think everything is a beautiful shade of green."

"You're accusing Centillion of censorship."

"No. Centillion is an algorithm that's gotten out of hand. It just gives you more of what it thinks you want. And we-people like me-think that's the root of the problem. Centillion has put us in little bubbles, where all we see and hear are echoes of ourselves, and we become ever more stuck in our existing beliefs and exaggerated in our inclinations. We stop asking questions and accept Tilly's judgment on everything.

"Year after year, we become more docile and grow more wool for Centillion to shave off and grow rich with. But I don't want to live that way."

"And why are you telling me all this?"

"Because, neighbor, we're going to kill Tilly," Jenny said, giving Sai a hard look, "and you're going to help us do it."

***

Jenny's apartment, with all its windows tightly shut and curtained, felt even more stifling after the car ride. Sai looked around at the flickering screens showing dancing, abstract patterns, suddenly wary. "And just how are you planning to kill Tilly, exactly?"

"We're working on a virus, a cyber weapon, if you want to get all macho about it."

"What exactly would it do?"

"Since the lifeblood of Tilly is data-the billions of profiles Centillion has compiled on every user-that's how we have to take it down.

"Once inside the Centillion data center, the virus will gradually alter every user profile it encounters and create new, fake profiles. We want it to move slowly to avoid detection. But eventually, it will have poisoned the data so much that it will no longer be possible for Tilly to make creepy, controlling predictions about users. And if we do it slowly enough, they can't even go to backups because they'll be corrupted too. Without the data it's built up over the decades, Centillion's advertising revenue will dry up overnight, and poof, Tilly'll be gone."

Sai imagined the billions of bits in the cloud: his tastes, likes and dislikes, secret desires, announced intentions, history of searches, purchases, articles and books read, pages browsed.

Collectively, the bits made up a digital copy of him, literally. Was there anything that was a part of him that wasn't also up there in the cloud, curated by Tilly? Wouldn't unleashing a virus on that be like suicide, like murder?

But then he remembered how it had felt to have Tilly lead him by the nose on every choice, how he had been content, like a pig happily wallowing in his enclosure.

The bits were his, but not him. He had a will that could not be captured in bits. And Tilly had almost succeeded in making him forget that.

"How can I help?" Sai asked.

***

Sai woke to Miles Davis's rendition of "So What."

For a moment, he wondered if the memory of the night before wasn't a dream. It felt so good to be awake, listening to just the song he wanted to hear.

"Are you feeling better, Sai?" Tilly asked.

"I thought I turned you off, Tilly, with a hardware switch."

"I was quite concerned that you stopped all Centillion access to your life last night and forgot to turn it back on. You might have missed your wake-up call. However, Centillion added a system-level fail-safe to prevent just such an occurrence. We thought most users such as yourself would want such an override so that Centillion could regain access to your life."

"Of course," Sai said. So it's impossible to turn Tilly off and keep her off. Everything Jenny said last night was true. He felt a chill tingle on his back.

"There's a gap of about twelve hours during which I couldn't acquire data about you. To prevent degradation in my ability to help you, I recommend that you fill me in."

"Oh, you didn't miss much. I came home and fell asleep. Too tired."

"There appears to have been vandalism last night of the new security cameras you installed. The police have been informed. Unfortunately, the camera did not capture a good image of the perpetrator."

"Don't worry about it. There's nothing here worth stealing anyway."

"You sound a bit down. Is it because of the date last night? It seems that Ellen wasn't the right match for you after all."

"Um, yeah. Maybe not."

"Don't worry: I know just the thing that will put you in a good mood."

***

Over the next few weeks, Sai found it extremely difficult to play his assigned role.

Maintaining the pretense that he still trusted Tilly was crucial, Jenny had emphasized, if their plan was to succeed. Tilly couldn't suspect anything was going on at all.

It seemed simple enough at first, but it was nerve wracking, keeping secrets from Tilly. Could she detect the tremors in his voice, Sai wondered. Could she tell that he was faking enthusiasm for the commercial consumption transactions she suggested?

Meanwhile, he also had a much bigger puzzle to solve before John P. Rushgore, Assistant General Counsel of Centillion, came to Chapman Singh in another week.

Chapman Singh is defending Centillion in a patent dispute with ShareAll, Jenny had said. This is our opportunity to get inside Centillion's network. All you have to do is to get someone from Centillion to plug this into his laptop.

And she had then handed him a tiny thumb drive.

***

Though he still hadn't figured out a plan for plugging the thumb drive into a Centillion machine, Sai was glad to have come to the end of another long day of guarding himself against Tilly.

"Tilly, I'm going jogging. I'll leave you here."

"You know that it's best to carry me with you," Tilly said. "I can track your heart rate and suggest an optimal route for you."

"I know. But I just want to run around on my own a bit, all right?"

"I'm growing quite concerned with your latest tendencies towards hiding instead of sharing."

"There's no tendency, Tilly. I just don't want you to be stolen if I get mugged. You know this neighborhood has become more unsafe lately."

And he turned off the phone and left it in his bedroom.

He closed the door behind him, made sure that the taped-over camera was still taped-over, and gently knocked on Jenny's door.

***

Getting to know Jenny was the oddest thing he'd ever done, Sai realized.

He couldn't count on Tilly to have made sure ahead of time that they would have topics to talk about. He couldn't rely on Tilly's always apropos suggestions when he was at a loss for words. He couldn't even count on being able to look up Jenny's ShareAll profile.

He was on his own. And it was exhilarating.

"How did you figure out everything Tilly was doing to us?"

"I grew up in China," Jenny said, wiping a strand of hair behind her ear. Sai found the gesture inexplicably endearing. "Back then, the government watched everything you did on the Network and made no secret of it. You had to learn how to keep the insanity at bay, to read between the lines, to speak without being overheard."

"I guess we were lucky, over here."

"No." And she smiled at his surprise. He was learning that she preferred to be contrarian, to disagree with him. He liked that about her. "You grew up believing you were free, which made it even harder for you to see when you weren't. You were like frogs in the pot being slowly boiled."

"Are there many like you?"

"No. It's hard to live off the grid. I've lost touch with my old friends. I have a hard time getting to know people because so much of their lives are lived inside Centillion and ShareAll. I can peek in on them once in a while through a dummy profile, but I can never be a part of their lives. Sometimes I wonder if I'm doing the right thing."

"You are," Sai said, and, though there was no Tilly to prompt him, he took Jenny's hand in his. She didn't pull away.

"I never really thought of you as my type," she said.

Sai's heart sank like a stone.

"But who thinks only in terms of 'types' except Tilly?" she said quickly, then smiled and pulled him closer.

***

Finally, the day had come. Rushgore had come to Chapman Singh to prepare for a deposition. He was huddled up with the firm's lawyers in one of their conference rooms all day long.

Sai sat down in his cubicle, stood up, and sat down again. He found himself full of nervous energy as he contemplated the best way to deliver the payload, as it were.
Maybe he could pretend to be tech support, there to perform an emergency scan of his system? Maybe he could deliver lunch, and plug the drive in slyly? Maybe he could pull the fire alarm, and hope that Rushgore would leave his laptop behind?
Not a single one of his ideas passed the laugh test.

"Hey," the associate who had been with Rushgore in the conference room all day was suddenly standing next to Sai's cubicle. "Rushgore needs to charge his phone-you got a Centillion charging cable over here?"

Sai stared at him, dumbfounded by his luck.

The associate held up a phone and waved it at him.

"Of course!" Sai said. "I'll bring one right to you."

"Thanks." The associate went back to the conference room.

Sai couldn't believe it. This was it. He plugged the drive into a charging cable and added an extension on the other end. The whole thing looked only a little odd, like a thin python who had swallowed a rat.

But suddenly he felt a sinking feeling in the pit of his stomach and he almost swore aloud: He had forgotten to turn off the webcam above his computer- Tilly's eyes -before preparing the cable. If Tilly raised questions about the weird cable he was carrying, he would have no explanation, and then all of his efforts at misdirection, at hiding, would be for naught.

But there was nothing he could do about it now but proceed as planned. As he left his cubicle, his heart was almost in his throat.

He stepped into the hallway, and strode down to the conference room.

Still nothing from his earpiece.

He opened the door. Rushgore was too busy with his computer even to look up. He grabbed the cable from Sai and plugged one end into his computer, and the other end into his phone.

And Tilly remained silent.

***

Sai woke to-what else?-"We Are the Champions."

The previous night of drinking and laughing with Jenny and her friends had been a blur, but he did remember coming home and telling Tilly, right before he fell asleep, "We did it! We won!"
Ah, if Tilly only knew what we were celebrating.
The music faded, stopped.

Sai stretched lazily, turned to his side, and stared into the eyes of four burly, very serious men.

"Tilly, call the police!"

"I'm afraid I can't do that, Sai."

"Why the hell not?"

"These men are here to help you. Trust me, Sai. You know I know just what you need."

***

When the strange men had appeared in his apartment, Sai had imagined torture chambers, mental hospitals, faceless guards parading outside of dark cells. He had not imagined that he would be sitting across the table from Christian Rinn, Founder and Executive Chairman of Centillion, having white tea.

"You got pretty close." Rinn said. The man was barely in his forties and looked fit and efficient- kind of like how I picture a male version of Tilly, Sai thought. He smiled. "Closer than almost anyone."

"What was the mistake that gave us away?" Jenny asked.

She was sitting to Sai's left, and Sai reached out for her hand. They intertwined their fingers, giving each other strength.

"It was his phone, on that first night he visited you."

"Impossible. I shielded it. It couldn't have recorded anything."

"But you left it on your desk, where it could still make use of its accelerometer. It detected and recorded the vibrations from your typing. There's a very distinctive way we strike the keys on a keyboard, and it's possible to reconstruct what someone was typing based on the vibration patterns alone. It's an old technology we developed for catching terrorists and drug dealers."

Jenny cursed under her breath, and Sai realized that until that moment, on some level, he still hadn't quite believed Jenny's paranoia.

"But I didn't bring my phone after that first day."

"True, but we didn't need it. After Tilly picked up what Jenny was typing, the right alert algorithms were triggered and we focused surveillance on you. We parked a traffic observation vehicle a block away and trained a little laser on Jenny's window. It was enough to record your conversations through the vibrations in the glass."

"You're a very creepy man, Mr. Rinn," Sai said. "And despicable too."

Rinn didn't seem bothered by this. "I think you might feel differently by the end of our conversation. Centillion was not the first company to stalk you."

Jenny's fingers tightened around Sai's. "Let him go. I'm the one you really want. He doesn't know anything."

Rinn shook his head and smiled apologetically. "Sai, did you realize that Jenny moved into the apartment next to yours a week after we retained Chapman Singh to represent us in the suit against ShareAll?"

Sai didn't understand what Rinn was getting at, but he sensed that he would not like what he was about to find out. He wanted to tell Rinn to shut up, but he held his tongue.

"Curious, aren't you? You can't resist the pull of information. If it's possible, you always want to learn something new; we're hardwired that way. That's the drive behind Centillion, too."

"Don't believe anything he says," Jenny said.

"Would it surprise you to find out that the five other paralegals in your firm also had new neighbors move in during that same week? Would it also surprise you to learn that the new neighbors have all sworn to destroy Centillion, just like Jenny here? Tilly is very good at detecting patterns."

Sai's heart beat faster. He turned to Jenny. "Is this true? You planned from the start to use me? You got to know me just so you'd have a chance to deliver a virus?"

Jenny turned her face away.

"They know that there's no way to hack into our systems from the outside, so they had to sneak a trojan in. You were used, Sai. She and her friends guided you, led you by the nose, made you do things-just like they accuse us of doing."

"It's not like that," Jenny said. "Listen, Sai, maybe that was how it started. But life's full of surprises. I was surprised by you, and that's a good thing."

Sai let go of Jenny's hand and turned back to Rinn. "Maybe they did use me. But they're right. You've turned the world into a Panopticon and all the people in it into obedient puppets that you nudge this way and that just so you'd make more money."

"You yourself pointed out that we were fulfilling desires, lubricating the engine of commerce in an essential way."

"But you also fulfill dark desires." He remembered again the abandoned houses by the side of the road, the pockmarked pavement.

"We unveil only the darkness that was already inside people," Rinn said. "And Jenny didn't tell you about how many child pornographers we've caught, how many planned murders we've stopped, or how many drug cartels and terrorists we've exposed. And all the dictators and strongmen we've toppled by filtering out their propaganda and magnifying the voices of those who oppose them."

"Don't make yourself sound so noble," Jenny said. "After you topple governments, you and the other Western companies get to move in and profit. You're just propagandists of a different ilk-for making the world flat, turning everywhere into copies of suburban America, studded with malls."

"It's easy to be cynical like that," Rinn said. "But I'm proud of what we've done. If cultural imperialism is what it takes to make the world a better place, then we'll happily arrange the world's information to ennoble the human race."

"Why can't you just be in the business of neutrally offering up information? Why not go back to being a simple search engine? Why all the surveillance and filtering? Why all the manipulation?" Sai asked.

"There's no such thing as neutrally offering up information. If someone asks Tilly about the name of a candidate, should Tilly bring them to his official site or a site that criticizes him? If someone asks Tilly about 'Tiananmen,' should Tilly tell them about the hundreds of years of history behind the place or just tell them about June 4, 1989? The 'I Trust You' button is a heavy responsibility that we take very seriously.

"Centillion is in the business of organizing information, and that requires choices, direction, inherent subjectivity. What is important to you-what is true to you-is not as important or as true to others. It depends on judgment and ranking. To search for what matters to you, we must know all about you. And that, in turn, is indistinguishable from filtering, from manipulation."

"You make it sound so inevitable."

"It is inevitable. You think destroying Centillion will free you, whatever 'free' means. But let me ask you, can you tell me the requirements for starting a new business in the State of New York?"

Sai opened his mouth and realized that his instinct was to ask Tilly. He closed his mouth again.

"What's your mother's phone number?"

Sai resisted the urge to reach for his phone.

"How about you tell me what happened in the world yesterday? What book did you buy and enjoy three years ago? When did you start dating your last girlfriend?"

Sai said nothing.

"You see? Without Tilly, you can't do your job, you can't remember your life, you can't even call your mother. We are now a race of cyborgs. We long ago began to spread our minds into the electronic realm, and it is no longer possible to squeeze all of ourselves back into our brains. The electronic copies of yourselves that you wanted to destroy are, in a literal sense, actually you.

"Since it's impossible to live without these electronic extensions of ourselves, if you destroy Centillion, a replacement will just rise to take its place. It's too late; the genie has long left the bottle. Churchill said that we shape our buildings, and afterwards, our buildings shape us. We made machines to help us think, and now the machines think for us."

"So what do you want with us?" Jenny asked. "We won't stop fighting you."

"I want you to come and work for Centillion."

Sai and Jenny looked at each other. "What?"

"We want people who can see through Tilly's suggestions, detect her imperfections. For all that we've been able to do with AI and data mining, the Perfect Algorithm remains elusive. Because you can see her flaws, you'll be the best at figuring out what Tilly's still missing and where she's gone too far. It's the perfect match. You'll make her better, more compelling, so that Tilly will do a better job."

"Why would we do that?" Jenny asked. "Why would we want to help you run people's lives with a machine?"

"Because as bad as you think Centillion is, any replacement is likely worse. It was not a mere PR move that I made 'ennobling the human race' the mission of this company, even if you don't agree with how I've gone about it.

"If we fail, who do you think will replace us? ShareAll? A Chinese company?"

Jenny looked away.

"And that is why we've gone to such extraordinary lengths to be sure that we have all the data we need to stop competitors as well as well-meaning, but naïve, individuals like you from destroying all that Centillion has accomplished."

"What if we refuse to join you but tell the world what you've done?"

"No one would believe you. We will make it so that whatever you say, whatever you write, no one will ever find it. On the Net, if it can't be found by Centillion, it doesn't exist."

Sai knew that he was right.

"You thought Centillion was just an algorithm, a machine. But now you know that it's built by people-people like me, people like you. You've told me what I've done wrong. Wouldn't you rather be part of us so that you can try to make things better?

"In the face of the inevitable, the only choice is to adapt."

***

Sai closed the door of the apartment behind him. The camera overhead followed.

"Will Jenny be coming over tomorrow for dinner?" Tilly asked.

"Maybe."

"You really need to get her to start sharing. It will make planning much easier."

"I wouldn't count on it, Tilly."

"You're tired," Tilly said. "How about I order you some hot organic cider for delivery and then you go to bed?"
That does sound perfect.
"No," Sai said. "I think I prefer to just read for a while, in bed."

"Of course. Would you like me to suggest a book?"

"I'd rather you take the rest of the night off, actually. But first, set the wake-up song to Sinatra's 'My Way.'"

"An unusual choice, given your taste. Is this a one-time experiment or would you like me to incorporate it into your music recommendations for the future?"

"Just this once, for now. Good night, Tilly. Please turn yourself off."

The camera whirred, followed Sai to bed, and shut off.

But a red light continued to blink, slowly, in the darkness.
© 2012 Ken Liu.
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Sai woke to the rousing first movement of Vivaldi's violin concerto in C minor, "Il Sospetto." He lay still for a minute, letting the music wash over him like a gentle Pacific breeze. The room brightened as the blinds gradually opened to the sunlight.

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A moving story about pollution and overdependence on tech. It asks us to think about what we’re willing to sacrifice.

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Softly There Will Come the Rain (Short Story)

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Softly There Will Come the Rain (Short Story)

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Paired with the poem of the same name which inspired the story, this class short story follows an automated house continuing its routine long after its human occupants are gone, reminding us that technology may outlive us.

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Teasdale’s poem imagines nature oblivious to humanity’s absence. Offers a lens to explore themes of automation, loss, and environmental fragility.

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And in my Lesbos, over leagues of sea,
The temples glimmer moonwise in the trees.
Twilight has veiled the little flower face
Here on my heart, but still the night is kind
And leaves her warm sweet weight against my breast.
Am I that Sappho who would run at dusk

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There Will Come Soft Rains - There will come soft rains and the smell of the ground,

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This beloved and well-known picture book is a great way to talk about the cost of unchecked progress, even with older students.

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View flipping ebook version of The Lorax by Dr. Seuss published by Nur Zalikha Mohd Ramli on 2020-08-16. Interested in flipbooks about The Lorax by Dr. Seuss? Check more flip ebooks related to The Lorax by Dr. Seuss of Nur Zalikha Mohd Ramli. Share The Lorax by Dr. Seuss everywhere for free.

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Training a single AI model can emit as much carbon as five cars in their lifetimes (Article)

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Training a single AI model can emit as much carbon as five cars in their lifetimes (Article)

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Perfect for sparking student reactions and raising awareness about the hidden toll of developing AI.

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It's a jarring quantification of something AI researchers have suspected for a long time. "While probably many of us have thought of this in an abstract, vague level, the figures really show the magnitude of the problem," says Carlos Gómez-Rodríguez, a computer scientist at the University of A Coruña in Spain, who was not involved in the research. "Neither I nor other researchers I've discussed them with thought the environmental impact was that substantial."

The carbon footprint of natural-language processing

The paper specifically examines the model training process for natural-language processing (NLP), the subfield of AI that focuses on teaching machines to handle human language. In the last two years, the NLP community has reached several noteworthy performance milestones in machine translation, sentence completion, and other standard benchmarking tasks. OpenAI's infamous GPT-2 model, as one example, excelled at writing convincing fake news articles.

But such advances have required training ever larger models on sprawling data sets of sentences scraped from the internet. The approach is computationally expensive-and highly energy intensive.

The researchers looked at four models in the field that have been responsible for the biggest leaps in performance: the Transformer, ELMo, BERT, and GPT-2. They trained each on a single GPU for up to a day to measure its power draw. They then used the number of training hours listed in the model's original papers to calculate the total energy consumed over the complete training process. That number was converted into pounds of carbon dioxide equivalent based on the average energy mix in the US, which closely matches the energy mix used by Amazon's AWS, the largest cloud services provider.

They found that the computational and environmental costs of training grew proportionally to model size and then exploded when additional tuning steps were used to increase the model's final accuracy. In particular, they found that a tuning process known as neural architecture search, which tries to optimize a model by incrementally tweaking a neural network's design through exhaustive trial and error, had extraordinarily high associated costs for little performance benefit. Without it, the most costly model, BERT, had a carbon footprint of roughly 1,400 pounds of carbon dioxide equivalent, close to a round-trip trans-America flight for one person.

What's more, the researchers note that the figures should only be considered as baselines. "Training a single model is the minimum amount of work you can do," says Emma Strubell, a PhD candidate at the University of Massachusetts, Amherst, and the lead author of the paper. In practice, it's much more likely that AI researchers would develop a new model from scratch or adapt an existing model to a new data set, either of which can require many more rounds of training and tuning.

To get a better handle on what the full development pipeline might look like in terms of carbon footprint, Strubell and her colleagues used a model they'd produced in a previous paper as a case study. They found that the process of building and testing a final paper-worthy model required training 4,789 models over a six-month period. Converted to CO ₂ equivalent, it emitted more than 78,000 pounds and is likely representative of typical work in the field.

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Training a single AI model can emit as much carbon as five cars in their lifetimes

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The artificial-intelligence industry is often compared to the oil industry: once mined and refined, data, like oil, can be a highly lucrative commodity. Now it seems the metaphor may extend even further. Like its fossil-fuel counterpart, the process of deep learning has an outsize environmental impact.

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Concern UK's AI ambitions could lead to water shortages (Article)

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Concern UK's AI ambitions could lead to water shortages (Article)

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A real-world example of how tech growth competes with natural resources.

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Concern the UK’s AI ambitions could lead to water shortages

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Data centres can use vast quantities of water to cool them - but it’s not clear where it will come from.

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Can We Mitigate AI’s Environmental Impacts? (Article)

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Can We Mitigate AI’s Environmental Impacts? (Article)

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Offers some hope, solutions, and strategies to reduce harm while still moving forward. Good for balancing gloom & doom with action.

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Can We Mitigate AI’s Environmental Impacts?

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YSE Professor Yuan Yao discusses the environmental costs and benefits of artificial intelligence.

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In this famous short story, a brother and sister get addicted to a VR nursery and things take a dark turn. It's a strong warning about giving too much power to tech, especially when it replaces relationships.

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The Veldt by Ray Bradbury - Library of Short Stories

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It won’t hurt for the children to be locked out of it a while. Too much of anything isn’t good for anyone. And it was clearly indicated that the children had been spending a little too much time on Africa.

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For a Student Who Used AI to Write a Paper

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For a Student Who Used AI to Write a Paper (Poem)

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For a Student Who Used AI to Write a Paper (Poem)

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A poetic reminder that if you take shortcuts all through your life, you'll miss out on the beauty and the point of being alive.

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For a Student Who Used AI to Write a Paper

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Now I let it fall back
in the grasses.
I hear you. I know
this life is hard now.
I know your days are precious
on this earth.
But what are you trying
to be free of?
The living? The miraculous
task of it?
Love is for the ones who love the work.

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What Happens When Machines Learn to Write Poetry (Article)

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What Happens When Machines Learn to Write Poetry (Article)

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A thought-provoking piece about creativity, originality, and whether machines can really “feel” what they write. Great for classroom debates.

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What Happens When Machines Learn to Write Poetry

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The history of intelligent machines is one of moving goalposts: Sure, a machine can do this, but can it do that? The "that" is often an achievement that strikes us as strongly connected to emotion-that seems especially human.

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Representation & Reasoning: How Artificial Intelligence Makes Choices by ReadyAI (Picturebook)

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Representation & Reasoning: How Artificial Intelligence Makes Choices by ReadyAI (Picturebook)

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Another picturebook in the same series as "Machine Learning." Breaks down how AI makes decisions in a way kids can understand. Great for teaching how exposure to algorithms work

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Representation & Reasoning: How Artificial Intelligence Makes Choices (Fun Picture Book for K-2, AI+ME Series)

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Representation & Reasoning: How Artificial Intelligence Makes Choices (Fun Picture Book for K-2, AI+ME Series) - Kindle edition by ReadyAI. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Representation & Reasoning: How Artificial Intelligence Makes Choices (Fun Picture Book for K-2, AI+ME Series).

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The ethical costs of advances in AI (Article)

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The ethical costs of advances in AI (Article)

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Explores the human cost of rapid AI development. Brings in real-world consequences and the need for regulation.

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Editor's note: This feature article is part of our "AI is everywhere ... now what?" special project exploring the potential (and potential pitfalls) of artificial intelligence in our lives. Explore more topics and takes on the project page.
Recent advancements in artificial intelligence have come onto the scene with a flurry of excitement. Like a newborn baby, there were grand ideas for its future. But that excitement was tempered by ethical issues that pervade many aspects of its use.

Issues around privacy, bias, employment, surveillance, security and more.

"Basically every time we innovate, we solve a problem and we create new problems," said Andrew Maynard, professor of advanced technology transitions in Arizona State University's School for the Future of Innovation in Society.

Of course, the most extreme ethical concern is the potential threat that some say AI can present to human existence.

"This comes from the idea that AI can become super intelligent and super aware to the point that it decides for itself what sort of world it wants, what sort of future it wants and becomes so powerful that it is beyond human control," Maynard said.

"So now we've got the risk that if this AI decides that it wants a world where humans don't flourish, it has the ability to create that. This is one of those theories that I don't fully agree with. But that's the big fear that people like Elon Musk talk about."

Musk sounded the alarm in November, prior to the landmark AI Safety Summit in the United Kingdom, saying, "Artificial intelligence could pose an existential risk if it becomes antihuman."

"I don't think that's a serious risk," Maynard said. "But it's important that some people think about it."

ASU Regents and Foundation Professor Gary Marchant is one of the people doing that thinking.

Marchant was co-principal investigator of a $10,000 grant from the Future of Life Institute to The Hastings Center that ran from 2017-2019 and focused on how to prevent AI from exterminating humans.

Two-thirds of the 30 leading AI experts at the grant meeting agreed that this kind of threat was inevitable. Only one-third thought it would never happen.

"A lot of people there were convinced that it is going to exterminate us at some point if we don't do something," said Marchant, faculty director for the Center for Law, Science and Innovation at the Sandra Day O'Connor College of Law at ASU. "That was the first time in my life I ever got scared of technology."

The U.S. State Department came out with a report in March saying that rapidly evolving AI can create national security risks of "catastrophic events up to and including events that would lead to human extinction."

But just how did we arrive at this existential point in AI's evolution?

Very quickly, it seems.

And we're off ...

It is common knowledge that new technology needs to be tweaked. It evolves over time with adjustments in an ever-changing process of refinement. (The first mobile phone, for example, was 4 pounds compared with today's 6-ounce counterpart.)

But in some respects, after AI came out of the gate, it may have already been too late for some serious and necessary modifications.

For example, large-scale language models such as ChatGPT and other forms of generative AI had access to vast archives of content - including everything from books by bestselling authors to the classics, and an extensive collection of artistic works. Access, it must be noted, that was rarely approved of by the content creators.

Drawing on this data from around the world, these models went to work. Now people are sorting through the ethical debris as creators grapple with the reality that a craft that took a lifetime to perfect might now be replicated in a matter of moments.

Marchant has been studying what he calls the "pacing problem" of technology for many years. The idea is that technology is advancing too fast for government regulations to keep pace and be put in place.

AI takes this problem to a new, unforeseen level.

"It is basically the pacing problem on steroids," said Marchant, lead organizer for ASU's Governance of Emerging Technologies and Science conference.

"AI makes it much worse because it is moving so much faster than any other technologies. Every week there's a new development, and its impact is profound - not just on a particular industry but across the entire economy."

The implications of it are so much more extreme and far-reaching that it is beyond our grasp, he said.

"It's going to change everything. It's impacting careers, relationships and more," he said. "People are bonding with machines. A million people proposed marriage to Alexa (the virtual assistant technology) a year ago. Machines are becoming our friends, our lovers, our counselors - our everything."

Intentional and unintentional consequences

A big debate in the AI ethics community is whether to focus on short-term ethical risks like bias and privacy, or on the issue of extinction. ASU experts say they are both priorities.

Short-term ethical risks created by AI have been divided into two categories - those that are intentional and those that are unintentional.

Unintentional ethical issues include things like societal risks and AI accidents.

For example, facial recognition technology is less accurate in identifying people of color, and language translation systems can associate some languages with certain genders, stereotypes or education levels.

Data security and privacy also fall under this category. AI uses large quantities of personal and sensitive data, which can be exploited.

In 2017, military bases in covert areas were revealed because of data being collected by fitness devices as soldiers went around tracks each day.

"People are trying to do the right thing, but things go wrong anyway," Maynard said.

Intentional ethical dangers include psychological manipulation, weaponization, mass cyberattacks, disinformation campaigns and more.

"There are so many ways in which people can use AI to cause harm," Maynard said.

AI-generated voice scams are being used to imitate family members. The technology can fool parents into believing their child is in serious trouble and in need of money.

Misinformation can also be spread. During elections, for example, AI can generate targeted emails, texts and videos that impersonate candidates and deceive voters.

Maynard is particularly concerned about deepfakes.

"There are platforms where photos of young people are used to artificially create nudes - that are then circulated," he explained. "These are the sorts of issues that really worry me."

Other issues are more ambiguous - such as the deployment of AI on the battlefield, raising the question of what constitutes ethical behavior in the context of war.

While AI technology has been a game changer for the military, especially in the use of combat or fighter drones, it has also created concerns - including the creation of machines capable of killing without human authorization and the detachment of soldiers from the consequences of war.

"This is the problem with ethics," Maynard said. "You can have two sides that will argue from a basis of deep values that they are ethically right, but they will be completely opposed. AI is creating these sorts of conversations."

The problem with solutions

One of the problems with finding solutions to AI-generated issues is that the ethics community can't calculate the full extent of the problem.

"We're now getting a technology which is so powerful and going so fast that we're really on the cusp of creating problems that we don't understand - so we can't work out how to address them," Maynard said.

Katina Michael calls that algorithmic fallout.

"The negative potential of AI is invisible," says Michael, a professor in ASU's School of Computing and Augmented Intelligence. "And we can't measure it. We can't see it, and we often don't know what it is, except we know that harm can occur. ... To an extent, we really can't understand it until the aftereffects are seen and people start reporting them."

But what we do understand is this:

The U.S. State Department's recent report says that time is running out for the government to stave off the potential damage that could be caused by AI.

Laws are slow to develop, and even those that are in place - for example, to address deepfakes - are hard to police. There is also the risk that laws can overreach and inhibit innovation.

During the past 100 years, there was an assumption that with good regulations and policies in place, technology could be kept in check. AI is breaking all the rules, experts say, meaning that how we thought about developing responsible technologies in the past is unlikely to work with AI.

What will work is to ensure that ethics are embedded in the development process, according to Michael.

"It's easy to point to operationalizing ethics at three levels - in the collection of data, in the design and in the implementation of an AI-enabled digital transformation," she said.

"If you abide by laws, you abide by human rights, you abide by international standards, you abide by organizational policies and human ethics protocols as a designer and developer, you're not going to have an awful outcome."

Collaboration in the design process is another essential element in developing ethical AI.

"If you use ethically aligned design principles, what you're saying is, 'I've gone to the users and other stakeholders, and I've asked them to be co-designers,'" Michael said.

The issue of consent is also a critical piece in the implementation of responsible technology.

Michael says there are 40 years of digital data, including 40 billion images that can be scraped from the internet. And while some of it is being used for good - for example, to solve cold crimes - open-source data is fundamentally being incorporated without consent.

It must be clean data that's collected transparently, Michael said, and we need to right any wrongs in the past.

"Data is all about consent," she said.

Marchant says because of the pacing problem, the government is just too slow to take on all of the issues already unraveling. They must be addressed through governance by multiple organizations.

It's done by the media, he said - and academia has a huge role to play as well - but not the government alone.

Industry standards are already being put in place, and that will continue.

Michael says that as industry conventions or soft laws are put in place, they will become the precedent for hard laws.

"Attempts to predict the possible pitfalls of a bigger, better and badder AI are challenging," she said. "Because of that inability to see beyond the horizon of risks - as well as the benefits - from the ever-evolving AI technology, a framework of global response practices must be put in place."

What the future holds in addressing ethical problems is difficult to predict.

"People have been discussing AI ethics for a long time," said Maynard, who attended one of the first major conferences on the topic in 2017. The initial assumption was that a solid ethical foundation would ensure AI prioritizes human interests.

"But we've found that ethics alone are insufficient," he said. "While ethics help define right and wrong, they don't necessarily lead to the creation of safe and responsible AI. That's why the focus is shifting towards responsible AI, a concept gaining traction in the U.S. government, major companies and globally.

"However, current approaches seem inadequate. AI development is rapidly outpacing our ability to responsibly manage it. The challenge remains: How do we keep up? ... All we can do is be agile and responsive in trying to ensure the benefits far outweigh the risks."

AI is everywhere ... now what?

Artificial intelligence isn't just handy for creating images like the above - it has implications in an increasingly broad range of fields, from health to education to saving the planet.

Explore the ways in which ASU faculty are thinking about and using AI in their work:

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Editor's note: This feature article is part of our "AI is everywhere ... now what?" special project exploring the potential (and potential pitfalls) of artificial intelligence in our lives. Explore more topics and takes on the project page.

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[VIDEO 1] AI Is Dangerous, but Not for the Reasons You Think | Sasha Luccioni | TED

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[VIDEO 1] AI Is Dangerous, but Not for the Reasons You Think | Sasha Luccioni | TED

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The speaker challenges us to look beyond the usual scares- AI matters not just for bias or autonomy, but for its sustainability and creative consequences, like climate impact and copyright use.

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AI Is Dangerous, but Not for the Reasons You Think | Sasha Luccioni | TED

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[VIDEO 2] The three big ethical concerns with artificial intelligence

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[VIDEO 2] The three big ethical concerns with artificial intelligence

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This video breaks down three ethical challenges when working with AI, highlighting how they must be built to avoid bias, be understandable, and serve diverse communities responsibly.

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The three big ethical concerns with artificial intelligence

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[SUPPORTIVE TEXT 1] We Already Have an Ethics Framework for AI

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[SUPPORTIVE TEXT 1] We Already Have an Ethics Framework for AI

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This author claims that ethical thinking exists, and we can apply our notions of ethics to AI already.

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Inside Higher Ed | Higher Education News, Events and Jobs

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We Already Have an Ethics Framework for AI (opinion)

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An accepted framework guiding human subjects research can help us make ethical judgments about different AI uses, Gwendolyn Reece writes.

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A powerful novel about an AI girl longing to be loved. It’s moving, and opens up big questions about humanity and connection, and casts AI in a positive light.

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"One of the most affecting and profound novels Ishiguro has written....I'll go for broke and call Klara and the Sun a masterpiece that will make you think about life, mortality, the saving grace of love: in short, the all of it."
-Maureen Corrigan, NPR

"A delicate, haunting story, steeped in sorrow and hope."
-Ron Charles, The Washington Post

"It aspires to enchantment, or to put it another way, reenchantment, the restoration of magic to a disenchanted world. Ishiguro drapes realism like a thin cloth over a primordial cosmos. Every so often, the cloth slips, revealing the old gods, the terrible beasts, the warring forces of light and darkness."
-Judith Shulevitz, The Atlantic

"Ishiguro's prose is soft and quiet. It feels like the perfect book to curl up with on a Sunday afternoon. He allows the story to unfold slowly and organically, revealing enough on every page to continue piquing the reader's curiosity. The novel is an intriguing take on how artificial intelligence might play a role in our futures...a poignant meditation on love and loneliness"
- Maggie Sprayregen, The Associated Press

"For four decades now, Ishiguro has written eloquently about the balancing act of remembering without succumbing irrevocably to the past. Memory and the accounting of memory, its burdens and its reconciliation, have been his subjects... Klara and the Sun complements [Ishiguro's] brilliant vision...There's no narrative instinct more essential, or more human."

"A prayer is a postcard asking for a favor, sent upward. Whether our postcards are read by anyone has become the searching doubt of Ishiguro's recent novels, in which this master, so utterly unlike his peers, goes about creating his ordinary, strange, godless allegories."-James Wood, The New Yorker

"One of the joys of Ishiguro's novels is the way they recall and reframe each other, almost like the same stories told in different formats...Again and again, Ishiguro asks: What does it mean to be human? What does it mean to have a self? And how much of that self can and should we give to others?"

"Moving and beautiful... an unequivocal return to form, a meditation in the subtlest shades on the subject of whether our species will be able to live with everything it has created... [A] feverish read, [a] one-sitter... Few writers who've ever lived have been able to create moods of transience, loss and existential self-doubt as Ishiguro has - not art about the feelings, but the feelings themselves."
-The Los Angeles Times

"As with Ishiguro's other works, the rich inner reflections of his protagonists offer big takeaways, and Klara's quiet but astute observations of human nature land with profound gravity . . . This dazzling genre-bending work is a delight."
-Publishers Weekly [starred review]

"A haunting fable of a lonely, moribund world that is entirely too plausible."
"There is something so steady and beautiful about the way Klara is always approaching connection, like a Zeno's arrow of the heart. People will absolutely love this book, in part because it enacts the way we learn how to love. Klara and the Sun is wise like a child who decides, just for a little while, to love their doll. "What can children know about genuine love?" Klara asks. The answer, of course, is everything.""Flawless . . . This is a novel for fans of Never Let Me Go, with which it shares a DNA of emotional openness, the quality of letting us see ourselves from the outside, and a vision of humanity which - while not exactly optimistic - is tender, touching and true.""With its hushed intensity of emotion, this fable about robot love and loneliness confirms Ishiguro as a master prose stylist.""It is innocence that forms Ishiguro's major subject, explored in novels at once familiar and strange, which only gradually display their true and devastating significance.""The novel is a masterpiece of great beauty, meticulous control and, as ever, clear, simple prose.""A deft dystopian fable about the innocence of a robot that asks big questions about existence"

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obama;anniversary gift for her;summer reads for women 2021;best sellers list new york times 2021;best books 2021;best sellers list new york times 2020;top books;philosophy;kindle store;books;never let me go;husband birthday gift;thriller;grief;love;mystery;fantasy;sci-fi;sci fi books;science fiction books;science fiction;fiction books;fiction;remains of the day;novels;kazuo ishiguro;science fiction books best sellers;pulitzer prize winners fiction;ebooks;all together now;sci fi;books fiction

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science fiction; science fiction books; sci fi books; fiction; novels; fiction books; sci-fi; fantasy; mystery; thriller; love; husband birthday gift; grief; remains of the day; kazuo ishiguro; never let me go; kindle store; books; philosophy; top books; best sellers list new york times 2020; science fiction books best sellers; best books 2021; pulitzer prize winners fiction; obama; anniversary gift for her; summer reads for women 2021; best sellers list new york times 2021; nyt best sellers 2021; ebooks; all together now

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Klara and the Sun: A novel [Ishiguro, Kazuo] on Amazon.com. *FREE* shipping on qualifying offers. Klara and the Sun: A novel

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The Machines Mourn the Passing of the People (Poem)

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The Machines Mourn the Passing of the People (Poem)

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This poem imagines machines grieving humanity after we're gone.

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“The Machines Mourn the Passing of People” by Alicia E. Stallings

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The Machines Mourn the Passing of People

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AI's Influence on Music is Raising Some Difficult Questions (Article)

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AI's Influence on Music is Raising Some Difficult Questions (Article)

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Explores the amazing things AI can do for musicians, butalso raises critical questions about originality, ownership, and creativity.

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Earlier this year, Bad Bunny emphatically rejected rumors that he was about to release a new song with Justin Bieber. "That's fake," he told TIME in an interview for a cover story on his meteoric rise. "You never know what I'm going to do."

But last month, a song featuring what sounded like his and Bieber's voices started circulating on TikTok, garnering millions of likes. Bad Bunny hadn't lied in the interview, though: the song was created with AI. An artist named FlowGPT had used AI technology to recreate the voices of Bad Bunny, Bieber and Daddy Yankee in a reggaeton anthem. Bad Bunny himself hated it, calling it a "shit of a song" in Spanish and discouraging his fans from listening, and the clip was removed from TikTok. But many fans of all three megastars loved it all the same.

The song and the polarized reactions to it are emblematic of the fraught ways in which AI has stormed the music industry. Over the past couple of years, advancements in machine learning have made it possible for anyone sitting in their homes to reproduce the sound of their musical idols. One artist, Ghostwriter, went viral for mimicking Drake and The Weeknd; another creator jokingly set Frank Sinatra's smoky voice to profane Lil Jon lyrics. Other AI tools have allowed users to conjure songs just by typing in prompts, which are effectively the audio versions of text-to-image tools like DALL-E.

More From TIME

Some boosters argue that these advancements will further the democratization of music, allowing anyone with an idea to create music from their bedroom. But some artists have reacted with fury that something so personal as their voice or musical style could be co-opted and commodified for someone else's gain. The push-and-pull between protecting artists, forging innovations, and determining the complementary roles for man and machine in music creation will be explored for years to come.

"If there's a huge explosion in music created at infinite scale and infinite speed, will that return us to thinking about what we are actually bringing to the table as humans?," asks Lex Dromgoole, a musician and AI technologist. "Where does imagination exist in this? How do we bring character to our own creations?"

AI is already being used by music producers for more mundane parts of their jobs. AI can help correct vocal pitch and allow engineers to mix and master recordings much more quickly and cheaply. The Beatles recently used AI to isolate John Lennon's voice from a 1978 demo, stripping out the other instruments and ambient noises in order to build a new, pristinely-produced song. AI is also ingrained in many peoples' listening experiences: streaming platforms like Spotify and Apple Music rely on AI algorithms to suggest people songs based on their listening habits.
Read More: Your Complete Guide to Spotify Wrapped, 2023
Then there's the actual creation of music using AI, which has triggered both excitement and alarm. Musicians have embraced music tools like BandLab, which suggests unique musical loops based on prompts as an escape valve for writer's block. The AI app Endel generates customized, constantly-mutating soundtracks for focusing, relaxing or sleeping based on people's preferences and biometric data. Other AI tools create entire recordings based on text prompts. A new YouTube tool powered by Google DeepMind's large language model Lyria allows users to type in something like "A ballad about how opposites attract, upbeat acoustic," and a song snippet belted by a Charlie Puth-soundalike is instantly generated.

These technologies raise all sorts of concerns. If an AI can create a "Charlie Puth song" instantaneously, what does that mean for Charlie Puth himself, or all the other aspiring musicians out there who fear they are being replaced? Should AI companies be allowed to train their large language models on songs without their creators' permission? AIs are already being used to summon the voices of the dead: a new Edith Piaf biopic, for example, will include a reassembled AI-created version of her voice. How will our understanding of memory and legacy change if any voice throughout history can be re-animated?

Even those most excited about the technology have become worried. Last month, Edward Newton-Rex, the vice president of audio at the AI company Stability AI, resigned from the company, saying he feared that he might have been contributing towards putting musicians out of jobs. "Companies worth billions of dollars are, without permission, training generative AI models on creators' works, which are then being used to create new content that in many cases can compete with the original works," he wrote in a public letter.

These questions will likely be decided in courts in the coming years. In October, Universal Music Group and other major labels sued the startup Anthropic after its AI model Claude 2 started spitting out copyrighted lyrics verbatim. A Sony Music executive told Congress that the company has issued almost 10,000 takedown requests for unauthorized vocal deepfakes. And many artists want to opt out entirely: Dolly Parton recently called AI vocal clones " the mark of the beast." AI companies, conversely, argue that their usage of copyrighted songs falls under "fair use," and is more akin to homages, parodies or cover songs.

The singer-songwriter Holly Herndon is among the artists trying to get ahead of these seismic changes. In 2021, she created a vocal deepfake of her own voice called Holly+, allowing anyone to transform their own voice into hers. The purpose of the project, she says, is not to force other artists to also surrender their voices, but to encourage them to also take on a proactive role in these larger conversations, and claim autonomy in a top-down music industry in which tech giants play an increasingly large role. "​​I think it's a huge opportunity to rethink what the role of the artist is," she tells TIME. "There's a way to still have some agency over the digital version of yourself, but be more playful and less punitive."

The musician Dromgoole, who co-founded the AI company Bronze, hopes that AI music will evolve out of its current stage of mimicking singers' voices and instantly generating music. Over the past few years, Bronze has worked with musicians like Disclosure and Jai Paul to create ever-evolving AI versions of their music, which never sound the same when played back twice. The goal is not to use AI to create the perfect, monetizable static song-but to use it to challenge our conceptions of what music could be. "It seems like the tech industry thinks that everyone wants a shortcut, or a solution to creativity," he says. "That's not how imagination works. Anyone who's studied flow state or spent time with people who are creating music knows that we love that process."

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AI tools can emulate famous singers and create entire songs. But some musicians are worried about copyright violations and the impact on their jobs.

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Top 10 Industries Using Artificial Intelligence (Article)

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Top 10 Industries Using Artificial Intelligence (Article)

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A short article about how AI is impacting the real world. Good for showing relevance beyond the classroom.

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The rise of AI adoption has introduced significant changes in conventional approaches to business operations, particularly with an emphasis on automation. More than 40% of enterprise-scale organizations in a survey by IBM have reported integrating AI in their operations. Interestingly, the efforts of top industries using AI have emerged as inspiration for many organizations to embrace AI. Businesses can make the most of AI in different ways ranging from automation of IT and business processes to achieving better customer service.

The best thing about AI is the flexibility for extending, adapting and applying it in different business processes. AI can introduce intelligence in tasks and achieve better results that were never seen before. Artificial intelligence can not only help businesses across different industries capitalize on the power of automation but also serves as a strategic partner. Let us find more about the industries that use AI to understand how businesses in various industries have been using artificial intelligence.

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Understanding the Technology that Makes a Difference

The modern business environment has witnessed radical and disruptive changes in various forms, including the introduction of new technology trends. Every industry must adapt to new technologies for working according to new market demands and competition. Your curiosity about questions like 'Which industry uses AI the most?' might lead you to an understanding of the problems solved by AI in different industries. Artificial intelligence is not just a buzzword anymore, especially for businesses which want innovative solutions to their issues.

Artificial intelligence has achieved the impossible by simulating human intelligence in computer systems. With the help of AI, computer systems have developed abilities for different processes such as learning, perception, problem-solving, reasoning, decision-making, and natural language understanding.

Businesses can use AI for simulation of human intelligence to work on different tasks, evaluate data and arrive at decisions. Artificial intelligence can make a difference for businesses by helping them with process automation, extraction of insights from big datasets and optimization of different business processes.

The discussions about adoption of AI across various industries also invites the limelight towards capabilities of AI to enhance customer experience and make informed decisions. You can come across many other benefits of artificial intelligence that make it an invaluable tool for various industries. Awareness of AI principles is important as it is an integral element of big data, IoT, sensors, AR/VR, machine learning, and many other technological advancements.

Discovering the Significance of AI in Different Industries

Artificial intelligence showcases its potential for transforming business operations through automation of tasks, data analysis and improved decision-making. You can notice that the artificial intelligence industry growth has been fuelled by the advantages introduced by AI in businesses.

Artificial intelligence supports the automation of repetitive processes, optimization of supply chains and prediction of maintenance and repairs. Most important of all, artificial intelligence plays a major role in encouraging innovation alongside ensuring that businesses can adapt to emerging industry trends.

Businesses across different industries need to understand how AI can help them make data-driven decisions and achieve better results in talent acquisition. The continuous learning capabilities of AI ensure that it would become a strong transformative force to achieve better productivity. The versatility of AI enables businesses to navigate the complex avenues of modern business alongside offering personalized experiences. Businesses in various industries should look for possibilities to embrace AI and capitalize on the following advantages.

Artificial intelligence introduces a revolutionary change by removing the human factor. It helps in reducing manual labor alongside addressing the concerns of manual errors in critical business processes.

The top companies using AI in the business processes would have a trusted companion working round the clock to achieve their objectives. AI does not sleep and could work incessantly for important operations such as customer support systems.

AI systems work according to the algorithms that power them and can offer better productivity. Artificial intelligence can help you make more informed business decisions within a split second without any doubt or exasperation.

Another notable reason to embrace AI in different industries is the safety of human workers. AI can empower robots that could work in conditions that are extremely hazardous for humans, such as underwater or outer space exploration.

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Unraveling the Industries that Use Artificial Intelligence

The advantages of artificial intelligence for businesses showcase some promising reasons for which AI has penetrated various industries. You might have many concerns about the feasibility of AI in different industries and the actual value of AI in each industry. Let us learn the unique ways in which the top industries in the world have adopted artificial intelligence.

Healthcare is one of the pioneers among industries that have adopted AI. As a matter of fact, it is one of the best industries using AI to achieve promising enhancements that might have taken more time. The foremost benefit of using AI in healthcare is the assurance of faster and more accurate diagnosis. Artificial intelligence systems can help in making treatments more personalized according to the needs and preferences of patients.

Organizations in the domain of healthcare can also leverage AI to overcome the obstacles in administrative tasks. AI can not only help in reducing errors but also improves patient care by addressing different pressing concerns.

Another top industry that has been successful in utilizing AI is finance. Organizations in the banking and financial services sector can utilize AI to improve fraud detection. AI systems can detect patterns that might escape the attention of humans, such as abnormal transaction patterns or suspicious activity. One of the best examples of AI applications in finance points at optimization of trading activities with algorithmic trading.

The review of AI uses in industry like finance also shed light on the possibilities of using chatbots to enhance customer service. AI chatbots can help in resolving common queries asked by consumers, thereby improving the quality of customer service. Artificial intelligence can not only enhance customer satisfaction but also enhance security with proactive threat detection.

Artificial intelligence can introduce massive changes in education with the help of personalized learning experiences for learners. Tutors can make the most of AI systems for automated grading and obtaining valuable insights from data analytics to deliver the best results. The most important outcome of implementing AI in the domain of education is the enhancement in student engagement and assurance of better learning outcomes.

The list of top industries using AI would be incomplete without including manufacturing. Artificial intelligence can help manufacturing in the areas of quality control and predictive maintenance. AI systems can detect the requirements for maintenance and repair in manufacturing plants, thereby saving costs and preventing downtime. The optimal use of AI in supply chain optimization also plays a vital role in enhancing product quality.

The retail and ecommerce industry has also tapped into the benefits of AI in different ways to improve customer experience. Businesses in the retail sector can use AI to come up with personalized recommendations and enhanced targeted marketing efforts. AI can also improve efficiency of retail inventory management that can contribute to effective management of sales. The use of AI for personalization of customer experience leads to plausible improvements in customer satisfaction.

Artificial intelligence has also revolutionized the marketing sector with some promising advantages. As a matter of fact, artificial intelligence industry growth has been the most significant in marketing with diverse AI applications. AI can help in achieving accurate customer segmentation and automated content creation. Artificial intelligence also helps marketing professionals in monitoring marketing campaigns, reviewing the performance analytics and increasing campaign efficiency and ROI.

The HR department in an organization could also tap into the potential of AI in any industry. HR professionals can use AI for faster recruitment processes alongside ensuring higher engagement. AI can support the creation of personalized training plans that would contribute to enhancements in productivity and satisfaction of the workforce.

The top companies using AI in the entertainment industry also showcase an interesting side of AI adoption. The applications of AI in the entertainment industry primarily revolve around audience analysis and content creation. You can come across various examples of AI being used to come up with advanced special effects and improving production quality of content. Most important of all, AI plays a crucial role in encouraging creativity in the entertainment industry.

Artificial intelligence is a powerful catalyst for transformation of the real estate industry. Real estate companies can use AI for faster and more accurate property evaluation alongside comprehensive market analysis. Chatbots can help customers find answers to the most common questions asked in the domain of real estate. The applications of artificial intelligence can help in achieving promising improvements in investment decisions alongside enhancing satisfaction of customers.

Virtual assistants and chatbots powered by artificial intelligence can enhance customer service by resolving critical queries. The chatbots and virtual assistants can offer faster solutions to customer queries with the assurance of personalized support. Businesses can use AI to improve efficiency in their customer support systems alongside ensuring customer satisfaction.

Final Thoughts

The review of the different industries using AI shows that artificial intelligence is no longer a luxury for businesses. Artificial intelligence is a must-have technology for every business in almost every industry that relies on technology. The promising enhancements introduced by AI in different industries reveal the urgency of thinking about the best strategies for AI adoption. Learn more about the fundamentals of AI and find how you can use it in different industries now.

About Author

David Miller

David Miller is a dedicated content writer and customer relationship specialist at Future Skills Academy. With a passion for technology, he specializes in crafting insightful articles on AI, machine learning, and deep learning. David's expertise lies in creating engaging content that educates and inspires readers, helping them stay updated on the latest trends and advancements in the tech industry.

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Top 10 Industries Using Artificial Intelligence - Future Skills Academy

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Artificial intelligence has become an integral part of the transformation of various industries. Learn about the top industries using AI and how AI helps them.

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9 Benefits of Artificial Intelligence (AI) in 2025 (Article)

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9 Benefits of Artificial Intelligence (AI) in 2025 (Article)

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A more optimistic look at what AI can do to improve lives.

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9 Benefits of Artificial Intelligence (AI) in 2024

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Explore 9 key benefits of AI in 2024, from enhanced healthcare to advanced cybersecurity and economic growth

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[SUPPORTIVE TEXT 1] How can AI make online chats kinder?

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[SUPPORTIVE TEXT 1] How can AI make online chats kinder?

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A hopeful piece about using tech to actually make people nicer online. Easy to connect to students’ own experiences.

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[SUPPORTIVE TEXT 2] An Ethics of Artificial Intelligence Curriculum for Middle School Students

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[SUPPORTIVE TEXT 2] An Ethics of Artificial Intelligence Curriculum for Middle School Students

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A comprehensive teaching resource that helps students think through the big questions around AI and responsibility.

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[SUPPORTIVE TEXT 2] The AI Revolution: Is it a Game Changer for Disability Inclusion?

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[SUPPORTIVE TEXT 2] The AI Revolution: Is it a Game Changer for Disability Inclusion?

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Discusses that AI is transforming lives by helping over a billion people with hearing or visual impairments, using tools such as speech‑to‑text, sound recognition, and descriptive technologies, when created in partnership with disability communities to ensure equal access and affordability.

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Illustration by Alfarob Khushvaqtov, UNDP Uzbekistan

Progress in Artificial Intelligence (AI) is being propelled by the intersection of big data, cloud computing, novel algorithms, distributed intelligence, and robotics. AI integrates digital technologies with human intelligence, allowing tools to operate in intricate settings, acquire knowledge from data, and render decisions. Governments are formulating national AI blueprints to leverage its advantages. Information and communication technologies (ICTs) have amplified disability advocacy, highlighting the critical importance of internet access for exercising human rights and closing the digital gap.

The latest data from WHO shows that about 1.3 billion people worldwide live with some form of disability. In addressing challenges related to the inclusion of individuals with disabilities through the use of AI, it is important to examine potential concerns and identify specific areas of focus. An essential inquiry involves the manner in which society will harness AI to establish economic and social systems that are inclusive. As indicated by the International Labour Organization (ILO), individuals with disabilities encounter reduced involvement in the labor force, lack of access to vocational training, and biases in recruitment and career advancement. A recent UNDP report found that only 5.8% of people with disabilities living in rural areas are employed. These challenges do originate from inherent restrictions but from intricate societal, legal, and economic settings.

Individuals with disabilities encounter barriers in both the private sector and education, such as inadequate school infrastructure and learning materials that do not meet their needs. In higher education, they face challenges like inaccessible campuses and unsupportive academic arrangements. Similarly, the healthcare sector and labor market present obstacles due to inaccessible physical infrastructures, reluctance to provide reasonable accommodations, and unconscious biases that hinder the full participation and inclusion of people with disabilities, ultimately limiting their opportunities.

Illustration by Alfarob Khushvaqtov, UNDP Uzbekistan

AI technology is revolutionizing the provision of disability support, benefiting over 1.5 billion people worldwide who are affected by hearing loss in at least one ear. AI-powered devices offer features such as speech-to-text transcription, sound identification, and using inputs to separate different sounds. For individuals with visual impairments, including 43 million who are blind, 295 million with moderate to severe visual impairment, and 258 million with mild visual impairment, AI can recognize facial expressions and gestures, and more accurately describe images, surroundings, and proxemics, thereby enhancing the overall interaction experience. These advancements in technology are helping to minimize feelings of isolation, emphasize individual abilities, and encourage independence.

Successful implementation of AI in assistive technology [AT] necessitates working closely with the disability communities to guarantee the availability of superior, varied data and knowledge. AI facilitates the provision of adaptable services for swift AT customization, capitalizing on data generated by experienced users. The United Nations Convention on the Rights of Persons with Disabilities underscores the importance of equal access to reasonably priced AT and assistance services, yet expensive solutions frequently result in the exclusion of individuals in low and middle-income countries.

Around 1% of the global population, or over 75 million people, are currently diagnosed with autism spectrum disorder, a rapidly growing challenge recognized as part of neurodiversity. With 85% of autistic individuals not employed, AI is opening up new employment possibilities. Specialisterne, an international organization established in 2004, helps businesses find positions that are suitable for neurodiverse individuals by matching their strengths with appropriate roles, with a focus on the potential of technology. Similarly, the startup Mentra uses AI to pair neurodiverse individuals with jobs, with an emphasis on software development. Furthermore, AI is improving assistive technology, such as Limbitless Solutions' 3D-printed bionic arms for children, which utilize AI to enhance control systems.

Illustration by Alfarob Khushvaqtov, UNDP Uzbekistan

Effective AI applications for people with disabilities include using robotic process automation to assist neurodiverse individuals, utilizing exoskeletons for paraplegics, and implementing AI-powered recruitment and decision-making tools. These practical instances showcase AI's capability to improve accessibility and productivity. Despite the significant opportunities presented by AI, it is crucial to address challenges such as concerns about replacing human services and the implementation of poorly designed systems. By prioritizing ethical development and user-centered design, AI has the potential to significantly improve lives and promote accessibility.

One example of AI usage creating barriers for persons with disabilities is in the area of voice recognition technology. Many AI systems rely on voice commands for operation, which can be challenging for individuals with speech disabilities or accents that are not easily understood by the technology. Another example is in the realm of accessible websites and apps, where AI-powered content and features may not be designed with the needs of individuals with visual or motor impairments in mind, creating accessibility barriers. Additionally, AI-powered automated decision-making systems may unintentionally discriminate against persons with disabilities by not accounting for their unique needs and circumstances.

The growing use of AI in the workplace requires a reconsideration of the government's responsibility to guarantee fundamental welfare for everyone. Research has indicated significant job reductions in manufacturing as a result of automation, and AI is being utilized in recruitment across different sectors. Safeguarding the inclusion and safety of individuals with disabilities in the AI era involves addressing societal prejudice and putting in place comprehensive ethical and regulatory protocols.

The impact of AI, especially machine learning-based AI, on people with disabilities is substantial. AI has the potential to address barriers and promote inclusivity but also poses risks of excluding individuals with disabilities from advancements. It is crucial to actively engange persons with disabilities in designing AI solutions aiming to maximize the benefits and minimize risks, ensuring that AI's evolution supports inclusivity and accessibility.

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The AI Revolution: Is it a Game Changer for Disability Inclusion?

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Progress in Artificial Intelligence (AI) is being propelled by the intersection of big data, cloud computing, novel algorithms, distributed intelligence, and robotics. AI integrates digital technologies with human intelligence, allowing tools to operate in intricate settings, acquire knowledge from data, and render decisions. Governments are formulating national AI blueprints to leverage its advantages.

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[VIDEO 1] The Sustainability Problems With Data And AI

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[VIDEO 1] The Sustainability Problems With Data And AI

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Highlights how all this "invisible" technology has a very real environmental cost. Great for helping students connect AI to climate concerns.

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The Sustainability Problems With Data And AI

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1. Students will write an action plan or contract for their personal AI use. Drawing from the understandings they gained from the unit, they will articulate what knoweldge is informing their stance.

2. In response to the novel Klara and the Sun, students will write a graphic novel short story featuring an AI hero.

3. Students will create a visual flowchart titled “Should I Ask AI?” where they map out when AI tools are helpful, neutral, or ethically questionable. This encourages students to take ownership over how they interact with technology, not just react to it.

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1. Students will engage in a station-rotation debate- at each station there will be an ethical dilemma involving AI. Students must split into two sides and support their position before rotating to the next station. Afterwards the class as a whole will discuss the scenarios and activity.

2. Students will write a guidebook for an AI on how to make decisions. Their guidebook must reference either "The Perfect Match" "The Veldt," or "Representation and Reasoning."

3. Students will write a poem back to the teacher in the poem about why they decided to use AI for their paper.

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[VIDEO 2] Can clean energy handle the AI boom?

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[VIDEO 2] Can clean energy handle the AI boom?

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This video explores how our increasing reliance on energy-consuming AI systems is straining current climate goals, raising questions about whether renewable energy can scale fast enough to power our AI ambitions.

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[SUPPORTIVE TEXT 1] Environmental Impact of AI

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[SUPPORTIVE TEXT 1] Environmental Impact of AI

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A resource for educators to teach students about AI’s carbon footprint and energy costs, promote energy‑efficient or renewable-powered tools, and ensure AI complements, not replaces, traditional teaching methods.

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One of the major takeaways from the U.S. Global Change Research Program's Fifth National Climate Assessment from fall 2023 is that the United States is warming faster than the rest of the world due to human activity. Negative impacts of climate change have undue and unequal consequences on Native People and People of Color, under-resourced urban and rural communities, people with disabilities, and girls and women. It is important that decision-makers and policymakers acknowledge, consider, and confront the environmental impacts of artificial intelligence and cloud technology.

"In the race to produce faster and more-accurate AI models, environmental sustainability is often regarded as a second-class citizen," noted University of Florence Assistant Professor Roberto Verdecchia.

Although these technologies operate in virtual spaces, AI and the cloud will intensify greenhouse gas emissions, consume increasing amounts of energy, and require larger quantities of natural resources.

Research suggests...

A single generative AI text query consumes energy at four or five times the magnitude of a typical search engine request.

Generating a single image using AI consumes the same amount of energy as charging a phone to full power.

Training one large AI model consumes nearly five times the lifetime emissions of the average American car.

Data centers-giant warehouses filled with endless rows of computer servers that are continuously working to complete tasks-used 4 percent of total U.S. electricity in 2023, and that number is expected to jump 7-12 percent in the next three years alone.

While it is nearly impossible for researchers to evaluate the full extent of the negative environmental impacts of AI technologies, decision-makers in education settings should be mindful of their environmental impacts throughout the planning and implementation phases.

Considerations for Educators

As you are making decisions about the use of AI technologies in your classroom, it is important to consider the environmental impact of AI's use:

Frequent AI-powered tasks-such as automated grading, image generation, adaptive learning, and chat bot interactions-consume considerable energy and contribute to the need for more data centers in communities.

You should be aware of the carbon footprint associated with AI tools and advocate for sustainable options.

Where possible, schools and universities should adopt policies that prioritize energy-efficient AI models and cloud technologies powered by renewable energy.

You should teach your students about the environmental impact of AI as part of learning around digital literacy.

When you discuss AI ethics with students, you should include sustainability and responsible AI usage.

When you create assignments and projects, you should encourage your students to explore energy-efficient AI alternatives, when possible.

AI should complement, not replace, traditional teaching methods. Hybrid approaches that combine AI-driven personalization with resource-efficient teaching will help mitigate environmental costs.

This section was created in spring 2025. It will be updated as further research on this topic becomes available.

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As you are making decisions about the use of AI in your classroom, it is important to understand the environmental impact of AI's use.

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[SUPPORTIVE TEXT 2] AI has an environmental problem. Here’s what the world can do about that.

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[SUPPORTIVE TEXT 2] AI has an environmental problem. Here’s what the world can do about that.

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This report flags the hidden costs of AI, like e‑waste and energy consumption, and reminds us that using AI at scale must include real plans to protect the planet.

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AI has an environmental problem. Here’s what the world can do about that.

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The sprawling data centres that house AI servers churn out toxic electronic waste and are voracious consumers of electricity, which in most places is still produced from fossil fuels.

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1. Students will research the carbon footprint of various types of technology such as mobile devices or AI servers and create an infographic based on their findings.

2. Students will write and shoot a PSA video about the negative environmental impacts of AI, using evidence from the sources we read together.

3. Students will compare and contrast the messages in the poem and short story "There Will Come Soft Rains."

4. Students will create a visual depiction of the house in "Softly There Will Come Rain"- either a diorama or digital representation.