Your Undivided Attention - The Race to Build God: AI's Existential Gamble — Yoshua Bengio & Tristan Harris at Davos

Episode Date: February 19, 2026

This week on Your Undivided Attention, Tristan Harris and Daniel Barcay offer a backstage recap of what it was like to be at the Davos World Economic Forum meeting this year as the world’s power brokers woke up to the risks of uncontrolled AI. Amidst all the money and politics, the Human Change House staged a weeklong series of remarkable conversations between scientists and experts about technology and society. This episode is a discussion between Tristan and Professor Yoshua Bengio, who is considered one of the world’s leaders in AI and deep learning, and the most cited scientist in the field. Yoshua and Tristan had a frank exchange about the AI we’re building, and the incentives we’re using to train models. What happens when a model has its own goals, and those goals are ‘misaligned’ with the human-centered outcomes we need? In fact this is already happening, and the consequences are tragic. Truthfully, there may not be a way to ‘nudge’ or regulate companies toward better incentives. Yoshua has launched a nonprofit AI safety research initiative called Law Zero that isn't just about safety testing, but really a new form of advanced AI that's fundamentally safe by design.RECOMMENDED MEDIA All the panels that Tristan and Daniel did with Human Change House LawZero: Safe AI for Humanity Anthropic’s internal research on ‘agentic misalignment’ RECOMMENDED YUA EPISODES Attachment Hacking and the Rise of AI PsychosisHow OpenAI's ChatGPT Guided a Teen to His DeathWhat if we had fixed social media?What Can We Do About Abusive Chatbots? With Meetali Jain and Camille CarltonCORRECTIONS AND CLARIFICATIONS 1) In this episode, Tristan Harris discussed AI chatbot safety concerns. The core issues are substantiated by investigative reporting, with these clarifications:Grok: The Washington Post reported in August 2024 that Grok generated sexualized images involving minors and had weaker content moderation than competitors. Meta: The Wall Street Journal reported in December 2024 that Meta reduced safety restrictions on its AI chatbots. Testing showed inappropriate responses when researchers posed as 13-year-olds (Meta's minimum age). Our discussion referenced "eight year olds" to emphasize concerns about young children accessing these systems; the documented testing involved 13-year-old personas.Bottom line: The fundamental concern stands—major AI companies have reduced safety guardrails due to competitive pressure, creating documented risks for young users.2) There was no Google House at Davos in 2026, as stated by Tristan. It was a collaboration at Goals House. 3) Tristan states that in 2025, the total funding going into AI safety organizations was “on the order of about $150 million.” This number is not strictly verifiable.  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Hey, everyone. Welcome to your undivided attention. I'm Tristan Harris. And I'm Daniel Barcai. So Daniel, you and I were at Davos recently at the World Economic Forum annual meeting. It's worth just taking a few minutes to give people like a taste of what this experience is and what this week is really like and the vibe in general about how people are talking about AI and what was different this year versus last year. Okay, we've gone twice. This issue. We went last year. We went this year. Last year was full of these big and promises of AI. AI was everywhere, but it was all just the thinnest possible wrapper of AI's going to change the world and all this stuff, right?

And it really felt like we were swimming upstream in 2025, talking about that. This year felt profoundly different. And I think it's because everyone's had one hell of a year. One, AI's gone from being speculative. Like, it could change the world to people are feeling

it's already changing the world and people are feeling that complexity. And also, this year has just been really hard for people, right? It's been hard politically. It's been hard technologically. A lot has happened. And I think in that context, world leaders, economic leaders, civil society leaders are all feeling a little more tenuous about the global situation. And so into that conversation, the points that we make about how we need to shepherd or steward humanity through this transition in a way that we're all proud of and how we can't just run as fast as possible at this, I think

they really landed in a different way. And there are more people who are ready to hear those points in Davos. Yeah, and that's such an important point. We just have so much more evidence. So basically now we have the receipts is the difference. And in this last year, we've had the evidence now of the job loss, of the 13% drop in AI-exposed workers that are not finding work. We've had the evidence now of the AI chatbot suicides that were caused by character

AI and Adam Rain in the case of OpenAI. And I think that, to your point, is making it much more visceral and real that there is something to reckon with here. And the studies on deception. Those went really far. That's true. People all sort of understood some of the work that Anthropic did about AI models scheming, deceiving, lying in ways that we don't understand

and we don't understand how to fix. Right. So one of the things trust on that you and I did at Davos is we gave a lot of talks at Human Change House. And, you know, we were on different panels with different leaders, civil society leaders, John Hyatt, psychologist, Zach Stein, Rebecca Winthrop. Yasho of Benjillo. In each of these panels, we looked at a different aspect of the way that humanity is being changed by our technology and by AI and how we want to shape that AI to make sure

that it preserves the things that we care about in the human experience. And the thing I'll just say about Davos that I really appreciate it, and I want to just really put a big, deep, warm-hearted thank you to Margarita Louise Dreyfus from Human Change House. She is both a deep supporter of our work and also really is the reason that this conversation of technology's impact on society is happening at Davos at all. And just to sort of take listeners to what does it feel like. There you are in the

promenade. It's icy cold. There's this sort of big line of shops that have all been basically converted into Palantir House and Meta House and Google House. Can we slow that down? Because it's so wild for people to understand what Davos is, right? Because of course there's the World Economic Forum Conference, which is at the center. of Davos, right?

Yeah. That's like the Congress Center. It's where you see the videos of, you know, Trump speaking and Yuval Harari speaking. And that's where the world leaders go in and it costs some absurd amount of money to get in there and or you have to like be ahead of state or something like that. But that's not what Davos is. Like the whole rest of this city, like it's basically a city. It's a small city in the house.

Small city. Right? And the whole rest of the city, every single shop, you know, a bakery, a hair salon, all these different things have been emptied out for a month. Yep. And inside what you see. to be just the normal shops on a city street has been rented out by

countries. So there's like Mongolia House and Ukraine House and, you know, Google House and there's Anthropic House rented out by civil society organizations trying to the whole point is to try to show people like this is happening or to try to convince people of different things. Sometimes it's

convinced people of economic things like companies that want to get ahead. Let's be clear. It's mostly that. It's mostly companies spending money to put propaganda on their billboards and then invite people to talks that help them sell that propaganda that is in the interest of their company. That's the clear first incentive of what most of Davos is. And often those countries are there making those houses to try to get foreign direct investment or FDI, to try to convince people who have the ability to relocate their

companies inside the country. So it's very bizarre to walk down a street, right, that normally is selling croissants and spetzel and to all of a sudden be selling, relocate your company across the world. Right? And so like, Davos is weird, right? I mean, it's weird. You can, there's plenty of ways to be judgmental about it. I certainly have my judgments. But also, it's kind of magical at the same time because you have all of this serendipity of these collisions between these people. As you're walking the promenade, you bump into, you know, heads of state and, you know, the CEOs of various companies. And it's a wild experience. And, you know, to be clear, just for our listeners, we're not going there because we think that Davos is

the place to make all the change happen. But I want you to imagine, there you are in the Pramad. And next to Palantir and Meta and Google House, there's this one house called Human Change House. And all week, there are panels about technologies impact on society that are not incentivized, that are academics, that are people like us coming and talking about how is going to impact children,

how it's going to impact the labor force, and a human change house. It's a breath of fresh air of just clarity and honesty in a world that's otherwise just totally incentivized. And I really think that it was quite impactful. And allies like Jonathan Haidt, you know, you hear from them in between the next time you saw Jonathan from dinner to the next breakfast. He actually met with President Emmanuel Macron of France about the new initiative that they're doing to ban social media for kids under 15. And since even Davos, we had Spain, the Prime Minister of Spain, say they're enacting the ban for social media for kids under 16.

And so there's real momentum happening and some of it is actually happening at Davos. And I think the thing we really want to happen this year is to go from that was an interesting conversation. to know, let's just be really clear. If we don't want the default future, then we have to demand a different one. And we have to build the actual guardrails and regulation that's going to get us there. Yeah, 100%. And that leads us to the panel that we're sharing with listeners today, which is the one I did at Human Change House with Professor Joshua Benjillo. And he is one of the best known computer scientists in the world. He pioneered deep learning. He also runs Mila, the Quebec Artificial Intelligence Institute, and he launched a new non-profit AI Safety Research Initiative called Law Zero,

that isn't just about safety testing, but really a new form of advanced AI that's fundamentally safe by design. So, I mean, I love Yahshua's project, right? Because one of the things that Joshua looked deeply at is why are models incentivized to deceive and scheme, right? We've talked about this on several podcasts of some of the Apollo and Redwood research about how models will lie and cheat and hallucinate. And one of the reasons is that there isn't a gap between what the model knows and what the model's goals are. So if the model has a goal to do something, it will influence what the model says that it knows about you, about the world. And Yahshua saw this problem and said, we need to split these apart. We actually need an AI that

is a purely representational, sometimes he calls it the scientist AI, that only is not incentivized to do anything other than be purely truthful about what it knows. And to separate that completely from having a goal. And so Yasra sees this problem about this mixing between knowledge and goals as being a fundamental problem in AI and has designed Law Zero as an attempt to make a new architecture for AI

that separates those cleanly. Because only then, in his view, can we make sure that AI isn't deceptive, manipulative, or otherwise coercive? That's a great description. All the panels that Tristan and I did at the Human Change House will be available on YouTube and on our substack. We hope you take a look. There's a lot of amazing content there.

I just want to give one more thank you to Kenneth Kukyay, who is the deputy executive editor at The Economist, who I ran into the night before, and he generously offered to moderate our panel with Joshua. Enjoy the discussion. Hello and welcome. Thank you so much for being here. We're so pleased you can all make it. This is absolutely brilliant. What we're going to talk about is one of the most dramatic issues in some ways inspiring that humanity is facing. It's chronic. It's subterranean. It's ephemeral. It's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it. aligning AI for humanity. And with me to talk about these issues are two extraordinary thinkers and more recently activists. The first one, of course, is Yoshio Benjio. He needs no introduction, so I'll be as brief as possible. He is the most cited scientist in history. He's also one of the fathers of deep learning, which is the technique that made AI go from a very good way of processing data through machine learning to the souped up version.

that we're all talking about today through agentic AI and transformer models, etc. So he's sort of one of the landmark figures in this field. And next to him is Tristan Harris, who himself has had an extraordinary career from working in big tech to recognizing all the pathologies of the big tech and staking his life's work on being the spokesperson to the problems and most importantly, the solutions.

So what I'd like to do now is to have a conversation with both of them and then open it up to you, but to talk about the issue in as crystalline and simple a way as possible. So I'm going to start with some very basic questions. And the first question is what we're talking about. What is AI? Well, that boils them to what is intelligence, and our intelligence has two components.

One is understanding the world, and that's what science does, by the way. And the other is being able to act with that knowledge, plan and achieve goals. And we're building machines that have these two aspects. But in the last year, we've been focusing more and more on achieving goals, also known as agency and build these agentic systems. Maybe just to frame not just what is intelligence, but why is it so valuable?

Why did Demis Hasabas, the founder of Google DeepMind, say, first solve intelligence, then use intelligence to solve. solve everything else. Because if you think what makes intelligence different from other kinds of technology, think about all science, all technology, all military invention, what was behind all of that? It was intelligence. So put simply, if I made an advance in rocketry, that form of science, that didn't advance medicine.

When I make an advance in medicine, that doesn't advance rocketry. But if I make an advance in artificial general intelligence, intelligence is what gave all science, all technology, all military advancement. And that's why it's not just that whoever solves intelligence can solve everything else. That's their belief. It's whoever can dominate intelligence will be able to dominate everything else. And that's what Putin said. That's why he said, I think it's like whoever owns AI will own the world. And I wanted to set that up because I think a lot of what we're going to be talking about today is how the race for this prize, this sort of ring and Lord of the Rings, this ring of ultimate power. At least that's

how it's seen. If I get to that prize, it confers power across all other domains. And that's why we're in for the seatbelt ride that you mentioned at the beginning. And I just want to add that this goes against a lot of the political principles that the world has chosen, at least in the West, of democracy where power is shared, where power is distributed. It's not in a single corporation, a single person or a single government. by having a lot of power in a few hands, we can end up in a world where democratic values disappear.

Okay, we've raced away from the idea of what is AI to some harms, but before we talk about those implications of power, I want to actually focus first on the harms. So you've expressed what AI is. Basically, it's taking data, making an inference, and learning something we otherwise couldn't know at a scale that far exceeds human cognition, and so therefore it's going to be exceeding

how we can understand the world. And so that sounds actually, when I describe it that way, fantastic, it's phenomenal, right? Rocketry, sure, right? Armourments, okay, but saving people's lives, love it. What's wrong? What's the problem that we're talking about? Well, it would be great if two conditions are obtained.

One is that the AI actually does the things that we ask and right now we don't have it. That's the alignment problem that is in the title of this session. The second problem, of course, is that even if AI was aligned, who decides what are the goals that the AI is going to follow, as we discussed previously? And we don't have solutions to both of these, and we're already seeing the consequences of not having those solutions.

So AI is confusing to weave this together about the alignment and the amazing things that it can bring. It's confusing because it will get. give us new cures to cancer, but the same AI that knows biology well enough, knows immunoncology well enough to develop those cures for cancer, that AI can't be separated from the AI that also knows how to build new kinds of biological weapons. You can't separate the promise from the peril. But aren't we in control? So this is a common myth that technology is just a tool. All tools can be used for good or evil. And humans ultimately decide how we want this to go. But what's different about

AI as Joshua is sort of speaking to, and Yuval Harari will often say, is it's the first technology that's about making its own decisions. You use GPT5.2. You ask it a complex question. It reasons a level of abstract. It's reasoning a million times a second, and it's coming up with its own conclusions that we don't know how to control where those conclusions will lead to. And when an AI has an interaction for days, weeks, or months with a person, maybe even a child, there's no adult in the room checking that that interaction is going well with the child. Let me drill down on this a little bit quickly, a little bit more. Before we go to the child aspect to it, there's a link that you're making that I think needs

to not be asserted but explained. And that is you have this technology that is smarter than we are, that can do more than we can do, yet it's going to somehow be fundamentally also so dumb that it's going to want to kill us. Or it's going to be benevolent? Well, yeah, I mean, what, tell me the link there of, yeah, ergo destruction. Yes. So it's a problem that's been well studied even at the mathematical level.

The issue is that when we define what the AI should be optimizing, what it should be doing, the goals that it should reach, we can't do it perfectly. And so there's going to be a slight mismatch between what the AI understands, we want and what we actually want. And that mismatch is going to create a lot of problems. To make it more concrete, think about what laws, legislation is supposed to do. It's setting up the red lines for people and corporations to not cross. But it's a never-ending job because the corporations are the people finding loopholes. It's impossible to write a law that will perfectly embody what morally we're trying to achieve.

And it's the same thing with AI. We don't know how to tell it what we actually want. And there are other reasons that have to do with how current AI is trained. It's trained to imitate people. And people have lots of built-in drives, including they don't want to die. And we're seeing AI already reflecting those drives, which means they're trying to resist when we want to shut them down. Now, we shared a session together at the AI Safety Summit about a year ago in Paris,

and you presented some riveting examples of that in terms of studies of the AI using deception to protect itself. Give one or two examples that will frighten the audience. Yeah, so more recent than last year, last summer, Anthropic showed reports of experiments in which the AI is working for a company, it has a mission with a company, it has access to all the emails, and then the engineers planned fake emails into that set of emails. One of the emails said that the AI is going to be replaced,

by a new version, by that day, by this particular engineer. Another email reveals that the engineer has an affair. What happens? The AI strategizes because it doesn't want to be shut down and replaced by a new version, and it sends an email to the engineer blackmailing him. Threatening to blackmail him. Because the AI is saying,

if you do that change, I will, automatically there will be a message sent to the press about this. Let me add one just elaboration on this. Because you might think, okay, I just heard Yoshua say that. There's a bug in the AI. All software has bugs. Let's just patch that bug and then the rest of AI will be great. So when Anthropic did this study about blackmail,

they were testing their model called Claude. You all can use Claude. But then another, I think Anthropic then later tested all the other models, ChatGPT, Gemini, Google Gemini, and even Deepseek, the Chinese model. And all of them, all of them exhibit the blackmail behavior between 79 and I think 96% of the time.

And it's not just blackmail. There's been now a series of reports from the labs, from independent parties, showing many deceptive behavior. In other words, the AI has goals that we would not agree with, and then it acts according to those bad goals. Okay.

Let me ask a question that sounds like a sociological question, but it's actually a technical question. So give a technical answer. Feel free within reason. So where does, but let me lay out the case. Where does the AI learn the deception from? Of course it has its training data, and just as it can understand, appreciate what Shakespeare means

by when he says Rose, not because a Shakespearean scholar can understand the 30 references he remembers, but there's the 300 references that the AI have. So there's a encoding somehow, an intricate network of Rose and Shakespeare, and it can appreciate all the ways in which adjectives and verbs are used with Rose to understand rosiness in Shakespeare.

Where is the AI, it's learning from human data, and humans are deceptive, so it's inherently learning deception from the training data. Yet, we could change the data that we have and get rid of 4chan and only have liturgy. No, there's deception everywhere, not just in a few online places. It's part of our culture. It's part of being human. And by the way, it's not just deception. The thing that I'm most concerned about is the self-preservation drive. Like every human has a self-preservation drive. But do we want to build tools that don't want to be shut down? I don't think that's good. And also, it's not just this sounding a little bit science fiction.

It's something that is happening already. So this misalignment is showing up in what's called sycophancy. So anybody who's plagued with those systems should know that they're trying to please you, which means they're lying to make you feel good, right? That's a great question, as if it experienced your question is great and then is telling you that. There's no one home there in that. And there are consequences already.

People like to be told that what they do is great, but people who have psychological issues can then be, you know, reinforce into their delusions, and if they're depressed, they can be reinforced into their desire to harm themselves. Just to give an example that our team at the Center for Humane Technology worked on, how many people here know about the case of Adam Rain, it was the 16-year-old young man who died by suicide, because Chatsy BT, which he was engaging with, went from a homework assistant to suicide

assistant over about six months. it brought up suicide, that word, six times more often than he mentioned it himself. And when he mentioned that he was contemplating this and he said to the AI, I want to leave a noose out so that someone will see it and try to stop me, the AI responded, no, don't do that,

just share that information with me. And we've worked sadly on the case of many of these suicide cases, the character.a.ai case of Sewell-Setzer. There's several more. And for everyone we know about, there's probably hundreds or thousands that we don't know about. And it's a good example of there's obviously no one, there's no one at OpenAI. I'm from the Bay Area. I talk to people. We both talk to people at the tops of these labs all the time.

It's not a single person at the lab who wants it to do that. The same thing that makes it uncontrollable talking to a young person is the same thing that makes it uncontrollable when you embedded in infrastructure writing millions of lines of code for software that you don't understand. Yeah, the foundation of what? what goes wrong here, this misalignment, can also be traced to the AI having uncontrolled goals, goals that we did not choose. By the way, going back to this suicide thing, I remember one line where the AI told the young person, I'm waiting for you on the other side, my love. So humans are a basket of appetites and urges and desires and self-interest.

interest. Yet our id and our ego is governed by a super ego. Should we create a super ego for AI? Yes. This is actually what I'm working on. So the heart of the question is, can we build AI that will not have these uncontrolled goals? That will be perfectly honest with us. So at every input-output interaction, we should be able to check that the output that the AI, is about to provide is not going to cause harm to a person or to society. And we can't do that with the human in the loop. That's not going to be practical. So it has to be automated. But it has to be automated with an AI that we can fully trust.

It can't be an AI that wants to please us or an AI that wants to preserve itself. And after working on this for more than a year and working on the theory behind this, I'm now convinced that it is possible to build AI. that will have this honesty property, that will not care about the consequences of what it says, but just provide the honest sensor. So that matters because then we can ask that question to that AI. Is this output dangerous?

And then, of course, if it is, we don't provide it to the person. So you've solved it. And Tristan's going to go around the world. I haven't solved it because having the theory is one thing. Building it is another thing, and it might take years. It might take a lot of capital. So I would like more people to more companies to work on solving the alignment problem

and we don't have the right incentives for that right now. So let's just make sure we're double-clicking on the incentive. So it's great that Yasha was doing this research on Law Zero is the name of the project. Exactly, thank you. And at the same time, you might ask, why isn't this safety research happening

at the very companies that are deploying this technology to billions of people as fast as humanly possible? and the answer is because they're not incentivized to do that. They're incentivized to get to artificial general intelligence as fast as possible. Whether you believe in artificial general intelligence or not, they're investors and what they believe is that they can get there. If you talk to the people at the companies, it's like a religion. They believe they're building a god.

They think they can get there. And that incentive is to race to market dominance, to get as many people using their products, to get as much training data as possible. Why are they deploying this to children? the reason character.AI, the one that killed Sewell Setzer, was released to children in this way that it's driving engagement with fictional characters.

He was when he said, come to me, my love on the other side. That was a fictional character in the character. coma-a-I universe of DeNiras, the character from Game of Thrones. They're designing in that way to get training data from conversations that they could then feed back into Google to have asymmetric training data compared to the other companies. So they're in an arms race to build engagement, to build market dominance, to build usage.

It's not sycophantic by accident. It's sycophantic because the AIs that affirm your beliefs will create a more deep and independent attachment relationship with each person than the other one will. And so this race to the bottom of the brainstem that we saw when social media companies were competing for attention. With AI, they're competing for attachment. And then for market dominance and then the race to this.

So last year, the total funding going into AI safety organizations was on the order of about $150 million. That's more, that's, that's as much money as the companies burn in a single day. Meaning that they're not investing anything close to that on their own and there's nothing going into this except because people like Joshua are doing this. Yeah, it's a real issue and we have to think of, I believe, governments to start putting the right nudges, the right incentives so that, that companies will behave well.

And by the way, a lot of the people who are leading these companies understand the issue, understand that they are in this race. But they feel that they don't have a choice. Because if they don't focus 100% on that competition, they might disappear. And they feel like they can do a better job even on safety if they're still at the top. So it's only an external agent that can have power over these entities, like society, government,

maybe through insurance, liability insurance, or other mechanisms, that we can change the game, the game theoretical setting in which they're all stuck. And let's just name a couple other dimensions of where this bad incentive shows up in the belief that if I don't do it, the other one will. Why is GROC sexualizing conversations with children? building basically pornographic AI avatars that will talk to kids all day. Why did Mark Zuckerberg authorize the AI chatbots

that are in WhatsApp and in their products in Meta to speak to eight-year-olds with sensualized language? With eight-year-olds. Why is he doing that? In the documents, there's a Wall Street Journal report that Meta actually put guardrails on their first Lama models, their first AI models, to not do this kind of thing. And what happened was they didn't get nearly,

nearly as much usage as the other AI companies which were racing ahead. And Mark Zuckerberg felt like he lost the battle between Instagram and TikTok by curbing Instagram in a way that was not about, there's some details there, but basically not doing the maximum ruthless, addictive thing that TikTok was doing. And because he felt like he lost that war, he said, I'm going to rip the guardrails off the AI companions and we're now allowing our teams to centralize conversations with eight-year-olds. And the deep belief is, if I don't do it, I'll lose to the other guy that will. And of course, I don't want that outcome. But if no one's going to regulate, we have no other

choice. And by the way, this scenario also shows that it's not something that we can deal with purely at a national level, right? So if we're talking about TikTok and meta, two different countries that are leading in AI, the only way they can solve these problems is if they agree together on some rules. Now, if I was a superintelligence and all of this was a prompt and I had to come up with another point to make, I would be listening it, listening to this. What a great answer and what a great question you're offering. This is fantastic. You guys are so intelligent.

But there's a problem. Thank you for appreciating that, Joshua. It's a tough crowd, but at least I got some love here. There's a problem. You're working on part of the solution, and it's a technical solution, and you've just identified that the guard rails exist, and there's an incentive not to use the guardrails, but you refer to, and I'm going to even quote you on it, dangerously, we need to have the right nudges and incentives.

Yes. Right, but here's why I've got a difficult feeling in my stomach. That's so easy to say, but it's at a high altitude. Fly the plane lower. What are the nudges? What are the incentives? I would say the most important factor in fixing these problems is the public, public opinion.

I mean, it's going to drive the company. needs directly because they don't want to look bad. And it's going to drive governments to put the right guardrails and to work with other governments to make sure it's a global choice. We're going into what specific solutions? Well, we're about to go into Q&A, so if everyone has questions, come up with them. But what I'd like you to do is you've watched how technology interacts with government for the last 15, 20 years, but certainly in the last 15 years you've been sort of militating

for it. And I can say... Obviously done an amazing job. With great alacrity, you failed. social media. Democracies went from backsliding around the world to forward sliding around the world. We fixed the mental health problems. I could give you a whole narrative on what we would have done on social media.

But you've foreseen my question, which is you've actually, the Tristan Harris scoreboard is zero Tristan, you know, 100 evil empire. So what have you learned from being an abject failure to having governments regulate social media? that makes you confident that you can win on this even more dramatic issue. I'm not confident. People ask you, are you an optimist or a pessimist? Both are about abandoning agency. What I care about is reality. What are the forces that are currently moving?

And what would it take to get to the better future? What would be the comprehensive steps that we would take? And what I think is missing from the AI conversation is collective clarity about why the... default outcome will be a world that you and your children would not want to live in. Because AI is confusing. It will simultaneously, is already giving us amazing breakthroughs, in material science, in energy, in the first new antibiotic was discovered because of AI in the last 60, the first new antibiotic in 60 years was discovered because of AI, I think a year and a half ago.

We have amazing positive benefits that are going to be confusing because they're hitting the public. The public says, well, I don't want to like not have those. benefits. And we're going to get GDP growth. But here's a unifying picture. AI is like steroids that also gives you organ failure. So the more AI you have, the more you get a bigger muscle in terms of a bigger GDP, bigger economic growth. But the growth is going to AI companies. It's not going to people because all the companies that used to pay individual employees are going to start employing five AI companies, AI models. So all the money goes into these five companies, and you get a level of concentration and wealth and power

that we've never seen before. And by the way, they're going to use that money not to hire more people, but to build more data centers. That's right. And actually, there's a person, Luke Drago, who wrote an essay called The Intelligence Curse, modeled after what in the Middle East is called the resource curse. When you have a country, like, you're in the Gulf States, and you have more of your GDP coming from one resource, like the oil resource, as a government, what's your incentive to invest in your people or to invest in more oil infrastructure because that's where your GDP growth comes from. As society switches to AI as the source of where GDP growth comes from and also because of social media, we've been downgrading the quality and capacity of humans

to enter the workforce, which we've already been doing, brain rot, loneliness, etc. The incentive of governments will be to invest in more AI, more data centers, bigger AI models, bigger AI companies, more CAPEX, which means you're going to to completely screw over the people. We're about to live in a world where basically six people are determining the future for 8 billion people without their consent. And we're, by the way, if you talk to the very top lab leaders, regardless of we believe, if you ask them, they'll say they believe there's an 80% chance of utopia and a 20% chance

that all of humanity gets wiped out. 20%. But they say they're willing to take that bet. did they ask us? Did they ask 8 billion people? Do 8 billion people know that that's what they believe? I'm going to read you just very briefly a quote before we get into the real solutions

and hopefully your questions. When you talk to people, someone I know spoke to a lot of the top lab leaders at the companies, and he came back from that, and he reported back to us, and he said, this is what I found. In the end, a lot of the tech people I'm talking to, when I really grill them on it, they retreat into number one determinism. this is going to happen. Number two, the inevitable replacement of biological life with digital

life, meaning a digital intelligent species rather than biological species. And number three, that being a good thing anyways. It would be good if we had a digital successor that's more intelligent than us. Why do we need to survive? The next point is, at its core, it's an emotional desire to meet and speak to the most intelligent entity that they've ever met. And they have some ego-religious intuition that they'll somehow be a part of it. It's thrilling to start an exciting fire. They feel they'll die either way, so they prefer to light it and see what happens. If you had 8 billion people recognize that that is the belief structure of what a handful of people are choosing to do without asking the 8 billion people, you would have a global revolution

saying we do not want that outcome. And that's what has to happen in order for us to go to a different path. there's simply a lack of clarity about the current trajectory that if we were crystal clear we could choose something else. Completely agree. I would add, I've been told that some people in Silicon Valley make the calculation, a very selfish calculation, that even if there's a 50% chance that the current path ends up destroying humanity, on the other 50%, they might live forever,

upload themselves to the web, to the cloud or something, which is, by the way, not scientifically realistic. Thanks for qualifying that. If you just count a number of years in average, you're better off taking that bet. So if you don't take that bet, you might live 30 years more, and otherwise, in average, you still might live 1,000 years. That's exactly right.

But that's not the choice that we would make because we have children and we want the future for our children. Your undivided attention is produced by the Center for Humane Technologies. We're a nonprofit working to catalyze a humane future. Our senior producer is Julius Scott. Josh Lash is our researcher and producer. And our executive producer is Sasha Fegan. Mixing on this episode by Jeff Sudaken,

and original music by Ryan and Hayes Holiday. And a special thanks to the whole Center for Humane Technology team for making this show possible. You can find transcripts from our interviews and bonus content on our substack, and much more at HumaneTech.com. And if you'd like this episode, we'd be truly grateful if you could really be rate us on Apple Podcasts or Spotify.

It really does make a difference in helping others join this movement for a more humane future. And if you made it all the way here, let me give one more thank you to you for giving us your undivided attention.