How I Built This with Guy Raz - The peril (and promise) of AI with Tristan Harris: Part 1

Episode Date: February 22, 2024

When Tristan Harris co-founded the Center for Humane Technology in 2018, he was trying to educate tech leaders and policymakers about the harms of social media.But today, he’s sounding the alarm about a different technology — one that he says could pose an existential threat to the entire world …Artificial intelligence.This week on How I Built This Lab: the first of a two-episode series in which Tristan and Guy examine the serious risks posed by the rapid development and deployment of AI — and what we can do to make sure this powerful technology is used for good.You can learn more about “The Social Dilemma,” the 2020 Emmy-winning docudrama featuring Tristan, here: https://www.thesocialdilemma.com/.This episode was researched and produced by Alex Cheng with music by Ramtin Arablouei.It was edited by John Isabella. Our audio engineer was Neal Rauch.You can follow HIBT on X & Instagram, and email us at [e-mail] Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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It had tall windows, beautiful old details, and plenty of space for all of us. And being in that home on Airbnb, right in the middle of Vienna, walking distance from so much of the city, made it feel less like a visit and more like we were actually living there. Plus, taking a trip is the perfect time to host your space on Airbnb. Your place with all of its personal touches and its amazing location could make someone else's vacation even better. Your home might be worth more than you think. Find out how much at Airbnb.ca.com Hello and welcome to how I built this lab. I'm Guy Raz. Okay, artificial intelligence is going to change everything, not just about business or entrepreneurship, but everything, or at least we think so. do, and a lot of it excites me. Breakthroughs and curing diseases or maybe even solving climate

change. But a lot of it really freaks me out, too, like how it might become impossible to know what's true and what's not, what's real and what's fake. And because trust is the invisible force that allows our societies to work, AI could completely undermine all of it. Now, we've had a lot of conversations about AI on the show in the past year, and we're going to have many, many more. And this week and next, we have a really important guest, and I really hope you all spend some time really listening to these episodes. Many years before anyone noticed, Tristan Harris warned about the perils of social media. And by and large, he was proved right. He even helped make a film about it. You might have seen it. It was called The Social Dilemma. Tristan is one of the

founders of the Center for Humane Technology and his roots in the tech world run deep. And today, he's sounding the alarm about AI. Now, to be clear, he's not anti-AI, but Tristan is really worried about the pace of its growth, because in a very short period of time, he argues we're going to lose control over it. Today, we're going to run part one of my conversation with Tristan, and next week will have part two. Anyway, Tristan grew up in the Bay Area, and he was a technology kid through and through. He even wrote fan mail to Steve Wozniak, one of the co-founders of Apple. And actually, one of Tristan's co-founders at the Center for Humane Technology is deeply connected to that early obsession with Apple. And I'm honored today to say that my co-founder, Azar Raskin, his father was

Jeff Raskin, who started the Macintosh project at Apple, along with Steve Jobs, who later took over the project. And I think there's an ethos that both he and I come from of the original days of Silicon Valley that is aspirational, you know, in which computers can be a bicycle for the mind, a bicycle for human creativity, extending human expression. I think sometimes we can get classed to domers, but the risk side of AI. We only do that because we care about the vision where technology actually is in service of humanity. And to do that, we just think we have to fix the incentives. Yeah. You eventually started your own. your own company. This is in the

2000s, the mid-2000s called Apture. And this was a it was a hyperlink. You would like click over a hover over a hyperlink and you would get like other information, right? More or less. Can you describe what that company did? Yeah. I started Apture in

2007 and it was going back to the original ethos of what the internet and hyperlinking was supposed to be about. You know, you could say when people click on this button or click on this image or click on this text, I want the computer to speak. this out loud or to issue a dialogue prompt or to play this song or to play the piano. And it was the first really creative idea of this interlinked, what if everything was connected to everything

else in the most visually expressive, multimedia, educational, inspiring, beautiful way. So then I learned a lesson, though, because while I was interested in kind of re-identiating this original inspiring ethos of multimedia and teaching and education into the internet, the way that Apshire, which is a for-profit company, we raised venture capital, we had investors, and our progress, our success was measured not in the number of children who were inspired by cool media that they got to learn and watch and click on, but our progress was measured in the form of engagement. We did deals with the Washington Post, the New York Times, the economist, and they would ask us one question, which was, how much did you increase the amount of time

people spent on my website, aka how many ad views impressions did you increase? And that's when, you know, I really saw, I think, the fallacy that that leads and guides both the social media work that we became known for with the social dilemma and our work with AI, which is there's all these positive stories we want to tell ourselves about what we're building. But the question that determines which future will end up in is the incentives. And Charlie Munger, Warren Buffett's business partner just passed away. He had a very famous quote we referenced in our work that he said, that if you show me the incentive, I'll show you the outcome. Yeah.

When people ask themselves the question, like, which way is AI going to go? Was it going to be the promise or is it going to be the peril? How are we going to know? Well, the point is that the way that we'll know which future we get is by where the incentives, where the profit motive, where the status and reputation is all conferred to. And that's what we have to change. We're going to talk a lot about AI in this conversation, but I want to go back to around 2011 when Apture, APTRO was acquired by Google and you started work at Google.

Yep. And it was around, I think around this time that you really started to focus on this idea of attention and to become more troubled by it. Something that is now just, you know, it's an article of faith. We now know that the attention economy is a term. And we now know that tech companies make money from capturing our attention. You know, media does, YouTube does, this show does, right? But you were thinking about this a long time before others were as a potential problem. How did those ideas begin to kind of percolate in your mind?

Well, again, starting with my experience at Apture, I realized that for, you know, for our company to be successful, we had to increase the total amount of time people spent on the Washington Post and New York Times. And that there obviously isn't an infinite amount of human attention out there. It's almost like planetary boundaries, right? Can you run infinite economic growth on a finite planet forever? Well, so long as economic growth has environmental externalities or depletes finite resources, you can't do it for. forever, unless you keep making scientific breakthroughs on every dimension. So, you know, I think similar to that, you can't run infinite growth of every company demanding more attention per quarter per year forever with a finite supply of human attention. And at the time, in 2007,

it was actually the year the iPhone came out. We started our company before the iPhone came out, but obviously what mobile phones did is they opened up the attention economy. It used to be people only spent a few hours a day on computers, and then they would get offline and go outside, go to a movie, do something else. And increasingly, every moment of our lives became part of this attention economy, sold for a commodity, like the time you sit in the toilet and you go to the bathroom. And that's the boom. Now there's 10 extra minutes in the attention economy because the smartphone opened up that new piece of real estate. So I was just seeing the fact that this is where this is all going. There's only so much. And it's going to get more competitive. People are

going to find more creative ways of creating stickier, more persuasive, more socially validating. more outrage driven, more addicted, more distracted, more polarizing, narcissistic, you know, these kinds of things. Yeah. And it was pretty daunting to see that in 2013 when I was at Google and made this presentation because you're starting to see, like, if this keeps going, I can tell what kind of society this is going to create. And that's not a society that I think we can afford to be in.

We need to turn the tide. This presentation that you're referencing, it was called. It was a call to minimize distraction and respect users' attention. You were an employee at Google, and you decided to put together a 144-page Google slide presentation about, you know, what was going on. And I just want to read a line in there. The line is never before in history have the decisions of a handful of designers working at three companies, Google, Apple, and Facebook, had so much impact on how millions of people around the world spend their attention. We should feel an enormous responsibility to get this right. That was written in 2013.

You wrote it internally in Google, and it kind of went. internally viral. How did the leadership of Google respond? I mean, did they, you know, sort of pay your lip service and say, yeah, this is all, you're saying all the right things or were people annoyed or what'd they say? I remember when I sent the presentation to just 10 friends at Google, just to say, hey, can I get your feedback on this? And I came to work the next day, and there was something like 40 simultaneous viewers. And I knew that was impossible because I'd only sent it to 10 people. They were sending it around. And then later I looked at that day, and there was 150 simultaneous viewers. And then thousands by the, you know, the end of the day.

And so I really realized I got to clean this up and finish it basically in less than a couple hours. And it was this real moment in time. I remember hearing that I think in the first 24 hours that Larry Page, the CEO of Google, had had several meetings that day in which people brought up this presentation to him. And I got emails from around the company, mostly from other employees who just said, I completely agree. This is happening to my children. This is affecting my relationships.

This is this thing that you're naming a thing that I felt, but I didn't know how to put into words. And, you know, there was even an executive at Google who decided to host me, basically, offer me at a chance to work on this topic. And he sent me a quote by Neil Postman that we were all worried about this dystopian future of 1984, the George Orwell vision of dystopia, where technology limits our access to information, that there's surveillance, there's control, we ban books. But he said alongside that vision, There's this other dystopian vision with technology, which is the Aldous Huxley vision of

brave new world in which control is not established by banning books, but by creating a world of so much amusing ourselves to death that no one wants to read a book. No one even knows. There's just this tsunami of information. That's right. It's impossible to discern what is real from what is not. That's right, because it doesn't have a single source. It's not big brother. It's the big incentives of the attention economy that have made this problem worse and then combine that with technology and AI. And we're heading into a bigger version of that. So I'm not trying to paint a dark picture here. It's just important that we get a clear-eyed view of what world we're pulling towards so that we can say if that's not the future that we want, how we want to change the incentives to arrive in that future that we all want for our children.

We're going to take a quick break. But when we come back, more from Tristan on how social media and now AI development are how. happening too fast for humans to fully process. Stay with us. I'm Guy Raz, and you're listening to How I Built This Lab. Welcome back to How I Built This Lab. I'm Guy Raz, and my guest is Tristan Harris, co-founder of the Center for Humane Technology. Now, back in 2013, social media was really starting to explode, and Tristan was at Google, and he was sounding the alarm about the dangers of the attention economy. And he wasn't the only one concerned about the power of this new technology. And I remember reading at the time, and I don't know if this was apocryphal or not,

but reading that Steve Jobs, who had died two years earlier, wouldn't allow iPads in his own home. He did not allow his children to have these products that he himself helped to create. And it really struck me as not so much hypocritical, but that there was something that people understood, fundamentally understood, about the dangers of what they were unleashing. Yeah. And did you feel, at least at Google, did you feel like, okay, you know, they're taking this seriously. They made a position for you. They're called design ethicist.

Did you feel like, you know, maybe I can really make a dent here at Google. Maybe I can have an impact. Well, I certainly told myself that story when I first got started. And I really want to make sure that I'm honoring that I thought it was generous for Google to support the fact that I was doing that work. Right. And I want people to hear that so you don't hear me as some kind of reactionary, you know, the evils of big tech and all. the people at the top are evil. At a human level, when you talk to the human beings who worked in these products, I had a lot of people who were very sympathetic with these concerns. But when it

came down to trying to change Android, like I met with the Android team, say, what if we could change how the operating system works and better protect people's attention? Met with the Chrome design team. What if we could change Chrome to make it better at protecting people's attention? At the end of the day, Android and Chrome, you know, and Google benefit, the more overall screen time there is versus not. And so I knew that my success within the company was going to be limited. and I had to eventually take the concerns outside of the public world to try to say, how do we create public pressure that will start to change those incentives? And I had no idea in 2015 or so when I left Google how I was going to do that.

But here we are today. And there's some amazing things that have shifted in the public consciousness around this. And a lot more needs to happen. The first nonprofit that you founded was called Time Well Spent. And that was around 2014. in at that time, and I mean, up until, you know, recently, understandably, your focus, I think increasingly was on social media as it began to capture more and more of our time and attention. Yeah. And you start to see this happen at lightning speed.

Yeah. Around this time. Yeah. I mean, so time well spent came from this turn of phrase time spent. Most tech products and advertising is maximizing time spent. And we said, but is it maximizing time spent? maximizing time well spent, meaning at an existentialist level as a human being, what are the choices that you endorse as time well spent? And imagine a world where technology is competing not to maximize

how much time it takes from you, but to maximize its contributions, its net positive contributions to a life that you would endorse on your deathbed, meaning enabling you and helping you make the choices that are the lasting, meaningful, fulfilling choices, not the full but empty choices. But certainly inside of the time we'll spend world and the attention economy, the biggest forces that we were dealing with at that time were the growing revenues of social media companies and the growing portion of social media in that problem. You know, it's, and I know you've made this analogy or versions of it, but you think about something like the Gutenberg Press, right? And, you know, that happens in the 15th century

in Europe. And all of a sudden, ordinary people can get access to the Bible and they can start to learn how to read it, and it doesn't have to be filtered through the priests. And so that creates, it launches the Reformation. You know, of course, a huge innovation, it changed the world, but it was very disruptive. At the same time, this happened over a long period of time, right? And so you can basically trace that moment all the way to the end of World War II, which was kind of the end of the European era of wars, but I'm talking about 500 years. What happened with social media was like five years, and it was like the Goudoir Buttenberg press on steroids and amphetamines and, you know, everything in between.

It's almost inconceivable how our brains were going to adapt to this massive rapid proliferation of information. Yeah. In our work, we often reference the E.O. Wilson quote, who's the father of the field of sociobiology, that the fundamental problem that humanity faces is that we have paleolithic brains, medieval institutions, and. godlike technology, which is to say both in the power and the speed, our brains and our emotions are not built to see exponential curves, right? There's nothing on the savannah when you see a

giraffe or a tiger and you got to run from, you know, something that your brain needed to understand an exponential curve. It took, you know, Isaac Newton and calculus and sort of teaching ourselves education about math to start to understand what exponential curves are. We get more practice with that with finance and savings accounts and things like that. But our brains are not built for that. So suddenly you have something like, you know, social media come along where you totally have an exponential curve of how many users, how much content, et cetera, is flowing in the system. Then you get AI and you get a double exponential. You get an exponential that accelerates its own exponential, meaning AI accelerates AI development. And so we now have something that is moving so fast that,

you know, it's like our brains are completely not comprehending the moment that we're in. As you said, social media took, you know, five, six years to get to market penetration and the absorption of elections and journalism kind of get sucked into the black hole of that superorganism. In the case of AI, the stat that we use is it took Instagram, I think, two years to get to 100 million users, and it took chat GPT two months. So we're living with a technology that's changing and undermining the assumptions about how our world worked. We can, humanity can absorb new technologies, but it takes time.

And the challenge is when the time pressure that you have to absorb that new change is, is faster than ever before. This is the fastest that we've ever had to face it. Just to provide one quick thought experiment, a friend of mine who's an AI policy researcher, one of the major labs, he said, imagine that we just named that humanity has a finite capacity to absorb new technologies

that undermine our assumptions about how everything works. And imagine instead of just releasing all the new technology as fast as possible and just blowing past those finite absorption boundaries, that we instead, what if you had to apply for a life, license to release a new technology into the commons. And so we're basically consciously choosing as a society which new technologies we want to absorb and we want to prioritize and which ones we want to like give ourselves a little bit more time. It's not yes or no to technology. It's how do we absorb technologies at the pace that we can get it right. And I think it's an interesting thought

experiment for people to think about. We're going to take a quick break. But when we come back, The story of how Tristan was alerted to the dangers of another nascent technology, one that he says could pose an existential threat to the entire world. Stay with us. I'm Guy Raz, and you're listening to How I Built This Lab. Welcome back to How I Built This Lab. I'm Guy Raz, and my guest is Tristan Harris, co-founder of the Center for Humane Technology. In 2018, Tristan co-founded that nonprofit, and at the time, it was focused on the dangers of social media. But then, in late 2022, early 2023, Tristan started getting messages from people working on a different technology. You and Azaraskin, one of your co-founders, were contacted by people working in AI. And they were sounding the alarm.

And the analogy that you've made about this encounter really alarmed me compared it to like to the Manhattan Project. Can you describe or explain that a little bit? Yeah. Well, a lot of people analogize that the invention of AI is as significant as the invention of the atomic bomb. Now, that might sound like alarmist or panic creating or something like that. And it's not, actually. And it's because of how the atomic bomb restructured the world order. It was a new kind of power that whoever had it was clearly sort of the dog on top of the food chain. And with AI, what people don't understand is if you just...

genuinely build something that can do full artificial intelligence across all kinds of cognitive labor, meaning scientific labor, research labor, market analyst labor, financial labor. If you can out-compete all stock traders on the stock market, if you can out-compete all military strategy games, if you can out-compete anyone in writing text to influence people on the internet, if you have that AI system that can do that, that is a new kind of power. in which your position in the world will be greatest relative to everybody else. And so there is a new atomic bomb project in the form of those who are racing to build towards this fullest expression of AI, which some people call artificial general intelligence.

Remember that the stated mission statement of open AI, anthropic, and deep mind from the very beginning those three companies, have been to create artificial general intelligence. So when we got calls from some people in those labs, it felt, like getting a call from a scientist working on the Manhattan Project before you knew what the Manhattan Project was. Okay. So in 2022, you are contacted by AI researchers who are kind of ringing the alarm, right, that there's this AI arms race underway.

And so presumably they wanted you to help spread the word about what was happening, right? Yeah, this is late 2022, early 2023. And frankly, as you said, when we started the Center for Human technology, We had all the other issues of how social media is, you know, undermining democracies. We had our plate full. And I actually, they were asking for our help. They basically said, okay, you all raise the alarm about social media and the social dilemma. You have a huge public platform.

Listen, this race to build AI has gotten out of hand. And Open AI and Anthropic and DeepMind are now in this race to release things as fast as possible. And this race is going to go to a dangerous place if we don't have some outside pressure that can help bend the curve, maybe slow it down, a little bit, create some international norms, create some safety guardrails. Would you use your public platform to help raise the alarm? And you did. And you and your co-founder, Aza Raskin, would go on to build a presentation called the AI Dilemma. I think you first delivered it in March of 23 here in the Bay Area. You presented several times since then. I've seen it live. It's available online. Anybody can watch it. What was a message that you were trying to send with this

presentation. You know, the main point we made in the presentation is that social media was really humanity's first contact experience with a mass-deployed AI because it's an AI pointed at your 13-year-old's brain trying to calculate what's the perfect next TikTok video to show you, or what's the perfect next politically outrageous tweet that will keep you scrolling. And we saw how that experiment went. You know, there's a lot of really good things that social media has done, but the overall picture of what social media has done, if you really take into account the full scope of impacts and externalities, is it's also created the backdrop of a more addicted outrage,

polarized, narcissistic, breakdown of truth, you know, lower trust society. And that that is like undermining the quality of the soil underneath your feet while you have a few nice shiny toys above the soil. We knew that no matter what positive stories we were telling about social media, unless you pay attention to the incentives, which is to maximize attention and engagement, which produces that race to the bottom of the brainstem,

that that was going to be the driving force of what would tell you which future we're going to land into. And if we care about which AI future we get, we're going to hear a lot of positive stories about AI developing antibiotics and solutions to climate change and new drugs for cancer. And of course, I have a beloved with cancer right now.

I want as many of those solutions as we possibly can get as fast as possible. But we have to also look at the incentives, which is if it's a race to roll out AI capabilities as fast as possible, like handing out new magic wands for new kinds of things that people can do, that they couldn't even do four months ago. The fact that, you know, there's a new magic wand that was released last year that with three seconds in your voice, Guy, I can talk to your bank representative of your grandmother and pretend to be you and get sensitive information out of them. And society wasn't prepared for that magic wand to be rolled out. I want you to explain.

I mean, there was a big breakthrough in 2017. Essentially, Google announced this development. It's called the transformer model. And this helped kind of spark this breakthrough. And what we now know is large language models. And that's kind of helped to trigger what's now called generative AI. But help me understand how it works. Because, I mean, I think a lot of people, you know, are thinking about or, you know,

hearing about breakthroughs in scientific developments and cancer research and climate change technology, things that are going to benefit us, things that will make our lives easier. But at the same time, from what I understand, based on what you've talked about, a lot of the scientists and researchers working with large language models are kind of developing a Prometheus, something that already they know is growing faster and becoming smarter, faster than they ever anticipated. Yeah. So just to say that I was pretty skeptical of a lot of the bigger AI risks when there was a community in San Francisco called the Effective Altruists that have been worried about bigger AI risks for a long time. I was incredibly skeptical of a lot of this stuff. In fact, I actually told them, I actually think you're all are misguided. You're not seeing the AI that's been released right underneath your feet that has already wrecked the world and it's called social media. So just want to say that I'm not walking into this conversation wanting to hype AI capabilities. What changed, though, is in 27, there was a paper at Google published called Attention is All You Need, in which they invented this new kind of AI paradigm of transformers.

I won't go too much into technical details, but we swapped the engine underneath the hood of AI in 2017. And everything that we used to be skeptical of about AI up until 2017, I would have agreed with everybody on. And, you know, there's AI when Siri mispronounces your mom's name, and there's AI when Google Maps gets the directions wrong or mispronounces a street address. But that AI that falls over and makes mistakes

is different than the AI of Transformers, in which basically, it's like a big brain neural network, and you're throwing more data, more training, more compute at it. So, for example, GPT4, they've been $100 million to get a bunch of invidia chips to churn away for something like six months and then come out with this weird digital spaghetti brain. This is a massive neural network. And the thing about it is that as you scale these digital brains,

they end up with more emergent capabilities that no one who built them anticipated. So suddenly when they scaled, you know, GPT4, they tested it and they could explain jokes. You could give in an image of the picture of an iPhone with the bottom of the port. There's like an old VGA cable, like those old monitor cables from the 1990s.

Yeah. And you could say, what's funny about this image? And it explained, well, it's funny because an iPhone can't have a 1990s VGA cable at the bottom of the iPhone. It's not that it had ever seen that image before. It's not that it was trained on that.

And this is not to sort of conjure this sort of mythical blank check of AI is going to have all sorts of magic capabilities. It's just that we know that it gains capabilities that people may not notice for a long time. It took two years, for example, for researchers to figure out that GPT 3.5, the predecessor to GPT4, had research-grade chemistry knowledge, meaning you could ask it questions about, you know, how to synthesize dangerous chemicals. and it would tell you how to do that. By the way, nobody knew that. Nobody knew that it had developed those capabilities on its own. That's right.

And it's confusing, by the way, because I want to also, for those who are listening to this and skeptical, because it's like, well, that's true, but look at how many times it hallucinates and it gets things wrong. That's 100% correct. It's hallucinating and getting a bunch of things wrong. So it's similar, we've never been around this new kind of brain

that is simultaneously in certain ways better than humans at a bunch of things, but also makes really dumb mistakes, like surprising and kind of, almost embarrassing the sticks. It's like a weird combo that we're not used to, but it's because it's an artificially intelligent mind. It's not a kind of mind that we're,

have any previous sort of knowledge about. That's part one of my conversation with Tristan Harris, co-founder of the Center for Humane Technology. You can catch the rest of my conversation with Tristan, where we discuss how AI could undermine the foundations of our society and what we can do to prevent that. That's coming up in part two next week. And thanks for listening to the show.

week, please make sure to click the follow button on your podcast app so you never miss an episode of the show. And as always, it's free. This episode was researched and produced by Alex Chung with editing by John Isabella. Our music was composed by Rumtina Irrublui. Our audio engineer was Neil Rouch. Our production team at How I Built This also includes Carla Estevez, Chris Messini, Casey Herman, J.C. Howard, Catherine Seifer, Carrie Thompson, Malia Agadello, Neva Grant, and Sam Paulson. I'm Guy Raz, and you've been listening to How I Built This Lab.