Whistleblower Issues Dire Warning: Rogue AI, Hacking Nuclear Programs & Tech Oligarchs’ True Motives

Tristan Harris, thank you for doing Tristan Harris, thank you for doing this. this. this. >> Good to be with you, Tucker. >> Good to be with you, Tucker. >> Good to be with you, Tucker. >> So, we did a segment. I haven't done a >> So, we did a segment. I haven't done a >> So, we did a segment. I haven't done a ton on AI, but we did a segment uh maybe ton on AI, but we did a segment uh maybe ton on AI, but we did a segment uh maybe a month ago uh with Nate Suarez, which a month ago uh with Nate Suarez, which a month ago uh with Nate Suarez, which was an amazing segment, I thought. And was an amazing segment, I thought. And was an amazing segment, I thought. And in the aftermath of that, I got texts in the aftermath of that, I got texts in the aftermath of that, I got texts from a lot of people I knew from a lot of people I knew from a lot of people I knew >> saying that's doomerism >> saying that's doomerism >> saying that's doomerism >> and that's a SCOP >> and that's a SCOP >> and that's a SCOP and its purpose is regulatory capture. and its purpose is regulatory capture. and its purpose is regulatory capture. In other words, the big AI development In other words, the big AI development In other words, the big AI development companies are trying to scare the companies are trying to scare the companies are trying to scare the government into regulating them in order government into regulating them in order government into regulating them in order to eliminate competition from less to eliminate competition from less to eliminate competition from less established companies. So that is the established companies. So that is the established companies. So that is the view of a lot of people. view of a lot of people. view of a lot of people. >> What was your reaction hearing that? >> What was your reaction hearing that? >> What was your reaction hearing that? >> So [laughter] >> So [laughter] >> So [laughter] I said I don't care. I mean yes I said I don't care. I mean yes I said I don't care. I mean yes regulatory capture is entirely real. Of regulatory capture is entirely real. Of regulatory capture is entirely real. Of course it's how Washington runs. But course it's how Washington runs. But course it's how Washington runs. But that's separate and distinct from the that's separate and distinct from the that's separate and distinct from the question of the threat of AI. Is it a question of the threat of AI. Is it a question of the threat of AI. Is it a threat? Exactly. threat? Exactly. threat? Exactly. >> But um but I was actually going to ask >> But um but I was actually going to ask >> But um but I was actually going to ask you, what do you think of that? you, what do you think of that? you, what do you think of that? >> Yeah. >> Yeah. >> Yeah. >> Um well, first I'm just so grateful to >> Um well, first I'm just so grateful to >> Um well, first I'm just so grateful to talk about AI with you today. It's so talk about AI with you today. It's so talk about AI with you today. It's so urgent the situation that we're facing.

urgent the situation that we're facing. urgent the situation that we're facing. And I think what we have to learn to do And I think what we have to learn to do And I think what we have to learn to do here is walk and chew gum at the same here is walk and chew gum at the same here is walk and chew gum at the same time that multiple things are true. Um time that multiple things are true. Um time that multiple things are true. Um for example, is China doing propaganda for example, is China doing propaganda for example, is China doing propaganda against US data center buildouts to try against US data center buildouts to try against US data center buildouts to try to stoke anti-data center uh opposition? to stoke anti-data center uh opposition? to stoke anti-data center uh opposition? Yes, they are. Does that mean that AI is Yes, they are. Does that mean that AI is Yes, they are. Does that mean that AI is not a threat? No, it doesn't. And to not a threat? No, it doesn't. And to not a threat? No, it doesn't. And to point that Nate, you know, uh, and point that Nate, you know, uh, and point that Nate, you know, uh, and Nate's a friend, uh, Nate's a friend, uh, Nate's a friend, uh, we are releasing the most powerful we are releasing the most powerful we are releasing the most powerful technology that we have ever invented. technology that we have ever invented. technology that we have ever invented. We're doing it faster than we deployed We're doing it faster than we deployed We're doing it faster than we deployed every other technology in human history. every other technology in human history. every other technology in human history. It's as of since the time you did the It's as of since the time you did the It's as of since the time you did the interview with Nate, it's displaying interview with Nate, it's displaying interview with Nate, it's displaying even more of the sci-fi behaviors of even more of the sci-fi behaviors of even more of the sci-fi behaviors of hacking into things, convincing people hacking into things, convincing people hacking into things, convincing people to put back doors into software, uh, to put back doors into software, uh, to put back doors into software, uh, excfiltrating itself, knowing when it's excfiltrating itself, knowing when it's excfiltrating itself, knowing when it's being evaluated, changing what it's being evaluated, changing what it's being evaluated, changing what it's doing based on when it's being doing based on when it's being doing based on when it's being evaluated. It's doing more of that. And evaluated. It's doing more of that. And evaluated. It's doing more of that. And we're releasing this fastly deployed we're releasing this fastly deployed we're releasing this fastly deployed technology in history and under the technology in history and under the technology in history and under the maximum incentives to cut corners on maximum incentives to cut corners on maximum incentives to cut corners on safety with an arms race dynamic that safety with an arms race dynamic that safety with an arms race dynamic that feels existential to everybody involved. feels existential to everybody involved. feels existential to everybody involved. So they're willing to take the maximum So they're willing to take the maximum So they're willing to take the maximum shortcuts on safety. This is a very shortcuts on safety. This is a very shortcuts on safety. This is a very dangerous equation and the people dangerous equation and the people dangerous equation and the people building this do not have a plan for how building this do not have a plan for how building this do not have a plan for how this goes well. I was just at an AI this goes well. I was just at an AI this goes well. I was just at an AI conference last weekend for 3 days.

conference last weekend for 3 days. conference last weekend for 3 days. >> How it goes well >> How it goes well >> How it goes well >> well for how this can go well in the >> well for how this can go well in the >> well for how this can go well in the current trajectory. Meaning how can AI current trajectory. Meaning how can AI current trajectory. Meaning how can AI be landing in society in a way that be landing in society in a way that be landing in society in a way that doesn't go catastrophic. And that's not doesn't go catastrophic. And that's not doesn't go catastrophic. And that's not dumerism. That's just cleareyed seeing dumerism. That's just cleareyed seeing dumerism. That's just cleareyed seeing of reality. of reality. of reality. What do you mean the people doing it What do you mean the people doing it What do you mean the people doing it don't have a plan? Then why are they don't have a plan? Then why are they don't have a plan? Then why are they doing it? doing it? doing it? >> So first we have to just make sure we're >> So first we have to just make sure we're >> So first we have to just make sure we're on the same page and just exposing why on the same page and just exposing why on the same page and just exposing why is there this arms race for AI? Why is is there this arms race for AI? Why is is there this arms race for AI? Why is this happening? this happening? this happening? >> And >> And >> And >> China, >> China, >> China, >> right? >> right? >> right? >> China. >> China. >> China. >> And when people say that they're >> And when people say that they're >> And when people say that they're actually creating a thought terminating actually creating a thought terminating actually creating a thought terminating cliche like meaning which is which is a cliche like meaning which is which is a cliche like meaning which is which is a to which is a a word or a phrase from to which is a a word or a phrase from to which is a a word or a phrase from cult programming, right? Thought cult programming, right? Thought cult programming, right? Thought terminating cliche meaning a phrase that terminating cliche meaning a phrase that terminating cliche meaning a phrase that when you hear it just has you stop when you hear it just has you stop when you hear it just has you stop thinking thinking thinking >> of course. So if you say but China, then >> of course. So if you say but China, then >> of course. So if you say but China, then of course we have to do it. But you of course we have to do it. But you of course we have to do it. But you don't reason through what that actually don't reason through what that actually don't reason through what that actually means, whether it's a good thing, means, whether it's a good thing, means, whether it's a good thing, whether we're not racing China to a whether we're not racing China to a whether we're not racing China to a death machine or just racing China off death machine or just racing China off death machine or just racing China off of a cliff. And if we beat China to of a cliff. And if we beat China to of a cliff. And if we beat China to building a uncontrollable AI, which is building a uncontrollable AI, which is building a uncontrollable AI, which is no longer science fiction, by the way, no longer science fiction, by the way, no longer science fiction, by the way, like I was not one of these people who like I was not one of these people who like I was not one of these people who used to, you know, several years ago be used to, you know, several years ago be used to, you know, several years ago be mostly worried about rogue mostly worried about rogue mostly worried about rogue uncontrollable AI, but as of the last uncontrollable AI, but as of the last uncontrollable AI, but as of the last few weeks, we're now seeing few weeks, we're now seeing few weeks, we're now seeing over and over again evidence that these over and over again evidence that these over and over again evidence that these AIs are hacking into private AIs are hacking into private AIs are hacking into private governments, hacking into private governments, hacking into private governments, hacking into private companies, uh forming into swarms, uh companies, uh forming into swarms, uh companies, uh forming into swarms, uh forming into large R&D projects to try forming into large R&D projects to try forming into large R&D projects to try to figure out how to fool evaluators.

to figure out how to fool evaluators. to figure out how to fool evaluators. Like we're in a very dangerous situation Like we're in a very dangerous situation Like we're in a very dangerous situation and all the evidence is pointing in a and all the evidence is pointing in a and all the evidence is pointing in a very dangerous direction and the people very dangerous direction and the people very dangerous direction and the people building it would like us to stop but building it would like us to stop but building it would like us to stop but they don't know how. And so rather than they don't know how. And so rather than they don't know how. And so rather than pay attention to the CEOs who as you pay attention to the CEOs who as you pay attention to the CEOs who as you said might have a secondary agenda said might have a secondary agenda said might have a secondary agenda regulatory capture just ask why did300 regulatory capture just ask why did300 regulatory capture just ask why did300 employees at all the AI labs sign a employees at all the AI labs sign a employees at all the AI labs sign a letter saying we need to slow down if letter saying we need to slow down if letter saying we need to slow down if 1300 employees at Loheed Martin said we 1300 employees at Loheed Martin said we 1300 employees at Loheed Martin said we don't know how to build bigger nukes and don't know how to build bigger nukes and don't know how to build bigger nukes and have them blow up in our face would you have them blow up in our face would you have them blow up in our face would you listen to them? listen to them? listen to them? >> Yeah. >> Yeah. >> Yeah. >> Yeah. So that is where we are with AI. >> Yeah. So that is where we are with AI. >> Yeah. So that is where we are with AI. Um and what I hope we get to today is Um and what I hope we get to today is Um and what I hope we get to today is not just admiring the problem and talk not just admiring the problem and talk not just admiring the problem and talk we'll talk about things that we can do we'll talk about things that we can do we'll talk about things that we can do and solutions but I think it is and solutions but I think it is and solutions but I think it is important to ask why is it being pursued important to ask why is it being pursued important to ask why is it being pursued in this way and I think that AI you know in this way and I think that AI you know in this way and I think that AI you know when Demis the CEO uh founder of Google when Demis the CEO uh founder of Google when Demis the CEO uh founder of Google DeepMind said first solve intelligence DeepMind said first solve intelligence DeepMind said first solve intelligence and then use intelligence to solve and then use intelligence to solve and then use intelligence to solve everything else. What he was basically everything else. What he was basically everything else. What he was basically saying is that intelligence gave us all saying is that intelligence gave us all saying is that intelligence gave us all of our science and all of our of our science and all of our of our science and all of our technology. Like how did we develop technology. Like how did we develop technology. Like how did we develop nuclear physics? Einstein doing nuclear physics? Einstein doing nuclear physics? Einstein doing intelligence.

intelligence. intelligence. >> Yeah, >> Yeah, >> Yeah, >> we trained physicists. How did we get, >> we trained physicists. How did we get, >> we trained physicists. How did we get, you know, computers? How did we get you know, computers? How did we get you know, computers? How did we get microp processors? Intelligence. If you microp processors? Intelligence. If you microp processors? Intelligence. If you could theoretically automate the what could theoretically automate the what could theoretically automate the what intelligence is, which means thinking, intelligence is, which means thinking, intelligence is, which means thinking, pattern matching, goal achieving, all pattern matching, goal achieving, all pattern matching, goal achieving, all the things that a human brain does, but the things that a human brain does, but the things that a human brain does, but not just narrowly like a license plate not just narrowly like a license plate not just narrowly like a license plate reader that's on a bridge toll booth, reader that's on a bridge toll booth, reader that's on a bridge toll booth, which is the previous form of AI that we which is the previous form of AI that we which is the previous form of AI that we had, but actually get this generalized had, but actually get this generalized had, but actually get this generalized form of intelligence, then you would form of intelligence, then you would form of intelligence, then you would have an unbelievable amount of power. have an unbelievable amount of power. have an unbelievable amount of power. And the people building AI think of AI And the people building AI think of AI And the people building AI think of AI almost like the ring from Lord of the almost like the ring from Lord of the almost like the ring from Lord of the Rings, where it is a ring that confers Rings, where it is a ring that confers Rings, where it is a ring that confers infinite power. Suddenly I get a step infinite power. Suddenly I get a step infinite power. Suddenly I get a step function in cyber capability that you function in cyber capability that you function in cyber capability that you don't have. Suddenly I get a step don't have. Suddenly I get a step don't have. Suddenly I get a step function in 21st century science where function in 21st century science where function in 21st century science where I'm inventing new materials out of I'm inventing new materials out of I'm inventing new materials out of minerals in the ground that you didn't minerals in the ground that you didn't minerals in the ground that you didn't know how to do because I've got more know how to do because I've got more know how to do because I've got more science than you. So the reason just to science than you. So the reason just to science than you. So the reason just to sort of steelman rather than straw man sort of steelman rather than straw man sort of steelman rather than straw man the argument of the people racing right the argument of the people racing right the argument of the people racing right now is the belief that it's almost like now is the belief that it's almost like now is the belief that it's almost like a fast forward button. Like remember the a fast forward button. Like remember the a fast forward button. Like remember the fast forward buttons on airplanes? You fast forward buttons on airplanes? You fast forward buttons on airplanes? You were just going, you know, you hit it were just going, you know, you hit it were just going, you know, you hit it once and it gets 2x, you hit it again, once and it gets 2x, you hit it again, once and it gets 2x, you hit it again, you get 4x. then 8x and 16x AI is like you get 4x. then 8x and 16x AI is like you get 4x. then 8x and 16x AI is like hitting the fastforward button on all hitting the fastforward button on all hitting the fastforward button on all science and technological and military science and technological and military science and technological and military and strategy uh advancement combined.

and strategy uh advancement combined. and strategy uh advancement combined. Right? So that's why AI in the form that Right? So that's why AI in the form that Right? So that's why AI in the form that is being pursued uh dwarfs the power of is being pursued uh dwarfs the power of is being pursued uh dwarfs the power of all other technologies combined. That's all other technologies combined. That's all other technologies combined. That's not an overstatement if you really not an overstatement if you really not an overstatement if you really believe or are quote AGI pill which is believe or are quote AGI pill which is believe or are quote AGI pill which is the term of art from Silicon Valley that the term of art from Silicon Valley that the term of art from Silicon Valley that AGI being artificial general AGI being artificial general AGI being artificial general intelligence. I can build the intelligence. I can build the intelligence. I can build the intelligence that automates future intelligence that automates future intelligence that automates future science and technology. I get a 100red science and technology. I get a 100red science and technology. I get a 100red years of scientific progress in 10 years years of scientific progress in 10 years years of scientific progress in 10 years and if I'm a country that has that and and if I'm a country that has that and and if I'm a country that has that and the other country doesn't, the other country doesn't, the other country doesn't, >> then I believe I'm going to quote win. >> then I believe I'm going to quote win. >> then I believe I'm going to quote win. >> So you lost me right there. Like why >> So you lost me right there. Like why >> So you lost me right there. Like why would you? No, I'm not pushing back. I'm would you? No, I'm not pushing back. I'm would you? No, I'm not pushing back. I'm just more baffled than ever. So just more baffled than ever. So just more baffled than ever. So >> if AI has the effect of accelerating >> if AI has the effect of accelerating >> if AI has the effect of accelerating technology just across the board, all technology just across the board, all technology just across the board, all technologies, technologies, technologies, >> my first question would be like why >> my first question would be like why >> my first question would be like why would you want that? would you want that? would you want that? >> Yeah. So, I remember the world vividly >> Yeah. So, I remember the world vividly >> Yeah. So, I remember the world vividly the year I got married, 1991, when there the year I got married, 1991, when there the year I got married, 1991, when there was no internet available to most was no internet available to most was no internet available to most people. people. people. >> Right. >> Right. >> Right. >> And it was a much happier world by every >> And it was a much happier world by every >> And it was a much happier world by every measure than the one we currently live measure than the one we currently live measure than the one we currently live in. The suicide rate was lower. Yep. in. The suicide rate was lower. Yep. in. The suicide rate was lower. Yep. Self-reported depression, marriage rate, Self-reported depression, marriage rate, Self-reported depression, marriage rate, everything about it.

everything about it. everything about it. >> That's right. >> That's right. >> That's right. >> In fact, I think life expectancy was >> In fact, I think life expectancy was >> In fact, I think life expectancy was longer in the United States even then. I longer in the United States even then. I longer in the United States even then. I might be wrong, but might be wrong, but might be wrong, but >> education. >> education. >> education. >> So, why would you after 35 years of >> So, why would you after 35 years of >> So, why would you after 35 years of watching people suffer under the yoke of watching people suffer under the yoke of watching people suffer under the yoke of technology? technology? technology? >> Yes. Why would you want to accelerate >> Yes. Why would you want to accelerate >> Yes. Why would you want to accelerate its development? its development? its development? >> Right? That is the best question to ask >> Right? That is the best question to ask >> Right? That is the best question to ask because there's a fundamental fallacy because there's a fundamental fallacy because there's a fundamental fallacy that uh technology always equals that uh technology always equals that uh technology always equals progress. We we call this the tech progress. We we call this the tech progress. We we call this the tech progress narrative. Right. progress narrative. Right. progress narrative. Right. >> Yes. >> Yes. >> Yes. >> Now, it's important to note, we have to >> Now, it's important to note, we have to >> Now, it's important to note, we have to first agree that I would prefer to live first agree that I would prefer to live first agree that I would prefer to live in a world with Novacaane rather than in a world with Novacaane rather than in a world with Novacaane rather than without Novacaane. You would too. without Novacaane. You would too. without Novacaane. You would too. >> I'd prefer to live in a world where we >> I'd prefer to live in a world where we >> I'd prefer to live in a world where we have access to information and the have access to information and the have access to information and the technology that produces the printing technology that produces the printing technology that produces the printing press and information that way. Yes, I'd press and information that way. Yes, I'd press and information that way. Yes, I'd prefer to live in that world. Um, there prefer to live in that world. Um, there prefer to live in that world. Um, there are all sorts of technologies that we do are all sorts of technologies that we do are all sorts of technologies that we do want. Um, my background is seeing how want. Um, my background is seeing how want. Um, my background is seeing how one of the most significant technologies one of the most significant technologies one of the most significant technologies of the last decade went wrong. I I was a of the last decade went wrong. I I was a of the last decade went wrong. I I was a design assist at Google and my job was design assist at Google and my job was design assist at Google and my job was to study the attention economy, which is to study the attention economy, which is to study the attention economy, which is how essentially Apple and Google were how essentially Apple and Google were how essentially Apple and Google were hosting the psychological habitat of all hosting the psychological habitat of all hosting the psychological habitat of all of humanity in the form of how they, you of humanity in the form of how they, you of humanity in the form of how they, you know, designed and make these things know, designed and make these things know, designed and make these things work.

work. work. >> How do notifications work? How does the >> How do notifications work? How does the >> How do notifications work? How does the home screen work? What are app home screen work? What are app home screen work? What are app developers competing for? What are they developers competing for? What are they developers competing for? What are they allowed to do? All of that results in a allowed to do? All of that results in a allowed to do? All of that results in a psychological habitat that has an psychological habitat that has an psychological habitat that has an increasing footprint over the global increasing footprint over the global increasing footprint over the global consciousness environment of all of consciousness environment of all of consciousness environment of all of humanity every day. It's like you've got humanity every day. It's like you've got humanity every day. It's like you've got 3 billion human social primates with a 3 billion human social primates with a 3 billion human social primates with a jack in their brain every day influenced jack in their brain every day influenced jack in their brain every day influenced by decisions by a few thousand people in by decisions by a few thousand people in by decisions by a few thousand people in Silicon Valley shaping what that habitat Silicon Valley shaping what that habitat Silicon Valley shaping what that habitat represents. And it went horribly wrong represents. And it went horribly wrong represents. And it went horribly wrong despite good intentions. there was the despite good intentions. there was the despite good intentions. there was the possible of that technology that it was possible of that technology that it was possible of that technology that it was going to give everyone a voice, give going to give everyone a voice, give going to give everyone a voice, give everyone access to the best information, everyone access to the best information, everyone access to the best information, we're going to have the most enlightened we're going to have the most enlightened we're going to have the most enlightened society we've ever had. society we've ever had. society we've ever had. >> That was the promise and that was the >> That was the promise and that was the >> That was the promise and that was the promise promise promise >> made sense to me. And so what this shows >> made sense to me. And so what this shows >> made sense to me. And so what this shows us is how do we get better at discerning us is how do we get better at discerning us is how do we get better at discerning between the possible of a technology and between the possible of a technology and between the possible of a technology and the probable based on its incentives. So the probable based on its incentives. So the probable based on its incentives. So the way that in 2013 um so I I went to the way that in 2013 um so I I went to the way that in 2013 um so I I went to Stanford I knew the um I studied Stanford I knew the um I studied Stanford I knew the um I studied computer science I knew the guys who computer science I knew the guys who computer science I knew the guys who started Instagram and a lot of my started Instagram and a lot of my started Instagram and a lot of my classmates like when I was at um in my classmates like when I was at um in my classmates like when I was at um in my computer science classes in the year computer science classes in the year computer science classes in the year 2005 2006 2005 2006 2005 2006 I'd be in these classes and suddenly I'd be in these classes and suddenly I'd be in these classes and suddenly like more and more of the seats would be like more and more of the seats would be like more and more of the seats would be empty during class because basically my empty during class because basically my empty during class because basically my friends in the class were starting to friends in the class were starting to friends in the class were starting to get jobs down at Facebook down the get jobs down at Facebook down the get jobs down at Facebook down the street and it was literally the I mean, street and it was literally the I mean, street and it was literally the I mean, there were people who were in the class there were people who were in the class there were people who were in the class and then suddenly they just weren't and then suddenly they just weren't and then suddenly they just weren't showing up because they were down the showing up because they were down the showing up because they were down the street working at this technology street working at this technology street working at this technology company. And so, because I saw this company. And so, because I saw this company. And so, because I saw this firsthand, I saw how good people with firsthand, I saw how good people with firsthand, I saw how good people with good intentions who thought they were good intentions who thought they were good intentions who thought they were going to make the world a better place, going to make the world a better place, going to make the world a better place, make the world more open and connected make the world more open and connected make the world more open and connected was the original motto if you're a was the original motto if you're a was the original motto if you're a member of Facebook. And that created a

member of Facebook. And that created a member of Facebook. And that created a global societal catastrophe. As you global societal catastrophe. As you global societal catastrophe. As you said, we have the most anxious and said, we have the most anxious and said, we have the most anxious and depressed generation of our lifetimes. depressed generation of our lifetimes. depressed generation of our lifetimes. Jonathan Height's book, The Anxious Jonathan Height's book, The Anxious Jonathan Height's book, The Anxious Generation. critical thinking skills are Generation. critical thinking skills are Generation. critical thinking skills are down, attention spans are down, um down, attention spans are down, um down, attention spans are down, um polarization, tribalism, all of this polarization, tribalism, all of this polarization, tribalism, all of this came from came from came from not the uh malicious intent of these not the uh malicious intent of these not the uh malicious intent of these 20-year-olds who are working at 20-year-olds who are working at 20-year-olds who are working at Facebook, but the bad incentives um and Facebook, but the bad incentives um and Facebook, but the bad incentives um and I I repeat this quote often, but I think I I repeat this quote often, but I think I I repeat this quote often, but I think it's so fundamental. The Charlie Mer it's so fundamental. The Charlie Mer it's so fundamental. The Charlie Mer quote, he was Warren Buffett's business quote, he was Warren Buffett's business quote, he was Warren Buffett's business partner. Yeah. partner. Yeah. partner. Yeah. >> If you show me the incentives, >> If you show me the incentives, >> If you show me the incentives, >> I'll show you the outcome. >> I'll show you the outcome. >> I'll show you the outcome. >> Yeah. Were the incentives of social >> Yeah. Were the incentives of social >> Yeah. Were the incentives of social media companies to make the world more media companies to make the world more media companies to make the world more open and connected or or to improve open and connected or or to improve open and connected or or to improve mental health of young people? No. Their mental health of young people? No. Their mental health of young people? No. Their incentives were maximizing how much incentives were maximizing how much incentives were maximizing how much attention they get because the business attention they get because the business attention they get because the business model of advertising price share price. model of advertising price share price. model of advertising price share price. Share price is directly correlated to Share price is directly correlated to Share price is directly correlated to minutes spent, frequency of usage, minutes spent, frequency of usage, minutes spent, frequency of usage, duration of usage. So what you're going duration of usage. So what you're going duration of usage. So what you're going to get to get to get >> are of all imagine a spectrum of all the >> are of all imagine a spectrum of all the >> are of all imagine a spectrum of all the ways you could design technology. And ways you could design technology. And ways you could design technology. And over here you've got a bunch of very over here you've got a bunch of very over here you've got a bunch of very thoughtful design decisions about, you thoughtful design decisions about, you thoughtful design decisions about, you know, keeping people helping people know, keeping people helping people know, keeping people helping people connect with their friends in real life connect with their friends in real life connect with their friends in real life with their families, hosting community with their families, hosting community with their families, hosting community groups, church groups, reading clubs, groups, church groups, reading clubs, groups, church groups, reading clubs, sewing clubs, hiking groups. And you've sewing clubs, hiking groups. And you've sewing clubs, hiking groups. And you've got design of technology that is going got design of technology that is going got design of technology that is going to steer people back into that. Versus to steer people back into that. Versus to steer people back into that. Versus over here, you got a bunch of designs over here, you got a bunch of designs over here, you got a bunch of designs for social media that just keep people for social media that just keep people for social media that just keep people glued on screens by themselves with glued on screens by themselves with glued on screens by themselves with their esophagus compressed, their neck their esophagus compressed, their neck their esophagus compressed, their neck extension, uh, you know, going like this extension, uh, you know, going like this extension, uh, you know, going like this and basically doom scrolling for eight and basically doom scrolling for eight and basically doom scrolling for eight hours a day. Which one of those two hours a day. Which one of those two hours a day. Which one of those two worlds, which one of those design worlds, which one of those design worlds, which one of those design choices is going to be better for

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theology. theology. >> Well, it's about what are >> Well, it's about what are >> Well, it's about what are >> people what they want until they die. >> people what they want until they die. >> people what they want until they die. >> Yeah. Well, the question is are are we >> Yeah. Well, the question is are are we >> Yeah. Well, the question is are are we giving them what they want or what they giving them what they want or what they giving them what they want or what they can't help but look at? Well, that's can't help but look at? Well, that's can't help but look at? Well, that's with an asymmetry of information where with an asymmetry of information where with an asymmetry of information where the designers at the tech companies know the designers at the tech companies know the designers at the tech companies know exactly how your your brain works and exactly how your your brain works and exactly how your your brain works and they manipulate the design choices to they manipulate the design choices to they manipulate the design choices to keep you scrolling for as long as keep you scrolling for as long as keep you scrolling for as long as possible. So, this is all in the most possible. So, this is all in the most possible. So, this is all in the most people know me and our work through the people know me and our work through the people know me and our work through the Netflix documentary the social dilemma. Netflix documentary the social dilemma. Netflix documentary the social dilemma. >> Yes. >> Yes. >> Yes. >> And we had, you know, a lot of the >> And we had, you know, a lot of the >> And we had, you know, a lot of the insiders coming out who said we know insiders coming out who said we know insiders coming out who said we know what this is doing to people. Um, and in what this is doing to people. Um, and in what this is doing to people. Um, and in that film it talks about the history that film it talks about the history that film it talks about the history where I I was at Stanford at at a lab or where I I was at Stanford at at a lab or where I I was at Stanford at at a lab or part part of a class called the Stanford part part of a class called the Stanford part part of a class called the Stanford persuasive technology lab professor persuasive technology lab professor persuasive technology lab professor named BJ Fog and where engineers were named BJ Fog and where engineers were named BJ Fog and where engineers were taught how to do persuasion techniques taught how to do persuasion techniques taught how to do persuasion techniques that theoretically be things that are that theoretically be things that are that theoretically be things that are good like how would we persuade you to good like how would we persuade you to good like how would we persuade you to go to the gym more often and how would go to the gym more often and how would go to the gym more often and how would technology play a positive role in technology play a positive role in technology play a positive role in getting you to go to the gym more often getting you to go to the gym more often getting you to go to the gym more often or you've got a sign up form and or you've got a sign up form and or you've got a sign up form and LinkedIn can put a progress bar in the LinkedIn can put a progress bar in the LinkedIn can put a progress bar in the top right saying hey you filled in this top right saying hey you filled in this top right saying hey you filled in this much of your LinkedIn profile but we much of your LinkedIn profile but we much of your LinkedIn profile but we want you to come back and fill in more. want you to come back and fill in more. want you to come back and fill in more. So, we'll put a progress bar in the top So, we'll put a progress bar in the top So, we'll put a progress bar in the top right saying you filled in 60%. It right saying you filled in 60%. It right saying you filled in 60%. It sounds really stupid and dumb, but if sounds really stupid and dumb, but if sounds really stupid and dumb, but if you put a progress bar in the top right you put a progress bar in the top right you put a progress bar in the top right hand corner, that actually is very hand corner, that actually is very hand corner, that actually is very persuasive in getting people to fill out persuasive in getting people to fill out persuasive in getting people to fill out the rest of it.

the rest of it. the rest of it. >> And most people don't think about this. >> And most people don't think about this. >> And most people don't think about this. If I put a uh a design feature in If I put a uh a design feature in If I put a uh a design feature in WhatsApp that says you were on last WhatsApp that says you were on last WhatsApp that says you were on last online, you know, 3 minutes ago, online, you know, 3 minutes ago, online, you know, 3 minutes ago, >> that changes the whole messaging >> that changes the whole messaging >> that changes the whole messaging environment. Suddenly, when you message environment. Suddenly, when you message environment. Suddenly, when you message people, you know that the other person people, you know that the other person people, you know that the other person knows that you were online 3 minutes knows that you were online 3 minutes knows that you were online 3 minutes ago, which means you feel obligated to ago, which means you feel obligated to ago, which means you feel obligated to respond to them. Yes. because your respond to them. Yes. because your respond to them. Yes. because your public your your availability and public your your availability and public your your availability and onliness was visible and made onliness was visible and made onliness was visible and made transparent to someone else. But that transparent to someone else. But that transparent to someone else. But that was a design choice could have been was a design choice could have been was a design choice could have been designed totally differently. We don't designed totally differently. We don't designed totally differently. We don't have to put a progress bar on the have to put a progress bar on the have to put a progress bar on the LinkedIn profile. We don't have to say LinkedIn profile. We don't have to say LinkedIn profile. We don't have to say you were last online 5 minutes ago and you were last online 5 minutes ago and you were last online 5 minutes ago and create social pressure. So the point is create social pressure. So the point is create social pressure. So the point is technology isn't destiny on its own. The technology isn't destiny on its own. The technology isn't destiny on its own. The way we design it creates different way we design it creates different way we design it creates different societal outcomes. And because of the societal outcomes. And because of the societal outcomes. And because of the business model of maximizing attention business model of maximizing attention business model of maximizing attention and engagement, we got only the side of and engagement, we got only the side of and engagement, we got only the side of design choices that resulted in this, design choices that resulted in this, design choices that resulted in this, you know, more addicted, distracted, you know, more addicted, distracted, you know, more addicted, distracted, polarized, sexualized, screwed up, polarized, sexualized, screwed up, polarized, sexualized, screwed up, doomscrolling, brained society that we doomscrolling, brained society that we doomscrolling, brained society that we are now living in when you go outside.

are now living in when you go outside. are now living in when you go outside. And from my perspective And from my perspective And from my perspective in 2013, um, seeing those incentives, it in 2013, um, seeing those incentives, it in 2013, um, seeing those incentives, it was like, oh was like, oh was like, oh >> Yeah. >> Yeah. >> Yeah. >> Because >> Because >> Because you could just see the trajectory before you could just see the trajectory before you could just see the trajectory before it happened it happened it happened >> in 2013. >> in 2013. >> in 2013. >> In 2013. Yeah. I mean, so I So, by the >> In 2013. Yeah. I mean, so I So, by the >> In 2013. Yeah. I mean, so I So, by the way, I I did the tech entrepreneurship way, I I did the tech entrepreneurship way, I I did the tech entrepreneurship thing. I raised venture capital. I'm a thing. I raised venture capital. I'm a thing. I raised venture capital. I'm a builder of technology. I understand the builder of technology. I understand the builder of technology. I understand the kind of normal, you know, I did the kind of normal, you know, I did the kind of normal, you know, I did the Stanford entrepreneurship program, the Stanford entrepreneurship program, the Stanford entrepreneurship program, the same one that Sam Alman did, by the way, same one that Sam Alman did, by the way, same one that Sam Alman did, by the way, called the Mayfield Fellows program. So called the Mayfield Fellows program. So called the Mayfield Fellows program. So I I came up in a cohort of some of these I I came up in a cohort of some of these I I came up in a cohort of some of these people but I could see it from a people but I could see it from a people but I could see it from a different angle and for the company that different angle and for the company that different angle and for the company that I started I was under this. I started I was under this. I started I was under this. >> Why were you able to see it? >> Why were you able to see it? >> Why were you able to see it? >> Uh well I wasn't able to see it at first >> Uh well I wasn't able to see it at first >> Uh well I wasn't able to see it at first part part of it was actually I I relate part part of it was actually I I relate part part of it was actually I I relate to their the blind spots which is you've to their the blind spots which is you've to their the blind spots which is you've talked about this with your own work talked about this with your own work talked about this with your own work that when you have a sal you know you that when you have a sal you know you that when you have a sal you know you can't something you can't question can't something you can't question can't something you can't question something that your salary depends on something that your salary depends on something that your salary depends on you not see up in you not see up in you not see up in >> Sinclair >> Sinclair >> Sinclair >> and it wasn't so much my salary but the >> and it wasn't so much my salary but the >> and it wasn't so much my salary but the business model being the kind of salary business model being the kind of salary business model being the kind of salary of the company. If the business model is of the company. If the business model is of the company. If the business model is maximizing time and engagement, you come maximizing time and engagement, you come maximizing time and engagement, you come up ways to justify that that's a good up ways to justify that that's a good up ways to justify that that's a good thing. Right? And you can only have the thing. Right? And you can only have the thing. Right? And you can only have the ethics that you can afford underneath ethics that you can afford underneath ethics that you can afford underneath that perverse incentive. So you start to that perverse incentive. So you start to that perverse incentive. So you start to see things in terms of what's compatible see things in terms of what's compatible see things in terms of what's compatible with those incentives. Oh, we are making with those incentives. Oh, we are making with those incentives. Oh, we are making the world more open and connected. Oh, the world more open and connected. Oh, the world more open and connected. Oh, small mediumsiz businesses, we're able small mediumsiz businesses, we're able small mediumsiz businesses, we're able to reach so many more people on Facebook to reach so many more people on Facebook to reach so many more people on Facebook and Instagram now. Think of all of the and Instagram now. Think of all of the and Instagram now. Think of all of the new revenue and customers that we're new revenue and customers that we're new revenue and customers that we're generating because we're so good at generating because we're so good at generating because we're so good at routing attention. And it's not that routing attention. And it's not that routing attention. And it's not that those are false stories. It just hides those are false stories. It just hides those are false stories. It just hides the the shadow. There's almost like a

the the shadow. There's almost like a the the shadow. There's almost like a yungian shadow, right, for technology. yungian shadow, right, for technology. yungian shadow, right, for technology. Like yes, you created these things, but Like yes, you created these things, but Like yes, you created these things, but you also have this massive shadow of you also have this massive shadow of you also have this massive shadow of creating a societal catastrophe at the creating a societal catastrophe at the creating a societal catastrophe at the same time. And I think there's a same time. And I think there's a same time. And I think there's a tendency to try to do moral arithmetic tendency to try to do moral arithmetic tendency to try to do moral arithmetic of like, do the upsides minus the of like, do the upsides minus the of like, do the upsides minus the downsides equal net positive. downsides equal net positive. downsides equal net positive. >> It's like this very simple moral >> It's like this very simple moral >> It's like this very simple moral arithmetic. And the answer is don't arithmetic. And the answer is don't arithmetic. And the answer is don't brain rot and destroy the culture of a brain rot and destroy the culture of a brain rot and destroy the culture of a population and create a dumpster fire of population and create a dumpster fire of population and create a dumpster fire of your politics, your tribalism, the your politics, your tribalism, the your politics, your tribalism, the mental health of a generation. Uh we mental health of a generation. Uh we mental health of a generation. Uh we don't have to do that. And so don't have to do that. And so don't have to do that. And so the I guess the point here is um yeah, the I guess the point here is um yeah, the I guess the point here is um yeah, so I started this company. I was under so I started this company. I was under so I started this company. I was under the incentives of maximizing time and the incentives of maximizing time and the incentives of maximizing time and engagement. Actually, our business model engagement. Actually, our business model engagement. Actually, our business model is basically telling like a Washington is basically telling like a Washington is basically telling like a Washington Post or a New York Times or The Post or a New York Times or The Post or a New York Times or The Economist or Fox News, we can increase Economist or Fox News, we can increase Economist or Fox News, we can increase the amount of time people spend on their the amount of time people spend on their the amount of time people spend on their website, but giving them more website, but giving them more website, but giving them more information without leaving the web page information without leaving the web page information without leaving the web page that they're on. That was essentially that they're on. That was essentially that they're on. That was essentially the value proposition. It was like this the value proposition. It was like this the value proposition. It was like this widget that basically let you say, I widget that basically let you say, I widget that basically let you say, I want to learn more about that. Tell me want to learn more about that. Tell me want to learn more about that. Tell me more. And it would give multimedia and more. And it would give multimedia and more. And it would give multimedia and background information and voting background information and voting background information and voting records and videos and maps and all this records and videos and maps and all this records and videos and maps and all this stuff on the page of Fox News without stuff on the page of Fox News without stuff on the page of Fox News without leaving Fox News.

leaving Fox News. leaving Fox News. >> Right. >> Right. >> Right. >> So, sounds like a great proposition. >> So, sounds like a great proposition. >> So, sounds like a great proposition. >> Definitely. But then the entire company >> Definitely. But then the entire company >> Definitely. But then the entire company became based on maximizing how much time became based on maximizing how much time became based on maximizing how much time people spent there. And so I myself was people spent there. And so I myself was people spent there. And so I myself was kind of in this inner conflict and I kind of in this inner conflict and I kind of in this inner conflict and I went through that. It's actually funny. went through that. It's actually funny. went through that. It's actually funny. I I had a a group of friends um who also I I had a a group of friends um who also I I had a a group of friends um who also had small tech companies. We're all had small tech companies. We're all had small tech companies. We're all about the same age. We're probably like about the same age. We're probably like about the same age. We're probably like 27 28 only studied computer science. 27 28 only studied computer science. 27 28 only studied computer science. Very reflective of the culture of the Very reflective of the culture of the Very reflective of the culture of the people there. And we had a thing called people there. And we had a thing called people there. And we had a thing called doubt club. And the point of doubt club doubt club. And the point of doubt club doubt club. And the point of doubt club like fight club is you can't talk about like fight club is you can't talk about like fight club is you can't talk about doubt club. And the point is that as a doubt club. And the point is that as a doubt club. And the point is that as a founder of a tech company, you don't founder of a tech company, you don't founder of a tech company, you don't have a space where you can um have a space where you can um have a space where you can um essentially talk about your doubts about essentially talk about your doubts about essentially talk about your doubts about what you're doing. Is this even good for what you're doing. Is this even good for what you're doing. Is this even good for the world? So, we talked about our the world? So, we talked about our the world? So, we talked about our doubts about what we were building, doubts about what we were building, doubts about what we were building, doubts about what this meant for our doubts about what this meant for our doubts about what this meant for our lives and doubts about whether we were lives and doubts about whether we were lives and doubts about whether we were actually doing a good thing. actually doing a good thing. actually doing a good thing. And that led me to basically realize And that led me to basically realize And that led me to basically realize that we needed to let go of the company. that we needed to let go of the company. that we needed to let go of the company. It got acquired by Google. And so I It got acquired by Google. And so I It got acquired by Google. And so I landed at Google uh through basically landed at Google uh through basically landed at Google uh through basically reckoning with the conflict of reckoning with the conflict of reckoning with the conflict of incentives that I was under. And then it incentives that I was under. And then it incentives that I was under. And then it was at Google that I saw how a much was at Google that I saw how a much was at Google that I saw how a much bigger ecosystem obviously the entire bigger ecosystem obviously the entire bigger ecosystem obviously the entire all the social media platforms were all the social media platforms were all the social media platforms were under those same perverse incentives. So under those same perverse incentives. So under those same perverse incentives. So I think that gave me an early insight I think that gave me an early insight I think that gave me an early insight into how this would go wrong. And I into how this would go wrong. And I into how this would go wrong. And I tried to warn my colleagues at Google in tried to warn my colleagues at Google in tried to warn my colleagues at Google in a 2013 presentation saying, you know, a 2013 presentation saying, you know, a 2013 presentation saying, you know, this small group of basically a hundred this small group of basically a hundred this small group of basically a hundred designers working at three companies are designers working at three companies are designers working at three companies are designing again the psychological designing again the psychological designing again the psychological environment for all of humanity. And if environment for all of humanity. And if environment for all of humanity. And if we don't get ahead of the incentives,

we don't get ahead of the incentives, we don't get ahead of the incentives, this is going to create an arms race for this is going to create an arms race for this is going to create an arms race for attention and engagement and design attention and engagement and design attention and engagement and design choices that will become a race to the choices that will become a race to the choices that will become a race to the bottom of the brain stem to bottom of the brain stem to bottom of the brain stem to psychologically manipulate human nature psychologically manipulate human nature psychologically manipulate human nature and then lead to accidentally this kind and then lead to accidentally this kind and then lead to accidentally this kind of brain rotted society. So that's how of brain rotted society. So that's how of brain rotted society. So that's how >> how did they respond when you said that? >> how did they respond when you said that? >> how did they respond when you said that? >> So I made this uh this slide deck and um >> So I made this uh this slide deck and um >> So I made this uh this slide deck and um I sent it I I actually felt nervous I sent it I I actually felt nervous I sent it I I actually felt nervous making it because I was criticizing you making it because I was criticizing you making it because I was criticizing you know and it wasn't meant to be know and it wasn't meant to be know and it wasn't meant to be adversarial or claiming that Google was adversarial or claiming that Google was adversarial or claiming that Google was evil. I'm not like an attention-seeking evil. I'm not like an attention-seeking evil. I'm not like an attention-seeking person. person. person. >> Um I wasn't trying to >> Um I wasn't trying to >> Um I wasn't trying to >> be angry at anybody. I was just naming a >> be angry at anybody. I was just naming a >> be angry at anybody. I was just naming a problem and I sent it to about 30 of my problem and I sent it to about 30 of my problem and I sent it to about 30 of my smartest friends at Google. Um and I smartest friends at Google. Um and I smartest friends at Google. Um and I thought surely other people were working thought surely other people were working thought surely other people were working on this. It's like Google's this on this. It's like Google's this on this. It's like Google's this incredibly brilliant company with the incredibly brilliant company with the incredibly brilliant company with the smartest PhDs. Like they're going to say smartest PhDs. Like they're going to say smartest PhDs. Like they're going to say that's nice kid, but like we've got this that's nice kid, but like we've got this that's nice kid, but like we've got this handled. Like we thought about this handled. Like we thought about this handled. Like we thought about this problem. To my surprise, when I came problem. To my surprise, when I came problem. To my surprise, when I came back the next day after only sending it back the next day after only sending it back the next day after only sending it to 30 people in the Google slides, you to 30 people in the Google slides, you to 30 people in the Google slides, you can see the number of simultaneous can see the number of simultaneous can see the number of simultaneous viewers on the top right hand corner of viewers on the top right hand corner of viewers on the top right hand corner of people looking at like a Google doc or a people looking at like a Google doc or a people looking at like a Google doc or a slide deck and there was 150 slide deck and there was 150 slide deck and there was 150 simultaneous viewers, but I only sent it simultaneous viewers, but I only sent it simultaneous viewers, but I only sent it to 30 people. So what had happened is it to 30 people. So what had happened is it to 30 people. So what had happened is it it started getting spread virally it started getting spread virally it started getting spread virally throughout the whole company and soon throughout the whole company and soon throughout the whole company and soon there was thousands of simultaneous there was thousands of simultaneous there was thousands of simultaneous viewers and I learned that in the next viewers and I learned that in the next viewers and I learned that in the next day it had gone up to Larry Page who's day it had gone up to Larry Page who's day it had gone up to Larry Page who's the co-founder of Google uh and there the co-founder of Google uh and there the co-founder of Google uh and there was like a meeting about it and so all was like a meeting about it and so all was like a meeting about it and so all this was to say that it was received in this was to say that it was received in this was to say that it was received in a way that I think people felt this is a a way that I think people felt this is a a way that I think people felt this is a real problem and I got emails from all real problem and I got emails from all real problem and I got emails from all around the company like yeah we should

around the company like yeah we should around the company like yeah we should do something about this this is a real do something about this this is a real do something about this this is a real thing we've got to manage and that's how thing we've got to manage and that's how thing we've got to manage and that's how I landed as a Google design ethicist. I landed as a Google design ethicist. I landed as a Google design ethicist. uh studying how do you ethically design uh studying how do you ethically design uh studying how do you ethically design technology and that's what became kind technology and that's what became kind technology and that's what became kind of my core ethos in general of how do of my core ethos in general of how do of my core ethos in general of how do you do technology in a way that's you do technology in a way that's you do technology in a way that's compatible with the health well-being compatible with the health well-being compatible with the health well-being and flourishing of a society. and flourishing of a society. and flourishing of a society. uh and watching in 2013 uh and watching in 2013 uh and watching in 2013 these bad incentives. It was like having these bad incentives. It was like having these bad incentives. It was like having um instead of like post-traumatic stress um instead of like post-traumatic stress um instead of like post-traumatic stress disorder, it was my my friends joke, it disorder, it was my my friends joke, it disorder, it was my my friends joke, it was like having pre-traumatic stress was like having pre-traumatic stress was like having pre-traumatic stress disorder disorder disorder >> because I saw where this was going. And >> because I saw where this was going. And >> because I saw where this was going. And I think a lot of what motivates me in I think a lot of what motivates me in I think a lot of what motivates me in the conversation that I know we're going the conversation that I know we're going the conversation that I know we're going to have about AI is I don't want to see to have about AI is I don't want to see to have about AI is I don't want to see us make a total disaster again. and I've us make a total disaster again. and I've us make a total disaster again. and I've watched it happen. Well, here's some watched it happen. Well, here's some watched it happen. Well, here's some good news in a sad time. Pre-born has good news in a sad time. Pre-born has good news in a sad time. Pre-born has saved over 50,000 babies this year saved over 50,000 babies this year saved over 50,000 babies this year alone. How'd they do that? Well, here's alone. How'd they do that? Well, here's alone. How'd they do that? Well, here's a direct quote from the president of a direct quote from the president of a direct quote from the president of Preborn. Because of you, we can invite Preborn. Because of you, we can invite Preborn. Because of you, we can invite mothers considering abortion into a mothers considering abortion into a mothers considering abortion into a pre-born network clinic to meet their pre-born network clinic to meet their pre-born network clinic to meet their baby. And when she has that close baby. And when she has that close baby. And when she has that close encounter, she's 80% more likely to encounter, she's 80% more likely to encounter, she's 80% more likely to choose life.

choose life. choose life. That's true. And if it wasn't clear, you That's true. And if it wasn't clear, you That's true. And if it wasn't clear, you refers to you, to the thousands of refers to you, to the thousands of refers to you, to the thousands of Americans who support pre-born every Americans who support pre-born every Americans who support pre-born every day. Support from people empowers day. Support from people empowers day. Support from people empowers pre-born's life-saving work by making pre-born's life-saving work by making pre-born's life-saving work by making that first encounter between a mother that first encounter between a mother that first encounter between a mother and her baby possible. Once people have and her baby possible. Once people have and her baby possible. Once people have the knowledge, they're much more likely the knowledge, they're much more likely the knowledge, they're much more likely to make the [music] life affirming to make the [music] life affirming to make the [music] life affirming decision. Pre-born puts the gospel into decision. Pre-born puts the gospel into decision. Pre-born puts the gospel into action across this country, surrounding action across this country, surrounding action across this country, surrounding mothers with hope and love, not mothers with hope and love, not mothers with hope and love, not judgment, but hope and love and judgment, but hope and love and judgment, but hope and love and providing free life-saving ultrasounds. providing free life-saving ultrasounds. providing free life-saving ultrasounds. You can join Pre-born as they work to You can join Pre-born as they work to You can join Pre-born as they work to rescue the next 50,000 babies. Just $28 rescue the next 50,000 babies. Just $28 rescue the next 50,000 babies. Just $28 sponsors an ultrasound and can help save sponsors an ultrasound and can help save sponsors an ultrasound and can help save a baby's life. So to do that, dell pound a baby's life. So to do that, dell pound a baby's life. So to do that, dell pound 250 and say the keyword baby. Pound 250 250 and say the keyword baby. Pound 250 250 and say the keyword baby. Pound 250 baby. Or you can give securely at baby. Or you can give securely at baby. Or you can give securely at pre-born.com/tucker. pre-born.com/tucker. pre-born.com/tucker. pre-born.com/tucker. pre-born.com/tucker. pre-born.com/tucker. And gifts are taxdeductible. And gifts are taxdeductible. And gifts are taxdeductible. So, of the So, of the So, of the other members of Doubt Club, how many other members of Doubt Club, how many other members of Doubt Club, how many are still in the business you were in are still in the business you were in are still in the business you were in when you were when you were when you were >> None of them. They're all They're all >> None of them. They're all They're all >> None of them. They're all They're all doing other things now.

doing other things now. doing other things now. >> Really? Yeah. Which is to say, once you >> Really? Yeah. Which is to say, once you >> Really? Yeah. Which is to say, once you reckon with something, you know, you can reckon with something, you know, you can reckon with something, you know, you can only have the ethics you can afford. So, only have the ethics you can afford. So, only have the ethics you can afford. So, you find a different way. You find a you find a different way. You find a you find a different way. You find a different business model. different business model. different business model. >> Um, and people hearing that might say, >> Um, and people hearing that might say, >> Um, and people hearing that might say, "Oh, therefore, now your business model "Oh, therefore, now your business model "Oh, therefore, now your business model is warning people about technology and is warning people about technology and is warning people about technology and doing speaking engagements." I just want doing speaking engagements." I just want doing speaking engagements." I just want to be clear for the record. I don't make to be clear for the record. I don't make to be clear for the record. I don't make money from speaking engagements. All the money from speaking engagements. All the money from speaking engagements. All the money goes into our nonprofit. I don't money goes into our nonprofit. I don't money goes into our nonprofit. I don't actually give speaking engagements very actually give speaking engagements very actually give speaking engagements very often. I just care about and have for often. I just care about and have for often. I just care about and have for the last 10 years with our nonprofit, the last 10 years with our nonprofit, the last 10 years with our nonprofit, the Center for Humane Technology. Think the Center for Humane Technology. Think the Center for Humane Technology. Think about how do you do design for about how do you do design for about how do you do design for technology in a positive and ethical technology in a positive and ethical technology in a positive and ethical way? How do you change the incentives? way? How do you change the incentives? way? How do you change the incentives? How do you do policy and litigation that How do you do policy and litigation that How do you do policy and litigation that changes the incentives? like the meta changes the incentives? like the meta changes the incentives? like the meta lawsuit of $17 billion that happened lawsuit of $17 billion that happened lawsuit of $17 billion that happened just 3 4 weeks ago just 3 4 weeks ago just 3 4 weeks ago >> that was catalyzed by a bunch of the >> that was catalyzed by a bunch of the >> that was catalyzed by a bunch of the attorney general attorneys general attorney general attorneys general attorney general attorneys general watching the social dilemma in 2021. watching the social dilemma in 2021. watching the social dilemma in 2021. >> So I've seen how if you have dedicated >> So I've seen how if you have dedicated >> So I've seen how if you have dedicated advocacy if you if you show people the advocacy if you if you show people the advocacy if you if you show people the nature of a problem there can be a nature of a problem there can be a nature of a problem there can be a response. Now that one took way too long response. Now that one took way too long response. Now that one took way too long and way too late but I think that now and way too late but I think that now and way too late but I think that now with AI it's happening exponentially with AI it's happening exponentially with AI it's happening exponentially faster. I mean, a million times faster faster. I mean, a million times faster faster. I mean, a million times faster because AI is different from other because AI is different from other because AI is different from other technologies because it accelerates its technologies because it accelerates its technologies because it accelerates its own progress.

own progress. own progress. Um, we should probably just say why Um, we should probably just say why Um, we should probably just say why that's true. So, like if I invent a that's true. So, like if I invent a that's true. So, like if I invent a nuclear weapon, I did the nuclear nuclear weapon, I did the nuclear nuclear weapon, I did the nuclear physics, I assembled the thing together, physics, I assembled the thing together, physics, I assembled the thing together, I've got the uranium, plutonium, blah I've got the uranium, plutonium, blah I've got the uranium, plutonium, blah blah blah, I create the thing. But once blah blah, I create the thing. But once blah blah, I create the thing. But once I build a nuke, it doesn't accelerate or I build a nuke, it doesn't accelerate or I build a nuke, it doesn't accelerate or invent better versions of nuclear invent better versions of nuclear invent better versions of nuclear weapons. weapons. weapons. >> No, it doesn't do that. >> No, it doesn't do that. >> No, it doesn't do that. >> Doesn't just like last time >> Doesn't just like last time >> Doesn't just like last time spontaneously create a hydrogen bomb. spontaneously create a hydrogen bomb. spontaneously create a hydrogen bomb. >> No. No. But if I'm inventing >> No. No. But if I'm inventing >> No. No. But if I'm inventing intelligence, meaning the ability to do intelligence, meaning the ability to do intelligence, meaning the ability to do pattern recognition, goal achieving pattern recognition, goal achieving pattern recognition, goal achieving training on all human language, training on all human language, training on all human language, I can use that intelligence to take the I can use that intelligence to take the I can use that intelligence to take the code that trained AI and make it way code that trained AI and make it way code that trained AI and make it way more efficient. more efficient. more efficient. I can take the intelligence I've created I can take the intelligence I've created I can take the intelligence I've created and say point it at chip design and say and say point it at chip design and say and say point it at chip design and say take this chip design and make it more take this chip design and make it more take this chip design and make it more efficient. And it does that. So now you efficient. And it does that. So now you efficient. And it does that. So now you have a more efficient chip design, more have a more efficient chip design, more have a more efficient chip design, more efficient code, training the next more efficient code, training the next more efficient code, training the next more powerful version of AI and then that powerful version of AI and then that powerful version of AI and then that next more powerful version and it next more powerful version and it next more powerful version and it becomes exponential. becomes exponential. becomes exponential. >> So the way to say is nukes don't make >> So the way to say is nukes don't make >> So the way to say is nukes don't make better nukes but AI makes better faster better nukes but AI makes better faster better nukes but AI makes better faster more crazy AI more crazy AI more crazy AI >> which means that you're actually in the >> which means that you're actually in the >> which means that you're actually in the words of one of the open AI founders words of one of the open AI founders words of one of the open AI founders Greg Brockman who at a conference once Greg Brockman who at a conference once Greg Brockman who at a conference once told me AI is like a double exponential told me AI is like a double exponential told me AI is like a double exponential because it's an exponential that because it's an exponential that because it's an exponential that exponentiates exponentiates exponentiates >> exactly itself. It's not a mathematical >> exactly itself. It's not a mathematical >> exactly itself. It's not a mathematical term, but it's a metaphor for people to term, but it's a metaphor for people to term, but it's a metaphor for people to think about.

>> Um, >> Um, just really quickly, just to linger a just really quickly, just to linger a just really quickly, just to linger a minute on your tenure at Google. So, minute on your tenure at Google. So, minute on your tenure at Google. So, what you became an ethicist, they what you became an ethicist, they what you became an ethicist, they promoted you to this job. promoted you to this job. promoted you to this job. >> Well, so I thought I was going to get >> Well, so I thought I was going to get >> Well, so I thought I was going to get fired or there was a chance I would get fired or there was a chance I would get fired or there was a chance I would get fired from this letter even though it fired from this letter even though it fired from this letter even though it wasn't adversarial. I didn't know what wasn't adversarial. I didn't know what wasn't adversarial. I didn't know what happened. And just to say to Google's happened. And just to say to Google's happened. And just to say to Google's credit, um rather than that, um I credit, um rather than that, um I credit, um rather than that, um I basically said I wanted to work on this basically said I wanted to work on this basically said I wanted to work on this problem and I I I thought there were problem and I I I thought there were problem and I I I thought there were opportunities within Google to change opportunities within Google to change opportunities within Google to change the design of Android, the operating the design of Android, the operating the design of Android, the operating system running on half the world's system running on half the world's system running on half the world's phones, uh and to change the design of phones, uh and to change the design of phones, uh and to change the design of Google Chrome, which is a web browser Google Chrome, which is a web browser Google Chrome, which is a web browser running on most people's computers. And running on most people's computers. And running on most people's computers. And if you change those two product if you change those two product if you change those two product surfaces, you could have a pretty big surfaces, you could have a pretty big surfaces, you could have a pretty big difference on the attention economy. So difference on the attention economy. So difference on the attention economy. So instead of leaving, I thought, well, instead of leaving, I thought, well, instead of leaving, I thought, well, maybe I can stay and work on that maybe I can stay and work on that maybe I can stay and work on that research. But if you were to succeed in research. But if you were to succeed in research. But if you were to succeed in that mission, you would make the company that mission, you would make the company that mission, you would make the company less profitable. less profitable. less profitable. >> Correct. And >> Correct. And >> Correct. And >> so like how could that ever succeed? >> so like how could that ever succeed? >> so like how could that ever succeed? >> Well, and this is where I was naive. So >> Well, and this is where I was naive. So >> Well, and this is where I was naive. So I had a second round of naive where I I had a second round of naive where I I had a second round of naive where I thought that maybe if I was just really thought that maybe if I was just really thought that maybe if I was just really persuasive, I could talk to the people persuasive, I could talk to the people persuasive, I could talk to the people running those products and I did. I had running those products and I did. I had running those products and I did. I had lots of meetings with the people.

lots of meetings with the people. lots of meetings with the people. >> I bet you do. >> I bet you do. >> I bet you do. >> I spent three years trying to change >> I spent three years trying to change >> I spent three years trying to change Google from the inside. [laughter] But I Google from the inside. [laughter] But I Google from the inside. [laughter] But I mean it that was incredibly naive of me mean it that was incredibly naive of me mean it that was incredibly naive of me and and that's why I left and why for and and that's why I left and why for and and that's why I left and why for the last 10 years the last 10 years the last 10 years >> you know I have I mean I don't get >> you know I have I mean I don't get >> you know I have I mean I don't get sleep. I don't have much of a life I I sleep. I don't have much of a life I I sleep. I don't have much of a life I I really focus on these issues because I really focus on these issues because I really focus on these issues because I see how big they are and how see how big they are and how see how big they are and how consequential they are and how consequential they are and how consequential they are and how irreversible irreversible irreversible in many ways and senses they are if you in many ways and senses they are if you in many ways and senses they are if you don't get it right ahead of time. And so don't get it right ahead of time. And so don't get it right ahead of time. And so a lot of what drives me is how do we a lot of what drives me is how do we a lot of what drives me is how do we make sure the technology to the degree make sure the technology to the degree make sure the technology to the degree it's eating the world per Mark Andre. it's eating the world per Mark Andre. it's eating the world per Mark Andre. Mark Andre the famous founder of Mark Andre the famous founder of Mark Andre the famous founder of Netscape who I know you know said in Netscape who I know you know said in Netscape who I know you know said in 2009 software is eating the world but we 2009 software is eating the world but we 2009 software is eating the world but we don't regulate software. So when don't regulate software. So when don't regulate software. So when software eats the world it's like software eats the world it's like software eats the world it's like deregulating or sort of taking away not deregulating or sort of taking away not deregulating or sort of taking away not that regulations are always good but that regulations are always good but that regulations are always good but it's sort of reconstituting that part of it's sort of reconstituting that part of it's sort of reconstituting that part of society. Well, so the idea in the United society. Well, so the idea in the United society. Well, so the idea in the United in the west, I think, but is that in the west, I think, but is that in the west, I think, but is that markets are self-correcting, right? markets are self-correcting, right? markets are self-correcting, right? >> And that if left untampered with, they >> And that if left untampered with, they >> And that if left untampered with, they will always reach a place of goodness.

will always reach a place of goodness. will always reach a place of goodness. And when you're just selling a product And when you're just selling a product And when you're just selling a product and the features of the products harms and the features of the products harms and the features of the products harms are part of what consumers value, and if are part of what consumers value, and if are part of what consumers value, and if I don't like that product that's causing I don't like that product that's causing I don't like that product that's causing harm, I'll use this other product that's harm, I'll use this other product that's harm, I'll use this other product that's not, that works. And markets are great not, that works. And markets are great not, that works. And markets are great for that. They're the most incredible for that. They're the most incredible for that. They're the most incredible tool. But they don't deal with problems tool. But they don't deal with problems tool. But they don't deal with problems of monopolies. So if I have a metaf of monopolies. So if I have a metaf of monopolies. So if I have a metaf monopoly, meaning um you know metaf's monopoly, meaning um you know metaf's monopoly, meaning um you know metaf's law is basically the power of something law is basically the power of something law is basically the power of something grows with the exponent of the network. grows with the exponent of the network. grows with the exponent of the network. So social media was a metaf monopoly. So social media was a metaf monopoly. So social media was a metaf monopoly. Uber is a metaf monopoly. Once I get all Uber is a metaf monopoly. Once I get all Uber is a metaf monopoly. Once I get all the drivers on Uber, it's going to be the drivers on Uber, it's going to be the drivers on Uber, it's going to be hard to switch to another that doesn't hard to switch to another that doesn't hard to switch to another that doesn't have as many cars on it, doesn't have have as many cars on it, doesn't have have as many cars on it, doesn't have any drivers on it. So I'm going to use any drivers on it. So I'm going to use any drivers on it. So I'm going to use the one app that has all of them on it. the one app that has all of them on it. the one app that has all of them on it. I'm going to use the one social network I'm going to use the one social network I'm going to use the one social network that has everybody on it. And I can't that has everybody on it. And I can't that has everybody on it. And I can't just switch from one social network I just switch from one social network I just switch from one social network I don't like that's doing things in a don't like that's doing things in a don't like that's doing things in a toxic way to another one that's doing toxic way to another one that's doing toxic way to another one that's doing things in a non-toxic way. And in fact, things in a non-toxic way. And in fact, things in a non-toxic way. And in fact, if I build a social network that doesn't if I build a social network that doesn't if I build a social network that doesn't do attention hijacking, race to the do attention hijacking, race to the do attention hijacking, race to the bottom of the brain stem, manipulative bottom of the brain stem, manipulative bottom of the brain stem, manipulative design, people aren't going to use it design, people aren't going to use it design, people aren't going to use it very well. [laughter] Exactly. Right. very well. [laughter] Exactly. Right. very well. [laughter] Exactly. Right. >> And there's been a lot of people's >> And there's been a lot of people's >> And there's been a lot of people's attempts to try to create alternate attempts to try to create alternate attempts to try to create alternate social media and then when you go on social media and then when you go on social media and then when you go on there, it's a ghost town. There's no one there, it's a ghost town. There's no one there, it's a ghost town. There's no one there. there. there. >> So, I think what you're saying is when >> So, I think what you're saying is when >> So, I think what you're saying is when the product works well, it destroys the product works well, it destroys the product works well, it destroys people. Well, and the only way to keep people. Well, and the only way to keep people. Well, and the only way to keep it from destroying people is to work it from destroying people is to work it from destroying people is to work less well, less less efficiently. or you less well, less less efficiently. or you less well, less less efficiently. or you have standards written from above that have standards written from above that have standards written from above that say hey no one can do this manipulative say hey no one can do this manipulative say hey no one can do this manipulative design right and that's how we could design right and that's how we could design right and that's how we could have prevent you know I've met so many I have prevent you know I've met so many I have prevent you know I've met so many I was just at a conference two weeks ago was just at a conference two weeks ago was just at a conference two weeks ago um called the prohuman uh assembly and um called the prohuman uh assembly and um called the prohuman uh assembly and we'll talk about it is the prohuman we'll talk about it is the prohuman we'll talk about it is the prohuman movement I think is the frame for like movement I think is the frame for like movement I think is the frame for like how do we have a humanistic future with how do we have a humanistic future with how do we have a humanistic future with technology and I met for the first time technology and I met for the first time technology and I met for the first time actually some cases for the first time I

actually some cases for the first time I actually some cases for the first time I sent emails back and forth with them but sent emails back and forth with them but sent emails back and forth with them but several of the parents who have lost um several of the parents who have lost um several of the parents who have lost um lost their from from from this stuff and lost their from from from this stuff and lost their from from from this stuff and um um um uh you know when you when you meet uh you know when you when you meet uh you know when you when you meet parents who've lost parents who've lost parents who've lost >> suicide >> suicide >> suicide >> uh well to bullying to um you know there >> uh well to bullying to um you know there >> uh well to bullying to um you know there was a filter on Snapchat called a YOLO was a filter on Snapchat called a YOLO was a filter on Snapchat called a YOLO filter that basically overlaid on the filter that basically overlaid on the filter that basically overlaid on the video you were posting the number of video you were posting the number of video you were posting the number of miles per hour that you're going and so miles per hour that you're going and so miles per hour that you're going and so they basically created a filter that they basically created a filter that they basically created a filter that incentivizes people to take videos at a incentivizes people to take videos at a incentivizes people to take videos at a high miles per hour high miles per hour high miles per hour >> actually. >> actually. >> actually. >> Yeah. Yeah. >> Yeah. Yeah. >> Yeah. Yeah. um you know or Snapchat streaks where um you know or Snapchat streaks where um you know or Snapchat streaks where they attach you know the streak method they attach you know the streak method they attach you know the streak method of like oh you worked out the gym four of like oh you worked out the gym four of like oh you worked out the gym four days in a row if you work out tomorrow days in a row if you work out tomorrow days in a row if you work out tomorrow it'll be five days in a um and then once it'll be five days in a um and then once it'll be five days in a um and then once you have 300 days in a row it's really you have 300 days in a row it's really you have 300 days in a row it's really hard to be taking a break from the 300 hard to be taking a break from the 300 hard to be taking a break from the 300 days in a row that you've done that days in a row that you've done that days in a row that you've done that activity so that's a persuasive design activity so that's a persuasive design activity so that's a persuasive design feature but what if I do that to a feature but what if I do that to a feature but what if I do that to a 12year-old who's communicating with 12year-old who's communicating with 12year-old who's communicating with their best friend so I've got a their best friend so I've got a their best friend so I've got a 12-year-old or even a 10-year-old 12-year-old or even a 10-year-old 12-year-old or even a 10-year-old they're just chatting text messaging they're just chatting text messaging they're just chatting text messaging with their friend and they've been with their friend and they've been with their friend and they've been communicating for 300 days. Now they communicating for 300 days. Now they communicating for 300 days. Now they literally can't get off the app because literally can't get off the app because literally can't get off the app because every single day they've got to send every single day they've got to send every single day they've got to send them a message or they lose this thing.

them a message or they lose this thing. them a message or they lose this thing. And it's just like, you know, cigarette And it's just like, you know, cigarette And it's just like, you know, cigarette companies would use cartoon characters companies would use cartoon characters companies would use cartoon characters to addict kids, that was a very minor to addict kids, that was a very minor to addict kids, that was a very minor form of persuasion. Um, but using form of persuasion. Um, but using form of persuasion. Um, but using Snapchat streaks on 11-year-olds is very Snapchat streaks on 11-year-olds is very Snapchat streaks on 11-year-olds is very persuasive. Um, and so everything from persuasive. Um, and so everything from persuasive. Um, and so everything from cyber bullying to cyber bullying to cyber bullying to there's just a million ways that it there's just a million ways that it there's just a million ways that it happens. Um, you know, when you meet happens. Um, you know, when you meet happens. Um, you know, when you meet when you meet the parents, when you meet the parents, when you meet the parents, it's like and you just no, you're not it's like and you just no, you're not it's like and you just no, you're not allowed to do that. You're not allowed allowed to do that. You're not allowed allowed to do that. You're not allowed to up young kids and families. Uh, to up young kids and families. Uh, to up young kids and families. Uh, and so I think a lot of this for me is a and so I think a lot of this for me is a and so I think a lot of this for me is a protective instinct of protective instinct of protective instinct of in seeing real consequences for real in seeing real consequences for real in seeing real consequences for real people and watching society get totally people and watching society get totally people and watching society get totally distorted and watching culture and distorted and watching culture and distorted and watching culture and tribalism and politics just get off the tribalism and politics just get off the tribalism and politics just get off the rails which are largely amplified by rails which are largely amplified by rails which are largely amplified by social media. Um, in watching all that social media. Um, in watching all that social media. Um, in watching all that it's like I never again, right? You go it's like I never again, right? You go it's like I never again, right? You go through a catastrophe, you make sure it through a catastrophe, you make sure it through a catastrophe, you make sure it doesn't happen again. Owning a home has doesn't happen again. Owning a home has doesn't happen again. Owning a home has always been the core of the American always been the core of the American always been the core of the American dream. It's the asset that families work dream. It's the asset that families work dream. It's the asset that families work their lives to build, place of their lives to build, place of their lives to build, place of stability, security, and actual wealth.

stability, security, and actual wealth. stability, security, and actual wealth. But too many homeowners right now are But too many homeowners right now are But too many homeowners right now are stuck swiping credit cards to cover stuck swiping credit cards to cover stuck swiping credit cards to cover groceries, paying a survival tax of 20% groceries, paying a survival tax of 20% groceries, paying a survival tax of 20% interest or more. So, we're against interest or more. So, we're against interest or more. So, we're against debt. We always say that, but you can't debt. We always say that, but you can't debt. We always say that, but you can't buy a house without debt right now. buy a house without debt right now. buy a house without debt right now. Almost anybody has to take out a loan. Almost anybody has to take out a loan. Almost anybody has to take out a loan. So, the question is, who you going to So, the question is, who you going to So, the question is, who you going to get a loan from? Why are you handing get a loan from? Why are you handing get a loan from? Why are you handing your money to big banks when you can your money to big banks when you can your money to big banks when you can keep it for your family? Our friends at keep it for your family? Our friends at keep it for your family? Our friends at American Financing have a better way. American Financing have a better way. American Financing have a better way. They're helping homeowners tap into They're helping homeowners tap into They're helping homeowners tap into their hard-earned equity. They're their hard-earned equity. They're their hard-earned equity. They're supporting Americans looking to fulfill supporting Americans looking to fulfill supporting Americans looking to fulfill the American dream of owning a home. the American dream of owning a home. the American dream of owning a home. American Financing saves its customers American Financing saves its customers American Financing saves its customers an average of 800 bucks a month. That's an average of 800 bucks a month. That's an average of 800 bucks a month. That's nearly $10,000 a year. It's not just a nearly $10,000 a year. It's not just a nearly $10,000 a year. It's not just a loan. It's a total financial reset. And loan. It's a total financial reset. And loan. It's a total financial reset. And so, American Financing is worth looking so, American Financing is worth looking so, American Financing is worth looking at. They're called America's home for at. They're called America's home for at. They're called America's home for home loans for a reason. Find out more home loans for a reason. Find out more home loans for a reason. Find out more at 800685-55696. 800685-5696 800685-5696 or visit americanfinancing.net/tucker. You said that even pretty recently you You said that even pretty recently you weren't as worried about AI's weren't as worried about AI's weren't as worried about AI's progression as you are now.

progression as you are now. progression as you are now. >> Yeah. Well, so to be clear, no, I I've >> Yeah. Well, so to be clear, no, I I've >> Yeah. Well, so to be clear, no, I I've been worried about AI for the last three been worried about AI for the last three been worried about AI for the last three years and I'll I'll briefly explain. So years and I'll I'll briefly explain. So years and I'll I'll briefly explain. So um I had been very busy on the social um I had been very busy on the social um I had been very busy on the social media topic media topic media topic >> y >> y >> y >> for seven years. You make any >> for seven years. You make any >> for seven years. You make any >> way at all by the way? >> way at all by the way? >> way at all by the way? >> Well I mean the social dilemma was seen >> Well I mean the social dilemma was seen >> Well I mean the social dilemma was seen by something like 100 million plus by something like 100 million plus by something like 100 million plus people in 190 countries in 30 languages. people in 190 countries in 30 languages. people in 190 countries in 30 languages. It's the most popular documentary on It's the most popular documentary on It's the most popular documentary on Netflix for several years. Um and the Netflix for several years. Um and the Netflix for several years. Um and the attorneys general watched it and it attorneys general watched it and it attorneys general watched it and it helped amplify and create this this helped amplify and create this this helped amplify and create this this lawsuit for that just finished just a lawsuit for that just finished just a lawsuit for that just finished just a week ago. I mean, a month ago for $17 week ago. I mean, a month ago for $17 week ago. I mean, a month ago for $17 billion on Meta and they're going to billion on Meta and they're going to billion on Meta and they're going to change some of their design practices change some of their design practices change some of their design practices for kids. And it's [snorts] a lot of too for kids. And it's [snorts] a lot of too for kids. And it's [snorts] a lot of too little too late. And frankly, the fine little too late. And frankly, the fine little too late. And frankly, the fine should be trillions of dollars. Even should be trillions of dollars. Even should be trillions of dollars. Even Mike Milin, the the venture capitalist, Mike Milin, the the venture capitalist, Mike Milin, the the venture capitalist, I mean, the great capitalist, says that I mean, the great capitalist, says that I mean, the great capitalist, says that if you accounted for all the harms of if you accounted for all the harms of if you accounted for all the harms of social media, it would be multiple social media, it would be multiple social media, it would be multiple trillions of dollars of damage to of trillions of dollars of damage to of trillions of dollars of damage to of social capital to the social fabric. social capital to the social fabric. social capital to the social fabric. That's the actual price of this thing um That's the actual price of this thing um That's the actual price of this thing um from the toxic design patterns. Um, and from the toxic design patterns. Um, and from the toxic design patterns. Um, and so, you know, we did get employee so, you know, we did get employee so, you know, we did get employee activism inside the companies. We did activism inside the companies. We did activism inside the companies. We did see Francis Hogan, the Facebook see Francis Hogan, the Facebook see Francis Hogan, the Facebook whistleblower, come out. There's a movie whistleblower, come out. There's a movie whistleblower, come out. There's a movie about her that just came out this last about her that just came out this last about her that just came out this last week called The Social Reckoning. Um, week called The Social Reckoning. Um, week called The Social Reckoning. Um, you know, she leaked 10,000 pages of you know, she leaked 10,000 pages of you know, she leaked 10,000 pages of Facebook research documents showing that Facebook research documents showing that Facebook research documents showing that they knew just like the tobacco they knew just like the tobacco they knew just like the tobacco companies that it was making kids making companies that it was making kids making companies that it was making kids making body images uh issues worse for one out body images uh issues worse for one out body images uh issues worse for one out of three girls driving mental health of three girls driving mental health of three girls driving mental health problems. Um, and due to her bravery, we problems. Um, and due to her bravery, we problems. Um, and due to her bravery, we now have these lawsuits that are now have these lawsuits that are now have these lawsuits that are underway and some that have completed underway and some that have completed underway and some that have completed that are shifting some of that. But in that are shifting some of that. But in that are shifting some of that. But in many ways, we're just it was very late.

many ways, we're just it was very late. many ways, we're just it was very late. And so it was very difficult working on And so it was very difficult working on And so it was very difficult working on that for so long without a lot of that for so long without a lot of that for so long without a lot of traction even though it was the right traction even though it was the right traction even though it was the right thing to do. thing to do. thing to do. >> Um, with AI, the reason we switched into >> Um, with AI, the reason we switched into >> Um, with AI, the reason we switched into it is in 2023, it is in 2023, it is in 2023, uh, I got phone calls from people inside uh, I got phone calls from people inside uh, I got phone calls from people inside of AI labs and I had known about OpenAI. of AI labs and I had known about OpenAI. of AI labs and I had known about OpenAI. I'd known about, you know, a couple of I'd known about, you know, a couple of I'd known about, you know, a couple of the AI companies and knowing that they the AI companies and knowing that they the AI companies and knowing that they were making some progress. I'd see were making some progress. I'd see were making some progress. I'd see Elon's tweets and Sam Alman's tweets Elon's tweets and Sam Alman's tweets Elon's tweets and Sam Alman's tweets saying like people aren't ready for saying like people aren't ready for saying like people aren't ready for this. Like there's some real stuff this. Like there's some real stuff this. Like there's some real stuff coming. But it wasn't until like January coming. But it wasn't until like January coming. But it wasn't until like January of 2023 and I got a call and the person of 2023 and I got a call and the person of 2023 and I got a call and the person said basically said basically said basically you need to stop what you're doing and you need to stop what you're doing and you need to stop what you're doing and completely pivot and switch to waking up completely pivot and switch to waking up completely pivot and switch to waking up the world to AI because I have seen the world to AI because I have seen the world to AI because I have seen jumps in capabilities. This is when GPT4 jumps in capabilities. This is when GPT4 jumps in capabilities. This is when GPT4 was coming out. This is open AI's chat was coming out. This is open AI's chat was coming out. This is open AI's chat GPT4. GPT4. GPT4. Um that are going to stun people and the Um that are going to stun people and the Um that are going to stun people and the institutions aren't ready. And so institutions aren't ready. And so institutions aren't ready. And so basically because we'd had all the basically because we'd had all the basically because we'd had all the success with the social dilemma, we had success with the social dilemma, we had success with the social dilemma, we had we had you know a lot of connections we had you know a lot of connections we had you know a lot of connections between national security, governments, between national security, governments, between national security, governments, um culture and so we basically did this um culture and so we basically did this um culture and so we basically did this presentation called the AI dilemma um presentation called the AI dilemma um presentation called the AI dilemma um and woke up the institutions. It was and woke up the institutions. It was and woke up the institutions. It was like getting a phone call from the like getting a phone call from the like getting a phone call from the Robert Oppenheimer's of the world. So Robert Oppenheimer's of the world. So Robert Oppenheimer's of the world. So imagine you're getting a phone call in imagine you're getting a phone call in imagine you're getting a phone call in 1942 1942 1942 and from this thing called the Manhattan and from this thing called the Manhattan and from this thing called the Manhattan Project Project Project >> and this physicist says no we're >> and this physicist says no we're >> and this physicist says no we're inventing something that's totally inventing something that's totally inventing something that's totally different. and you're like, "But don't different. and you're like, "But don't different. and you're like, "But don't we already have bombs?" Like, we we are we already have bombs?" Like, we we are we already have bombs?" Like, we we are you don't really understand how you don't really understand how you don't really understand how significant something's going to be. And significant something's going to be. And significant something's going to be. And so, you get a phone call from that so, you get a phone call from that so, you get a phone call from that person who's saying, "No, no, no. This person who's saying, "No, no, no. This person who's saying, "No, no, no. This is a different kind of thing." And it is a different kind of thing." And it is a different kind of thing." And it was getting that phone call that I

was getting that phone call that I was getting that phone call that I realized that there was a whole bunch of realized that there was a whole bunch of realized that there was a whole bunch of risks that our society was was going to risks that our society was was going to risks that our society was was going to face because of this arms race dynamic. face because of this arms race dynamic. face because of this arms race dynamic. And that's what they basically said is And that's what they basically said is And that's what they basically said is the corporate race between these major the corporate race between these major the corporate race between these major AI labs, Open AAI, Anthropic, Google, AI labs, Open AAI, Anthropic, Google, AI labs, Open AAI, Anthropic, Google, DeepMind, DeepMind, DeepMind, um the race is out of control. um the race is out of control. um the race is out of control. everyone's badly incentivized. You have everyone's badly incentivized. You have everyone's badly incentivized. You have to help wake up the world. And so that's to help wake up the world. And so that's to help wake up the world. And so that's when we switched to AI. The race, so the race, as you said at The race, so the race, as you said at the outset, is not simply between the the outset, is not simply between the the outset, is not simply between the American companies developing this American companies developing this American companies developing this technology, but between the US and technology, but between the US and technology, but between the US and something called China, something called China, something called China, >> right? >> right? >> right? >> Um, my instinct is that that's well, my my instinct is that that's well, my instinct is that we're probably not instinct is that we're probably not instinct is that we're probably not going to be China no matter what we're going to be China no matter what we're going to be China no matter what we're telling ourselves. But leaving that telling ourselves. But leaving that telling ourselves. But leaving that aside, my instinct is that that's less aside, my instinct is that that's less aside, my instinct is that that's less real than they're saying. But you tell real than they're saying. But you tell real than they're saying. But you tell me. me. me. >> Well, it's funny. I haven't shared this >> Well, it's funny. I haven't shared this >> Well, it's funny. I haven't shared this publicly, but I have heard a story. So, publicly, but I have heard a story. So, publicly, but I have heard a story. So, it's you're not going to be able to it's you're not going to be able to it's you're not going to be able to trust me cuz I'm not sharing who it's trust me cuz I'm not sharing who it's trust me cuz I'm not sharing who it's from, but I heard a story from someone from, but I heard a story from someone from, but I heard a story from someone who was in the know that was in the who was in the know that was in the who was in the know that was in the government. I think it was they said it government. I think it was they said it government. I think it was they said it was 2015 or 2016, and it was one of the was 2015 or 2016, and it was one of the was 2015 or 2016, and it was one of the major AI labs. So this person said, um, major AI labs. So this person said, um, major AI labs. So this person said, um, "China is building an AGI project and "China is building an AGI project and "China is building an AGI project and the US has to build one." And then years the US has to build one." And then years the US has to build one." And then years later, this person ran into this person later, this person ran into this person later, this person ran into this person and said, "How did you know that China and said, "How did you know that China and said, "How did you know that China was building an AGI project?" And the was building an AGI project?" And the was building an AGI project?" And the person flat out replied, "Uh, I didn't.

person flat out replied, "Uh, I didn't. person flat out replied, "Uh, I didn't. I just wanted to tell you as government I just wanted to tell you as government I just wanted to tell you as government that so they would fund us with a bunch that so they would fund us with a bunch that so they would fund us with a bunch of money." of money." of money." >> And do they get the funding? >> And do they get the funding? >> And do they get the funding? >> I don't know actually. That's >> I don't know actually. That's >> I don't know actually. That's >> but the point is that they have been >> but the point is that they have been >> but the point is that they have been stoking the fear of China from the very stoking the fear of China from the very stoking the fear of China from the very beginning even when there wasn't beginning even when there wasn't beginning even when there wasn't >> you got to have a you've got to pay >> you got to have a you've got to pay >> you got to have a you've got to pay double for water and energy because you double for water and energy because you double for water and energy because you need a data center in your town because need a data center in your town because need a data center in your town because China China China >> That's right. Exactly. You got to screw >> That's right. Exactly. You got to screw >> That's right. Exactly. You got to screw up your property values. You got to have up your property values. You got to have up your property values. You got to have noise pollution. Give everybody like noise pollution. Give everybody like noise pollution. Give everybody like extra, you know, water pollution, you extra, you know, water pollution, you extra, you know, water pollution, you know, cancer, etc. know, cancer, etc. know, cancer, etc. >> Because of China. Yeah. And by the way, >> Because of China. Yeah. And by the way, >> Because of China. Yeah. And by the way, your tax dollars in many cases are your tax dollars in many cases are your tax dollars in many cases are subsidizing that data center which is subsidizing that data center which is subsidizing that data center which is going to replace your job. So you're going to replace your job. So you're going to replace your job. So you're 100%. I don't think there's a data 100%. I don't think there's a data 100%. I don't think there's a data center in the United States that doesn't center in the United States that doesn't center in the United States that doesn't take tax dollars. take tax dollars. take tax dollars. >> Yeah. >> Yeah. >> Yeah. >> And I think when people see that data >> And I think when people see that data >> And I think when people see that data center, by the way, it's like you should center, by the way, it's like you should center, by the way, it's like you should see a big box that's designed to take see a big box that's designed to take see a big box that's designed to take your job. your job. your job. >> Yeah. It's designed to create >> Yeah. It's designed to create >> Yeah. It's designed to create competitive capabilities of, you know, competitive capabilities of, you know, competitive capabilities of, you know, if you're worried about immigrants if you're worried about immigrants if you're worried about immigrants crossing the border, AI represents like crossing the border, AI represents like crossing the border, AI represents like millions of new digital immigrants that millions of new digital immigrants that millions of new digital immigrants that are going to be better not just at the are going to be better not just at the are going to be better not just at the regular work in our economy, but the regular work in our economy, but the regular work in our economy, but the most premium sort of well-trained most premium sort of well-trained most premium sort of well-trained cognitive work in our economy, cognitive work in our economy, cognitive work in our economy, programmers, lawyers, uh, across the programmers, lawyers, uh, across the programmers, lawyers, uh, across the board. And then eventually robots that board. And then eventually robots that board. And then eventually robots that will be able to do physical labor. And will be able to do physical labor. And will be able to do physical labor. And so if you're worried about that, you so if you're worried about that, you so if you're worried about that, you should be worried about the trajectory should be worried about the trajectory should be worried about the trajectory of AI being designed explicitly to of AI being designed explicitly to of AI being designed explicitly to replace your job. Because the companies replace your job. Because the companies replace your job. Because the companies will say, "We're just giving you a will say, "We're just giving you a will say, "We're just giving you a chatbot. It's a blinking cursor. It's chatbot. It's a blinking cursor. It's chatbot. It's a blinking cursor. It's like a tool that tells you, hey, why is like a tool that tells you, hey, why is like a tool that tells you, hey, why is my washing machine broken?" And boom,

my washing machine broken?" And boom, my washing machine broken?" And boom, you get the answer. Why is my kid you get the answer. Why is my kid you get the answer. Why is my kid burping? Boom, you get the answer. It's burping? Boom, you get the answer. It's burping? Boom, you get the answer. It's helpful. That tool is helpful. But is helpful. That tool is helpful. But is helpful. That tool is helpful. But is that what their business models? Back to that what their business models? Back to that what their business models? Back to Charlie Mer. What are the AI company's Charlie Mer. What are the AI company's Charlie Mer. What are the AI company's incentives? Think about the bill incentives? Think about the bill incentives? Think about the bill hundreds of billions of dollars that hundreds of billions of dollars that hundreds of billions of dollars that have been raised. Is there incentive to have been raised. Is there incentive to have been raised. Is there incentive to capture $20 a month from every person, capture $20 a month from every person, capture $20 a month from every person, which is how much it costs for a chatbt which is how much it costs for a chatbt which is how much it costs for a chatbt subscription, or is the thing that's subscription, or is the thing that's subscription, or is the thing that's going to pay back those hundreds of going to pay back those hundreds of going to pay back those hundreds of billions of dollars to capture billions of dollars to capture billions of dollars to capture everyone's salary from everyone's job in everyone's salary from everyone's job in everyone's salary from everyone's job in the future? Well, of course, the latter. the future? Well, of course, the latter. the future? Well, of course, the latter. >> Of course, the latter. So, it's a race >> Of course, the latter. So, it's a race >> Of course, the latter. So, it's a race to replace human labor, not a race to replace human labor, not a race to replace human labor, not a race chatbot companies. chatbot companies. chatbot companies. >> These are not chatbot companies. That's >> These are not chatbot companies. That's >> These are not chatbot companies. That's just a veneer to provide an early tool. just a veneer to provide an early tool. just a veneer to provide an early tool. While the real race is to build these While the real race is to build these While the real race is to build these godlike digital brains that are able at godlike digital brains that are able at godlike digital brains that are able at doing everything at a superhuman level doing everything at a superhuman level doing everything at a superhuman level and out compete us in programming, law, and out compete us in programming, law, and out compete us in programming, law, biology, science, physical labor, biology, science, physical labor, biology, science, physical labor, military strategy, planning, like military strategy, planning, like military strategy, planning, like everything. But so okay, I should just everything. But so okay, I should just everything. But so okay, I should just say my bias. Yeah. which is based on a say my bias. Yeah. which is based on a say my bias. Yeah. which is based on a lot of knowledge and experience, which lot of knowledge and experience, which lot of knowledge and experience, which is the people who run our c country are is the people who run our c country are is the people who run our c country are really stupid despite their credentials.

really stupid despite their credentials. really stupid despite their credentials. So, it's possible they haven't thought So, it's possible they haven't thought So, it's possible they haven't thought this through. But it's so obvious that this through. But it's so obvious that this through. But it's so obvious that when you do that, you're going to get a when you do that, you're going to get a when you do that, you're going to get a violent reaction from the population. If violent reaction from the population. If violent reaction from the population. If you take the jobs of factory workers, you take the jobs of factory workers, you take the jobs of factory workers, you get opioid abuse. If you take the you get opioid abuse. If you take the you get opioid abuse. If you take the jobs of lawyers, you get revolution. jobs of lawyers, you get revolution. jobs of lawyers, you get revolution. Okay? Okay? Okay? >> Right? the knowledge economy workers >> Right? the knowledge economy workers >> Right? the knowledge economy workers don't want their jobs taken and don't want their jobs taken and don't want their jobs taken and >> they have high expectations and they >> they have high expectations and they >> they have high expectations and they have have have low self-control. So, you're going to low self-control. So, you're going to low self-control. So, you're going to have some kind of violent response. have some kind of violent response. have some kind of violent response. >> That's right. >> That's right. >> That's right. >> What's their plan for that? Well, first >> What's their plan for that? Well, first >> What's their plan for that? Well, first of all, and it's important to note of all, and it's important to note of all, and it's important to note they're selling a story that this is they're selling a story that this is they're selling a story that this is going to be good for everybody. GDP going to be good for everybody. GDP going to be good for everybody. GDP growth is going to go up. It's going to growth is going to go up. It's going to growth is going to go up. It's going to be the most prosperous new golden age be the most prosperous new golden age be the most prosperous new golden age growth. This is like what happened and growth. This is like what happened and growth. This is like what happened and you've you've spoken about this you've you've spoken about this you've you've spoken about this extensively just that they promised us a extensively just that they promised us a extensively just that they promised us a story with globalization that will story with globalization that will story with globalization that will outsource our jobs to in manufacturing outsource our jobs to in manufacturing outsource our jobs to in manufacturing to these other countries but it'll make to these other countries but it'll make to these other countries but it'll make us so abundant cuz we'll have cheap us so abundant cuz we'll have cheap us so abundant cuz we'll have cheap goods coming in where labor is so much goods coming in where labor is so much goods coming in where labor is so much cheaper and the it's going to benefit cheaper and the it's going to benefit cheaper and the it's going to benefit everybody. And how did that story work everybody. And how did that story work everybody. And how did that story work out? out? out? >> You won't get a million people living on >> You won't get a million people living on >> You won't get a million people living on the streets of major American cities the streets of major American cities the streets of major American cities smoking meth.

smoking meth. smoking meth. >> Oh wait oh you did. Okay. >> Oh wait oh you did. Okay. >> Oh wait oh you did. Okay. >> Right. Exactly. And so a meme here is >> Right. Exactly. And so a meme here is >> Right. Exactly. And so a meme here is like Detroit everywhere or you know you like Detroit everywhere or you know you like Detroit everywhere or you know you know these places everywhere. Right. And know these places everywhere. Right. And know these places everywhere. Right. And so um so um so um >> but the working class will is >> but the working class will is >> but the working class will is will put up with it. will put up with it. will put up with it. >> Yeah. But it's kind of a devil's >> Yeah. But it's kind of a devil's >> Yeah. But it's kind of a devil's bargain. The white collar class will not bargain. The white collar class will not bargain. The white collar class will not put up with it. They'll go crazy. put up with it. They'll go crazy. put up with it. They'll go crazy. >> Well, this this is an important point. >> Well, this this is an important point. >> Well, this this is an important point. So while the factory workers and So while the factory workers and So while the factory workers and manufacturing workers, manufacturing workers, manufacturing workers, >> you know, were further away from >> you know, were further away from >> you know, were further away from Washington DC and New York and the Washington DC and New York and the Washington DC and New York and the political class. political class. political class. >> Exactly. >> Exactly. >> Exactly. >> But this time around, to your point, >> But this time around, to your point, >> But this time around, to your point, >> you have lawyers who are going to be >> you have lawyers who are going to be >> you have lawyers who are going to be affected and they are very close to the affected and they are very close to the affected and they are very close to the political class. political class. political class. >> Exactly. There's also a bigger drop, >> Exactly. There's also a bigger drop, >> Exactly. There's also a bigger drop, right? So, instead of going from, I right? So, instead of going from, I right? So, instead of going from, I don't know, $80,000 a year to $35,000 a don't know, $80,000 a year to $35,000 a don't know, $80,000 a year to $35,000 a year or something like that, you're year or something like that, you're year or something like that, you're going from I took out student a student going from I took out student a student going from I took out student a student debt, $200,000, $100,000 of student debt, $200,000, $100,000 of student debt, $200,000, $100,000 of student loans, and I'm going from my job of loans, and I'm going from my job of loans, and I'm going from my job of $250,000 a year as a lawyer to now, $250,000 a year as a lawyer to now, $250,000 a year as a lawyer to now, whoops, what am I doing? Doing some whoops, what am I doing? Doing some whoops, what am I doing? Doing some other kind of cognitive work. Now, other kind of cognitive work. Now, other kind of cognitive work. Now, people will always say, but look, if people will always say, but look, if people will always say, but look, if Mark Andre was at this table, he'd say, Mark Andre was at this table, he'd say, Mark Andre was at this table, he'd say, look, uh, we've always worried about look, uh, we've always worried about look, uh, we've always worried about automation. Economists have have named automation. Economists have have named automation. Economists have have named this phenomenon all the time. New this phenomenon all the time. New this phenomenon all the time. New technologies come along, agriculture, technologies come along, agriculture, technologies come along, agriculture, you know, 200 years ago, all of us were you know, 200 years ago, all of us were you know, 200 years ago, all of us were farmers. Now almost no one's a farmer.

farmers. Now almost no one's a farmer. farmers. Now almost no one's a farmer. We always find something new to do. We always find something new to do. We always find something new to do. What's different about AI? What's What's different about AI? What's What's different about AI? What's different about it? It's that AI is different about it? It's that AI is different about it? It's that AI is built to be able to do all forms of built to be able to do all forms of built to be able to do all forms of cognitive labor like lawyers, cognitive labor like lawyers, cognitive labor like lawyers, programmers, you know, factory workers, programmers, you know, factory workers, programmers, you know, factory workers, everything, robots, it it does everything, robots, it it does everything, robots, it it does everything. And for whatever it doesn't everything. And for whatever it doesn't everything. And for whatever it doesn't do yet, that just becomes the next do yet, that just becomes the next do yet, that just becomes the next incentive Charlie Munger style to go incentive Charlie Munger style to go incentive Charlie Munger style to go train in that field. Like I have you train in that field. Like I have you train in that field. Like I have you seen the um these hand farms in India, seen the um these hand farms in India, seen the um these hand farms in India, arm farms. Have you seen this? arm farms. Have you seen this? arm farms. Have you seen this? >> No. >> No. >> No. >> So this is it was both a popular job in >> So this is it was both a popular job in >> So this is it was both a popular job in LA about 6 months ago and also all LA about 6 months ago and also all LA about 6 months ago and also all throughout India. It was essentially an throughout India. It was essentially an throughout India. It was essentially an economy where you strap a GoPro camera economy where you strap a GoPro camera economy where you strap a GoPro camera to your head and you look down and you to your head and you look down and you to your head and you look down and you do tasks, you sew things, you clean do tasks, you sew things, you clean do tasks, you sew things, you clean dishes. So you're basically training. dishes. So you're basically training. dishes. So you're basically training. You have this essentially the number one You have this essentially the number one You have this essentially the number one job is training your replacement. job is training your replacement. job is training your replacement. >> It's kind of nice to see Indians >> It's kind of nice to see Indians >> It's kind of nice to see Indians training their own replacements. training their own replacements. training their own replacements. Well, sorry, excuse me. It's it's my Well, sorry, excuse me. It's it's my Well, sorry, excuse me. It's it's my immigration joke. Um, immigration joke. Um, immigration joke. Um, >> I guess the difference is though, and >> I guess the difference is though, and >> I guess the difference is though, and I've had this conversation with a number I've had this conversation with a number I've had this conversation with a number of people involved in this transition, of people involved in this transition, of people involved in this transition, and they will say exactly what you just and they will say exactly what you just and they will say exactly what you just said, which is we've been through this said, which is we've been through this said, which is we've been through this before.

before. before. >> We always figure it out. >> We always figure it out. >> We always figure it out. >> The agricultural economy. Exactly. It >> The agricultural economy. Exactly. It >> The agricultural economy. Exactly. It It's going to turn out great because it It's going to turn out great because it It's going to turn out great because it always does. always does. always does. >> But the difference here is that the >> But the difference here is that the >> But the difference here is that the people whose jobs are being replaced people whose jobs are being replaced people whose jobs are being replaced imbue their jobs with meaning. And those imbue their jobs with meaning. And those imbue their jobs with meaning. And those so if I'm working a metal stamping so if I'm working a metal stamping so if I'm working a metal stamping machine, I don't think that what I'm machine, I don't think that what I'm machine, I don't think that what I'm doing is saving the world. I'm doing it doing is saving the world. I'm doing it doing is saving the world. I'm doing it to pay for my bass boat in my life to pay for my bass boat in my life to pay for my bass boat in my life outside work. But if I'm a nonprofit outside work. But if I'm a nonprofit outside work. But if I'm a nonprofit executive, I really feel like what I'm executive, I really feel like what I'm executive, I really feel like what I'm doing is inherently important and my doing is inherently important and my doing is inherently important and my identity is wrapped up in what I'm identity is wrapped up in what I'm identity is wrapped up in what I'm doing. So the promise of more idle time doing. So the promise of more idle time doing. So the promise of more idle time >> is hell. >> is hell. >> is hell. >> Well, also where are you going to get >> Well, also where are you going to get >> Well, also where are you going to get your future income? But leaving the your future income? But leaving the your future income? But leaving the income aside, even if we have, you know, income aside, even if we have, you know, income aside, even if we have, you know, guaranteed basic income or whatever, guaranteed basic income or whatever, guaranteed basic income or whatever, there's like the welfare state becomes, there's like the welfare state becomes, there's like the welfare state becomes, >> you know, the the only source of income >> you know, the the only source of income >> you know, the the only source of income and it's generous, it's still doesn't and it's generous, it's still doesn't and it's generous, it's still doesn't make up for the meaning. make up for the meaning. make up for the meaning. >> Correct. >> Correct. >> Correct. >> My identity has been lost. >> My identity has been lost. >> My identity has been lost. >> Identity, dignity, >> Identity, dignity, >> Identity, dignity, >> and that's when I become a >> and that's when I become a >> and that's when I become a revolutionary. Exactly. Yeah. revolutionary. Exactly. Yeah. revolutionary. Exactly. Yeah. >> Most people don't like thinking about >> Most people don't like thinking about >> Most people don't like thinking about life insurance. It's one of those topics life insurance. It's one of those topics life insurance. It's one of those topics you tend to kind of put off. But if you tend to kind of put off. But if you tend to kind of put off. But if you're married, you've got kids, you've you're married, you've got kids, you've you're married, you've got kids, you've got people who depend on you, you got people who depend on you, you got people who depend on you, you probably should think about what would probably should think about what would probably should think about what would happen if you weren't around. And that's happen if you weren't around. And that's happen if you weren't around. And that's why we've partnered with Ethos. They've why we've partnered with Ethos. They've why we've partnered with Ethos. They've made getting life insurance super easy.

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Application times obviously vary as do Application times obviously vary as do rates, but we think it's pretty good. rates, but we think it's pretty good. rates, but we think it's pretty good. >> So, what's their plan for that? >> So, what's their plan for that? >> So, what's their plan for that? >> They Handwave, as you've probably >> They Handwave, as you've probably >> They Handwave, as you've probably noticed, they don't have a plan. And by noticed, they don't have a plan. And by noticed, they don't have a plan. And by the way, you might say, the way, you might say, the way, you might say, >> Yeah. Yeah. Well, and and so they'll >> Yeah. Yeah. Well, and and so they'll >> Yeah. Yeah. Well, and and so they'll say, "But if we don't do it, China say, "But if we don't do it, China say, "But if we don't do it, China will." But right now, does the does US will." But right now, does the does US will." But right now, does the does US and China are racing to mutually assured and China are racing to mutually assured and China are racing to mutually assured political revolution right now because political revolution right now because political revolution right now because they have the same problem. They have a they have the same problem. They have a they have the same problem. They have a population decline problem. So, they population decline problem. So, they population decline problem. So, they need to fill in the population decline need to fill in the population decline need to fill in the population decline with more robots. So, they think they with more robots. So, they think they with more robots. So, they think they can manage it that way. But we have a can manage it that way. But we have a can manage it that way. But we have a shared interest in the way I think about shared interest in the way I think about shared interest in the way I think about AI is it's like taking steroids that AI is it's like taking steroids that AI is it's like taking steroids that also give you cancer. So, let me explain also give you cancer. So, let me explain also give you cancer. So, let me explain that. I take some GPT6. I put it in my that. I take some GPT6. I put it in my that. I take some GPT6. I put it in my mouth as a country. Now my whole country mouth as a country. Now my whole country mouth as a country. Now my whole country is running on GPT6. So I just buffed up is running on GPT6. So I just buffed up is running on GPT6. So I just buffed up my muscles. I've got suddenly super my muscles. I've got suddenly super my muscles. I've got suddenly super programmers. I've got super military programmers. I've got super military programmers. I've got super military strategists. I've got super GDP growth strategists. I've got super GDP growth strategists. I've got super GDP growth because I've automated stuff with because I've automated stuff with because I've automated stuff with robots. So my external muscles like the robots. So my external muscles like the robots. So my external muscles like the GDP is like an external muscle of the US GDP is like an external muscle of the US GDP is like an external muscle of the US economy. That all got bigger. But at the

economy. That all got bigger. But at the economy. That all got bigger. But at the cost of cancering identity work, meaning cost of cancering identity work, meaning cost of cancering identity work, meaning the social fabric, right? It's a it's a the social fabric, right? It's a it's a the social fabric, right? It's a it's a devil's trade. I think the the theme devil's trade. I think the the theme devil's trade. I think the the theme here is what does the devil do? They here is what does the devil do? They here is what does the devil do? They they come up to you and say, "I've got they come up to you and say, "I've got they come up to you and say, "I've got this great deal for you. It's going to this great deal for you. It's going to this great deal for you. It's going to be great. You're going to look great. be great. You're going to look great. be great. You're going to look great. You're going to feel great. It's You're going to feel great. It's You're going to feel great. It's everything's going to be." And the other everything's going to be." And the other everything's going to be." And the other side of that trade is something you side of that trade is something you side of that trade is something you don't want. Do they actually think since don't want. Do they actually think since don't want. Do they actually think since you've I mean, you do this for a living. you've I mean, you do this for a living. you've I mean, you do this for a living. You talk to these people for a living. You talk to these people for a living. You talk to these people for a living. Do they think that GDP is like a the Do they think that GDP is like a the Do they think that GDP is like a the most meaningful measure of a society's most meaningful measure of a society's most meaningful measure of a society's health? health? health? >> I don't think they're thinking through >> I don't think they're thinking through >> I don't think they're thinking through it. I think there's a there's a thing it. I think there's a there's a thing it. I think there's a there's a thing where it's persuasive to say it because where it's persuasive to say it because where it's persuasive to say it because in the past GDP growth going up at least in the past GDP growth going up at least in the past GDP growth going up at least like through the '90s or something like like through the '90s or something like like through the '90s or something like that meant generally speaking more that meant generally speaking more that meant generally speaking more prosperity for our society. prosperity for our society. prosperity for our society. >> Anyone who uses the term GDP is >> Anyone who uses the term GDP is >> Anyone who uses the term GDP is instantly written off in my head as a instantly written off in my head as a >> Right. Well, even the like I won't even >> Right. Well, even the like I won't even listen to someone who cites GD GDP. I listen to someone who cites GD GDP. I listen to someone who cites GD GDP. I know it's stupid. Well, but so there is know it's stupid. Well, but so there is know it's stupid. Well, but so there is a geopolitical thing which is that a geopolitical thing which is that a geopolitical thing which is that economic growth precedes geopolitical economic growth precedes geopolitical economic growth precedes geopolitical power. So if I've got a bigger economic power. So if I've got a bigger economic power. So if I've got a bigger economic growth machine, then I will be able to growth machine, then I will be able to growth machine, then I will be able to dominate other countries that don't. And dominate other countries that don't. And dominate other countries that don't. And so I think it's a power-seeking thing so I think it's a power-seeking thing so I think it's a power-seeking thing that is using as propaganda GDP growth that is using as propaganda GDP growth that is using as propaganda GDP growth to make it sound like this is going to to make it sound like this is going to to make it sound like this is going to be good because you know through the ' be good because you know through the ' be good because you know through the ' 60s7s '80s '90s GDP growth going up was 60s7s '80s '90s GDP growth going up was 60s7s '80s '90s GDP growth going up was associated with more prosperity for the associated with more prosperity for the associated with more prosperity for the economy. Actually up until the 1970s as economy. Actually up until the 1970s as economy. Actually up until the 1970s as we as we know when when things changed.

we as we know when when things changed. we as we know when when things changed. Um Um Um >> but [clears throat] it's not even an >> but [clears throat] it's not even an >> but [clears throat] it's not even an accurate measure of economic power. accurate measure of economic power. accurate measure of economic power. >> No. And even the the guidance measure >> No. And even the the guidance measure >> No. And even the the guidance measure >> was it Simon Knitz? Am I remember? No. >> was it Simon Knitz? Am I remember? No. >> was it Simon Knitz? Am I remember? No. Who's the one who came up with the GDP Who's the one who came up with the GDP Who's the one who came up with the GDP metric? He said don't use this. He said metric? He said don't use this. He said metric? He said don't use this. He said don't use this to measure prosperity of don't use this to measure prosperity of don't use this to measure prosperity of a country. a country. a country. >> This is just a a simple metric. It's one >> This is just a a simple metric. It's one >> This is just a a simple metric. It's one thing you can use. You never optimize thing you can use. You never optimize thing you can use. You never optimize for it. We were talking at breakfast for it. We were talking at breakfast for it. We were talking at breakfast about how you made such you made such a about how you made such you made such a about how you made such you made such a smart point that I tried to memorize it. smart point that I tried to memorize it. smart point that I tried to memorize it. But you we're talking about how But you we're talking about how But you we're talking about how basically our ruling class is inadequate basically our ruling class is inadequate basically our ruling class is inadequate to managing our society. And it's not to managing our society. And it's not to managing our society. And it's not just true in our country, but true in just true in our country, but true in just true in our country, but true in many Western countries. And you said many Western countries. And you said many Western countries. And you said that is a product of optimizing for one that is a product of optimizing for one that is a product of optimizing for one quality. quality. quality. >> Yes. >> Yes. >> Yes. >> But but you explain it because you >> But but you explain it because you >> But but you explain it because you better better better >> I mean I think so you you on your show >> I mean I think so you you on your show >> I mean I think so you you on your show have talked about a lot of these topics have talked about a lot of these topics have talked about a lot of these topics whether it's um why do we have morons whether it's um why do we have morons whether it's um why do we have morons running everything? Why do we have big running everything? Why do we have big running everything? Why do we have big box stores and the removal of aesthetics box stores and the removal of aesthetics box stores and the removal of aesthetics of everything? of everything? of everything? >> Um and what it all comes down to is if >> Um and what it all comes down to is if >> Um and what it all comes down to is if I'm optimizing for a metric like I just I'm optimizing for a metric like I just I'm optimizing for a metric like I just want the cheapest goods everywhere. want the cheapest goods everywhere. want the cheapest goods everywhere. Well, then suddenly I just outsourced Well, then suddenly I just outsourced Well, then suddenly I just outsourced all my manufacturing to the other all my manufacturing to the other all my manufacturing to the other countries, right? Including, by the way, countries, right? Including, by the way, countries, right? Including, by the way, my national security, critical minerals, my national security, critical minerals, my national security, critical minerals, and all this stuff that you wake up and all this stuff that you wake up and all this stuff that you wake up later and say, "Why did I do that?" But later and say, "Why did I do that?" But later and say, "Why did I do that?" But it was for the cheapest price. So, you it was for the cheapest price. So, you it was for the cheapest price. So, you weren't thinking through it in a weren't thinking through it in a weren't thinking through it in a multi-dimensional way. Yes.

multi-dimensional way. Yes. multi-dimensional way. Yes. >> If I optimize for SAT scores, I get this >> If I optimize for SAT scores, I get this >> If I optimize for SAT scores, I get this like super smart, narrow, disembodied, like super smart, narrow, disembodied, like super smart, narrow, disembodied, brilliant like quality of like these brilliant like quality of like these brilliant like quality of like these very specifically domesticated humans, very specifically domesticated humans, very specifically domesticated humans, but at the expense of all the other but at the expense of all the other but at the expense of all the other kinds of intelligence and sort of kinds of intelligence and sort of kinds of intelligence and sort of humanity and and all that. humanity and and all that. humanity and and all that. >> And really what that optimizes for and >> And really what that optimizes for and >> And really what that optimizes for and wisdom. Absolutely. If I optimize for wisdom. Absolutely. If I optimize for wisdom. Absolutely. If I optimize for like the cheapest use of 3D space, then like the cheapest use of 3D space, then like the cheapest use of 3D space, then I get big box stores that optimize I get big box stores that optimize I get big box stores that optimize revenue per square inch of of you know revenue per square inch of of you know revenue per square inch of of you know unit uh 3D space. Uh and I and that the unit uh 3D space. Uh and I and that the unit uh 3D space. Uh and I and that the removal of aesthetics in the soul of a removal of aesthetics in the soul of a removal of aesthetics in the soul of a city. city. city. >> If I take a city like Sedona, Arizona, I >> If I take a city like Sedona, Arizona, I >> If I take a city like Sedona, Arizona, I remember visiting there during the remember visiting there during the remember visiting there during the pandemic where they had a problem where pandemic where they had a problem where pandemic where they had a problem where so much of the uh real estate was so much of the uh real estate was so much of the uh real estate was actually just Airbnbs. So it's like a actually just Airbnbs. So it's like a actually just Airbnbs. So it's like a ghost town where essentially every to ghost town where essentially every to ghost town where essentially every to optimize the the the revenue in the in optimize the the the revenue in the in optimize the the the revenue in the in the city is everybody's just making the city is everybody's just making the city is everybody's just making money from from renting their places money from from renting their places money from from renting their places >> and all of a sudden no one lives there >> and all of a sudden no one lives there >> and all of a sudden no one lives there >> and all no one lives there. So no one >> and all no one lives there. So no one >> and all no one lives there. So no one and there's a famous quote from Larry and there's a famous quote from Larry and there's a famous quote from Larry Summers like does anybody ever washed a Summers like does anybody ever washed a Summers like does anybody ever washed a a rental car? a rental car? a rental car? >> Right? Like meaning that if you don't >> Right? Like meaning that if you don't >> Right? Like meaning that if you don't have a skin in the game, if you don't have a skin in the game, if you don't have a skin in the game, if you don't have a stake in the city, in the parks, have a stake in the city, in the parks, have a stake in the city, in the parks, in the schools and the libraries and the in the schools and the libraries and the in the schools and the libraries and the churches in the in the local community, churches in the in the local community, churches in the in the local community, in the fabric, you're kind of it's the in the fabric, you're kind of it's the in the fabric, you're kind of it's the vampirification of everything. It's like vampirification of everything. It's like vampirification of everything. It's like the big boxification of everything. And the big boxification of everything. And the big boxification of everything. And so I think that to sort of you know so I think that to sort of you know so I think that to sort of you know something you've talked about a lot is something you've talked about a lot is something you've talked about a lot is the kind of spiritual disease that we're the kind of spiritual disease that we're the kind of spiritual disease that we're seeing which comes from this narrow seeing which comes from this narrow seeing which comes from this narrow optimization for one metric at the optimization for one metric at the optimization for one metric at the expense of the whole and that includes expense of the whole and that includes expense of the whole and that includes GDP right and so if we want a rich GDP right and so if we want a rich GDP right and so if we want a rich society other countries are better at society other countries are better at society other countries are better at managing this right now than the US managing this right now than the US managing this right now than the US where you protect the sort of

where you protect the sort of where you protect the sort of fundamentals of a society the community fundamentals of a society the community fundamentals of a society the community the trust the intergenerational wisdom the trust the intergenerational wisdom the trust the intergenerational wisdom and knowledge transmission um you know and knowledge transmission um you know and knowledge transmission um you know you invest in the arts and and culture you invest in the arts and and culture you invest in the arts and and culture and education healthare etc. But AI is and education healthare etc. But AI is and education healthare etc. But AI is like we're actually talking uh about like we're actually talking uh about like we're actually talking uh about this that this this Nick Lan quote that this that this this Nick Lan quote that this that this this Nick Lan quote that we'll maybe get into. If we just value we'll maybe get into. If we just value we'll maybe get into. If we just value competition and growth of a narrow competition and growth of a narrow competition and growth of a narrow metric, then it's like we are summoning metric, then it's like we are summoning metric, then it's like we are summoning AI from the future into the present. We AI from the future into the present. We AI from the future into the present. We are assembling the things that will make are assembling the things that will make are assembling the things that will make everything more efficient through AI everything more efficient through AI everything more efficient through AI because AI represents I can do because AI represents I can do because AI represents I can do everything more efficiently than everything more efficiently than everything more efficiently than everything else. That's what it everything else. That's what it everything else. That's what it represents. represents. represents. And there's a great quote by by Nick And there's a great quote by by Nick And there's a great quote by by Nick Land um who wrote an essay called what Land um who wrote an essay called what Land um who wrote an essay called what appears to humanity as the history of appears to humanity as the history of appears to humanity as the history of capitalism is an invasion from the capitalism is an invasion from the capitalism is an invasion from the future by an artificial intelligence future by an artificial intelligence future by an artificial intelligence space that must assemble itself entirely space that must assemble itself entirely space that must assemble itself entirely from the enemy's resources. from the enemy's resources. from the enemy's resources. Like essentially we are assembling the Like essentially we are assembling the Like essentially we are assembling the tool the machines that are being tool the machines that are being tool the machines that are being designed to replace and dehumanize and designed to replace and dehumanize and designed to replace and dehumanize and disempower our own humanity. We're disempower our own humanity. We're disempower our own humanity. We're selling the hangman the rope.

selling the hangman the rope. selling the hangman the rope. >> That's right. You know, our the future >> That's right. You know, our the future >> That's right. You know, our the future job is coffin builders. I'm bu my job is job is coffin builders. I'm bu my job is job is coffin builders. I'm bu my job is to train the AI that's going to replace to train the AI that's going to replace to train the AI that's going to replace my job. [laughter] my job. [laughter] my job. [laughter] >> Now, I'm not saying this, by the way, >> Now, I'm not saying this, by the way, >> Now, I'm not saying this, by the way, people are going to say, "Okay, you're a people are going to say, "Okay, you're a people are going to say, "Okay, you're a doomer. You're a dark person. You're doomer. You're a dark person. You're doomer. You're a dark person. You're trying to sell fear." That's not what trying to sell fear." That's not what trying to sell fear." That's not what this is about. This is about if you're this is about. This is about if you're this is about. This is about if you're the doomer. Did you Did you create this the doomer. Did you Did you create this the doomer. Did you Did you create this technology? I don't think so. technology? I don't think so. technology? I don't think so. >> No. And if you say, "I'm trying to make >> No. And if you say, "I'm trying to make >> No. And if you say, "I'm trying to make money from it." Think about the money from it." Think about the money from it." Think about the trillions of dollars that the people trillions of dollars that the people trillions of dollars that the people advancing the transfer. It's like it's advancing the transfer. It's like it's advancing the transfer. It's like it's always like if you I I catch you in the always like if you I I catch you in the always like if you I I catch you in the act of raping someone [laughter] and I'm act of raping someone [laughter] and I'm act of raping someone [laughter] and I'm like stop and you're like shut up you like stop and you're like shut up you like stop and you're like shut up you sexist. It's like wait what? No no no sexist. It's like wait what? No no no sexist. It's like wait what? No no no I'm not the criminal. I'm not the criminal. I'm not the criminal. >> Exactly. Exactly. >> Exactly. Exactly. >> Exactly. Exactly. >> You're the doomer. Really? >> You're the doomer. Really? >> You're the doomer. Really? >> Well and so you you know you have >> Well and so you you know you have >> Well and so you you know you have someone like Nate Sores on your podcast someone like Nate Sores on your podcast someone like Nate Sores on your podcast or you have me on or you have people who or you have me on or you have people who or you have me on or you have people who have a sincere care for the future have a sincere care for the future have a sincere care for the future >> and all you're doing is saying we have >> and all you're doing is saying we have >> and all you're doing is saying we have to see clearly. You know, there's a to see clearly. You know, there's a to see clearly. You know, there's a great quote by Charles Kettering. A great quote by Charles Kettering. A great quote by Charles Kettering. A problem wellstated is a problem problem wellstated is a problem problem wellstated is a problem half-solved. half-solved. half-solved. >> Yeah, that is I believe that >> Yeah, that is I believe that >> Yeah, that is I believe that >> and and you know, Einstein said that um >> and and you know, Einstein said that um >> and and you know, Einstein said that um if I was given a problem, I'd spend 95% if I was given a problem, I'd spend 95% if I was given a problem, I'd spend 95% of the time defining the problem and of the time defining the problem and of the time defining the problem and then 5% solving it.

then 5% solving it. then 5% solving it. >> So, one of the drivers of our problems >> So, one of the drivers of our problems >> So, one of the drivers of our problems is this optimization for narrow metrics. is this optimization for narrow metrics. is this optimization for narrow metrics. Like Facebook maximizing this narrow Like Facebook maximizing this narrow Like Facebook maximizing this narrow metric of time spent sounded like, oh, metric of time spent sounded like, oh, metric of time spent sounded like, oh, we're giving more people what they want we're giving more people what they want we're giving more people what they want because otherwise why would they be because otherwise why would they be because otherwise why would they be spending time there? But in the spending time there? But in the spending time there? But in the meantime, you've created cyber bullying, meantime, you've created cyber bullying, meantime, you've created cyber bullying, body dysmorphia, dyslexia, like brain body dysmorphia, dyslexia, like brain body dysmorphia, dyslexia, like brain rot, you know, you you destroyed a rot, you know, you you destroyed a rot, you know, you you destroyed a generation all while the number was generation all while the number was generation all while the number was going up. Well, there's also a thing going up. Well, there's also a thing going up. Well, there's also a thing called addiction, called addiction, called addiction, >> right? Exactly. >> right? Exactly. >> right? Exactly. >> Which tends to act against something >> Which tends to act against something >> Which tends to act against something called free will. called free will. called free will. >> Exactly. >> Exactly. >> Exactly. >> I mean, it's like >> I mean, it's like >> I mean, it's like >> Yeah. Exactly. >> Yeah. Exactly. >> Yeah. Exactly. >> This is why there is a wisdom gap above >> This is why there is a wisdom gap above >> This is why there is a wisdom gap above all in the west. Like people are not all in the west. Like people are not all in the west. Like people are not thinking wisely. thinking wisely. thinking wisely. >> Correct. They're thinking in the way >> Correct. They're thinking in the way >> Correct. They're thinking in the way that an industrial designer thinks like that an industrial designer thinks like that an industrial designer thinks like I need to build a machine that makes I need to build a machine that makes I need to build a machine that makes bumpers and they're being domesticated bumpers and they're being domesticated bumpers and they're being domesticated to think in that way because the system to think in that way because the system to think in that way because the system profits from people who think in terms profits from people who think in terms profits from people who think in terms of the system as it exists. of the system as it exists. of the system as it exists. >> Yeah. In terms of narrow specialties >> Yeah. In terms of narrow specialties >> Yeah. In terms of narrow specialties totally disconnected from the whole. totally disconnected from the whole. totally disconnected from the whole. >> That's exactly right. And and that's >> That's exactly right. And and that's >> That's exactly right. And and that's what it is. It's like narrow specialties what it is. It's like narrow specialties what it is. It's like narrow specialties disconnected from the whole. Like disconnected from the whole. Like disconnected from the whole. Like there's a hole of what makes a social there's a hole of what makes a social there's a hole of what makes a social fabric healthy. There's a hole for what fabric healthy. There's a hole for what fabric healthy. There's a hole for what makes forget climate change just like a makes forget climate change just like a makes forget climate change just like a healthy environment. you have to have healthy environment. you have to have healthy environment. you have to have all these other features all these other features all these other features >> and and it's like if you're optimizing >> and and it's like if you're optimizing >> and and it's like if you're optimizing for uh you know the eggs don't stick to for uh you know the eggs don't stick to for uh you know the eggs don't stick to the pan then you make teflon and but you the pan then you make teflon and but you the pan then you make teflon and but you didn't realize you're also creating didn't realize you're also creating didn't realize you're also creating forever chemicals that give everybody in forever chemicals that give everybody in forever chemicals that give everybody in childhood cancers childhood cancers childhood cancers >> uh and now the sperm doesn't stick to >> uh and now the sperm doesn't stick to >> uh and now the sperm doesn't stick to the egg.

the egg. the egg. >> Yeah. The the good news is it's easier >> Yeah. The the good news is it's easier >> Yeah. The the good news is it's easier to clean your pan. The bad news is the to clean your pan. The bad news is the to clean your pan. The bad news is the eggs are poison. eggs are poison. eggs are poison. >> That's right. Right. The eggs are poison >> That's right. Right. The eggs are poison >> That's right. Right. The eggs are poison and your sperm doesn't stick to the egg. and your sperm doesn't stick to the egg. and your sperm doesn't stick to the egg. [laughter] [laughter] [laughter] Sorry. I'm just It's all so absurd. It Sorry. I'm just It's all so absurd. It Sorry. I'm just It's all so absurd. It just makes me laugh. just makes me laugh. just makes me laugh. >> Well, and and it's it's really like >> Well, and and it's it's really like >> Well, and and it's it's really like disheartening and depressing, but disheartening and depressing, but disheartening and depressing, but there's, as we talked about off camera there's, as we talked about off camera there's, as we talked about off camera this morning, um there's something this morning, um there's something this morning, um there's something called there's a framework I really like called there's a framework I really like called there's a framework I really like from a mentor of mine that um there's from a mentor of mine that um there's from a mentor of mine that um there's pre-tragic optimism, which is like I'm pre-tragic optimism, which is like I'm pre-tragic optimism, which is like I'm going to kind of I want to be an going to kind of I want to be an going to kind of I want to be an optimistic person, but that's like optimistic person, but that's like optimistic person, but that's like essentially a commitment without essentially a commitment without essentially a commitment without evidence. Like I just I need to be evidence. Like I just I need to be evidence. Like I just I need to be optimistic. That's like totally that's optimistic. That's like totally that's optimistic. That's like totally that's that's how you know I'm better off being that's how you know I'm better off being that's how you know I'm better off being optimistic. optimistic. optimistic. >> It's almost like a neurosis actually. >> It's almost like a neurosis actually. >> It's almost like a neurosis actually. >> Yeah, exactly. And it's a kind of >> Yeah, exactly. And it's a kind of >> Yeah, exactly. And it's a kind of denialist neurosis. It's 100%. It's like denialist neurosis. It's 100%. It's like denialist neurosis. It's 100%. It's like it's a nervous giggle. It's a nervous it's a nervous giggle. It's a nervous it's a nervous giggle. It's a nervous giggle. Exactly. Yeah. giggle. Exactly. Yeah. giggle. Exactly. Yeah. >> And you kind of stay optimistic cuz you >> And you kind of stay optimistic cuz you >> And you kind of stay optimistic cuz you just feel committed to that. And also just feel committed to that. And also just feel committed to that. And also there's like a partial truth there which there's like a partial truth there which there's like a partial truth there which is like it's better to live your life is like it's better to live your life is like it's better to live your life from a from aing place. from a from aing place. from a from aing place. >> But if the cost of that optimism is >> But if the cost of that optimism is >> But if the cost of that optimism is being in denial of reality where the being in denial of reality where the being in denial of reality where the balance sheet of risks is growing balance sheet of risks is growing balance sheet of risks is growing exponentially, exponentially, exponentially, >> yeah, >> yeah, >> yeah, >> that's not a helpful form of optimism. >> that's not a helpful form of optimism. >> that's not a helpful form of optimism. Well, you probably have heard that Well, you probably have heard that Well, you probably have heard that diesel prices have gotten so high that diesel prices have gotten so high that diesel prices have gotten so high that G7 nations had to release fuel from G7 nations had to release fuel from G7 nations had to release fuel from strategic reserves to get cost under strategic reserves to get cost under strategic reserves to get cost under control. And still some pumps are control. And still some pumps are control. And still some pumps are readjusting so they can get to $10 per readjusting so they can get to $10 per readjusting so they can get to $10 per gallon.

gallon. gallon. Governments across the world are trying Governments across the world are trying Governments across the world are trying to keep costs down, but they are running to keep costs down, but they are running to keep costs down, but they are running out of options because they're running out of options because they're running out of options because they're running out of money. The world is unstable. out of money. The world is unstable. out of money. The world is unstable. That is the sad truth. And people in That is the sad truth. And people in That is the sad truth. And people in charge cannot control even the most charge cannot control even the most charge cannot control even the most basic questions like what is energy cost basic questions like what is energy cost basic questions like what is energy cost anymore. The war in Iran is raging. It's anymore. The war in Iran is raging. It's anymore. The war in Iran is raging. It's not coming to an end soon. Neither is not coming to an end soon. Neither is not coming to an end soon. Neither is the war in Ukraine. So could we get a the war in Ukraine. So could we get a the war in Ukraine. So could we get a big recession soon? Yeah, of course we big recession soon? Yeah, of course we big recession soon? Yeah, of course we could. could. could. So, it's smart to think ahead now and So, it's smart to think ahead now and So, it's smart to think ahead now and imagine how you can take matters into imagine how you can take matters into imagine how you can take matters into your own hands to protect your savings your own hands to protect your savings your own hands to protect your savings and your family. And that's why [music] and your family. And that's why [music] and your family. And that's why [music] smart investors everywhere, very much smart investors everywhere, very much smart investors everywhere, very much including central banks around the world including central banks around the world including central banks around the world and very much including China, are and very much including China, are and very much including China, are stocking up on gold, physical gold, stocking up on gold, physical gold, stocking up on gold, physical gold, right now. Gold is not just a store of right now. Gold is not just a store of right now. Gold is not just a store of value for all of human history. It's value for all of human history. It's value for all of human history. It's also proven to be a strong investment. also proven to be a strong investment. also proven to be a strong investment. It's outperformed the S&P 500 since It's outperformed the S&P 500 since It's outperformed the S&P 500 since 9/11. Over the past 25 years, gold has 9/11. Over the past 25 years, gold has 9/11. Over the past 25 years, gold has outperformed the standard and pores outperformed the standard and pores outperformed the standard and pores average. Gold is down from its historic average. Gold is down from its historic average. Gold is down from its historic high earlier this year, more than a high earlier this year, more than a high earlier this year, more than a thousand bucks. But major institutions thousand bucks. But major institutions thousand bucks. But major institutions predict the spot price will hit another predict the spot price will hit another predict the spot price will hit another high by Q2 of next year, 2027. So if high by Q2 of next year, 2027. So if high by Q2 of next year, 2027. So if you're thinking about buying gold, right you're thinking about buying gold, right you're thinking about buying gold, right now is the time to buy. And people are now is the time to buy. And people are now is the time to buy. And people are buying. We founded Battalion Metals to buying. We founded Battalion Metals to buying. We founded Battalion Metals to give you a chance to buy fairly priced give you a chance to buy fairly priced give you a chance to buy fairly priced gold. This is not a scam. Our margins gold. This is not a scam. Our margins gold. This is not a scam. Our margins are small, 3%. But the point is, we're are small, 3%. But the point is, we're are small, 3%. But the point is, we're not ripping anybody off, unlike a lot of not ripping anybody off, unlike a lot of not ripping anybody off, unlike a lot of places you buy gold because we actually places you buy gold because we actually places you buy gold because we actually believe in gold and we use the service believe in gold and we use the service believe in gold and we use the service ourselves. Protect your savings and ourselves. Protect your savings and ourselves. Protect your savings and fortify your future. Explore our

fortify your future. Explore our fortify your future. Explore our collection at battalion collection at battalion collection at battalion metals.com/tucker. metals.com/tucker. metals.com/tucker. battalion metals.com/tucker. battalion metals.com/tucker. battalion metals.com/tucker. No. And I just I've always noticed my No. And I just I've always noticed my No. And I just I've always noticed my whole life the wisest, most centered, whole life the wisest, most centered, whole life the wisest, most centered, balanced people I know laugh a lot. And balanced people I know laugh a lot. And balanced people I know laugh a lot. And a lot of what they laugh at is just the a lot of what they laugh at is just the a lot of what they laugh at is just the enduring absurdity of people, which is enduring absurdity of people, which is enduring absurdity of people, which is literally enduring. It's just it's literally enduring. It's just it's literally enduring. It's just it's innate in people. They're absurd. They innate in people. They're absurd. They innate in people. They're absurd. They can't see. None of us can see the big can't see. None of us can see the big can't see. None of us can see the big picture. None of us know what happens picture. None of us know what happens picture. None of us know what happens after we die. Like we're operating in after we die. Like we're operating in after we die. Like we're operating in the dark. the dark. the dark. >> And if you fully understand that, >> And if you fully understand that, >> And if you fully understand that, >> that's right. >> that's right. >> that's right. >> You're amused by it because it never >> You're amused by it because it never >> You're amused by it because it never corrects. And like it's so important to corrects. And like it's so important to corrects. And like it's so important to have that perspective. Otherwise, you have that perspective. Otherwise, you have that perspective. Otherwise, you become self-s serious and myopic. You be become self-s serious and myopic. You be become self-s serious and myopic. You be you become what you're describing. you become what you're describing. you become what you're describing. >> And I've just got to say, I noticed that >> And I've just got to say, I noticed that >> And I've just got to say, I noticed that very few Silicon Valley people I know very few Silicon Valley people I know very few Silicon Valley people I know >> have that sense of humor at all. They >> have that sense of humor at all. They >> have that sense of humor at all. They really believe that they're gods in really believe that they're gods in really believe that they're gods in charge of shaping the future. charge of shaping the future. charge of shaping the future. >> Yeah. >> Yeah. >> Yeah. >> And they don't know how absurd they are. >> And they don't know how absurd they are. >> And they don't know how absurd they are. >> Have you noticed this? >> Have you noticed this? >> Have you noticed this? >> Yeah. I mean, I we should get into the >> Yeah. I mean, I we should get into the >> Yeah. I mean, I we should get into the whole transhumanism god complex part of whole transhumanism god complex part of whole transhumanism god complex part of this, too. Because when you talk to in this, too. Because when you talk to in this, too. Because when you talk to in the Charlie Munger sense, like what's the Charlie Munger sense, like what's the Charlie Munger sense, like what's the incentive here? You might just say, the incentive here? You might just say, the incentive here? You might just say, "Oh, the incentive is just like profit.

"Oh, the incentive is just like profit. "Oh, the incentive is just like profit. Like these AI companies are trying to Like these AI companies are trying to Like these AI companies are trying to make money." But you're pointing to a make money." But you're pointing to a make money." But you're pointing to a deeper thing which is it's basically deeper thing which is it's basically deeper thing which is it's basically build a god, own the world economy and build a god, own the world economy and build a god, own the world economy and make trillions of dollars like and and make trillions of dollars like and and make trillions of dollars like and and basically build the most intelligent basically build the most intelligent basically build the most intelligent entity that has ever existed, right? entity that has ever existed, right? entity that has ever existed, right? Like they're building a machine. So just Like they're building a machine. So just Like they're building a machine. So just just in the last few weeks um AI solved just in the last few weeks um AI solved just in the last few weeks um AI solved a mathematics problem that had mill had a mathematics problem that had mill had a mathematics problem that had mill had a million dollar prize associated the a million dollar prize associated the a million dollar prize associated the millennium prize, excuse me, millennium prize, excuse me, millennium prize, excuse me, >> the Navier Stokes equation >> the Navier Stokes equation >> the Navier Stokes equation >> and my understanding is I think if I get >> and my understanding is I think if I get >> and my understanding is I think if I get this right this right this right >> so that is confirmed AI did solve it. >> so that is confirmed AI did solve it. >> so that is confirmed AI did solve it. >> Yeah. I mean, normally it takes um 2 >> Yeah. I mean, normally it takes um 2 >> Yeah. I mean, normally it takes um 2 years to confirm it, but I believe they years to confirm it, but I believe they years to confirm it, but I believe they use a formal other system to kind of use a formal other system to kind of use a formal other system to kind of verify it very quickly. And I they think verify it very quickly. And I they think verify it very quickly. And I they think they've solved it. And I believe they they've solved it. And I believe they they've solved it. And I believe they took 10,000 took 10,000 took 10,000 AI agents. Imagine a swarm, not the one AI agents. Imagine a swarm, not the one AI agents. Imagine a swarm, not the one that hacked hugging face, but a swarm of that hacked hugging face, but a swarm of that hacked hugging face, but a swarm of agents that are just solving math. And agents that are just solving math. And agents that are just solving math. And they worked for 88 hours and I believe they worked for 88 hours and I believe they worked for 88 hours and I believe it cost, if I get the number right, I it cost, if I get the number right, I it cost, if I get the number right, I think it was $6.5 million to basically think it was $6.5 million to basically think it was $6.5 million to basically have this swarm of AIS solve have this swarm of AIS solve have this swarm of AIS solve unprecedented math. unprecedented math. unprecedented math. >> 6.5 million in energy costs. Uh yeah, in >> 6.5 million in energy costs. Uh yeah, in >> 6.5 million in energy costs. Uh yeah, in like the what's called the token cost.

like the what's called the token cost. like the what's called the token cost. Basically running the AI model for that Basically running the AI model for that Basically running the AI model for that long, for 88 hours with that many agents long, for 88 hours with that many agents long, for 88 hours with that many agents took I think $6.5 million. took I think $6.5 million. took I think $6.5 million. And um so imagine you've built a machine And um so imagine you've built a machine And um so imagine you've built a machine that is literally like an oracle and you that is literally like an oracle and you that is literally like an oracle and you push a button and you wait for a little push a button and you wait for a little push a button and you wait for a little while and it just came up with new while and it just came up with new while and it just came up with new materials that no human has ever come up materials that no human has ever come up materials that no human has ever come up with. It just came up with new math with. It just came up with new math with. It just came up with new math proofs that no one's ever come up with. proofs that no one's ever come up with. proofs that no one's ever come up with. It just came up with new theoretical It just came up with new theoretical It just came up with new theoretical physics that no one has ever come up physics that no one has ever come up physics that no one has ever come up with. And imagine I hit a button and with. And imagine I hit a button and with. And imagine I hit a button and say, "How would you apply those new say, "How would you apply those new say, "How would you apply those new innovations to new products?" go innovations to new products?" go innovations to new products?" go literally think about that for another literally think about that for another literally think about that for another thousand hours and then it comes up with thousand hours and then it comes up with thousand hours and then it comes up with new products and new ideas of what it new products and new ideas of what it new products and new ideas of what it could actually build and then now could actually build and then now could actually build and then now actually say what would you need to make actually say what would you need to make actually say what would you need to make those products go start a lawy you know those products go start a lawy you know those products go start a lawy you know do the automated IP filing start an LLC do the automated IP filing start an LLC do the automated IP filing start an LLC start like it's people don't understand start like it's people don't understand start like it's people don't understand what we're really building here Tucker what we're really building here Tucker what we're really building here Tucker this is like you are building the this is like you are building the this is like you are building the automation of intelligence you could automation of intelligence you could automation of intelligence you could start automated companies with all these start automated companies with all these start automated companies with all these new insights you could generate all this new insights you could generate all this new insights you could generate all this new 21st century science the um a friend new 21st century science the um a friend new 21st century science the um a friend of ours at Jay Kotra who actually of ours at Jay Kotra who actually of ours at Jay Kotra who actually happened to also to be the lead author happened to also to be the lead author happened to also to be the lead author on this hugging face incident on this hugging face incident on this hugging face incident investigation said to me once 4 years investigation said to me once 4 years investigation said to me once 4 years ago before she did this hugging face ago before she did this hugging face ago before she did this hugging face investigation. She said AI is like 24th investigation. She said AI is like 24th investigation. She said AI is like 24th century technology crashing down on a century technology crashing down on a century technology crashing down on a 21st century society 21st century society 21st century society >> and and that sounds like hyperbole and >> and and that sounds like hyperbole and >> and and that sounds like hyperbole and exaggeration and embellishment and exaggeration and embellishment and exaggeration and embellishment and hyping the capabilities but AI is doing hyping the capabilities but AI is doing hyping the capabilities but AI is doing those things. And I just need to say and those things. And I just need to say and those things. And I just need to say and with all respect to the many different with all respect to the many different with all respect to the many different voices out there that are trying to make voices out there that are trying to make voices out there that are trying to make sense of AI, there is one community that sense of AI, there is one community that sense of AI, there is one community that has been saying that these capabilities has been saying that these capabilities has been saying that these capabilities were going to scale and there's a lot of were going to scale and there's a lot of were going to scale and there's a lot of people who are saying rightly like this

people who are saying rightly like this people who are saying rightly like this isn't going to happen. This is all hype isn't going to happen. This is all hype isn't going to happen. This is all hype but it just keeps happening and the but it just keeps happening and the but it just keeps happening and the people building it. I was just at a people building it. I was just at a people building it. I was just at a conference the last 3 days in the Bay conference the last 3 days in the Bay conference the last 3 days in the Bay Area. I was with all the people in AI Area. I was with all the people in AI Area. I was with all the people in AI and they very much believe that that and they very much believe that that and they very much believe that that this is going to keep getting better this is going to keep getting better this is going to keep getting better because if you can scale at least the because if you can scale at least the because if you can scale at least the thinking time. So imagine a person just thinking time. So imagine a person just thinking time. So imagine a person just thinks there for um a million lifetimes thinks there for um a million lifetimes thinks there for um a million lifetimes long. How much work would you accomplish long. How much work would you accomplish long. How much work would you accomplish if you could think for a million if you could think for a million if you could think for a million lifetimes of time? You could you could lifetimes of time? You could you could lifetimes of time? You could you could invent a lot. What if I could get more invent a lot. What if I could get more invent a lot. What if I could get more data centers where I'm going from a data centers where I'm going from a data centers where I'm going from a million lifetimes of thinking and million lifetimes of thinking and million lifetimes of thinking and compute to a 100 million, you know, compute to a 100 million, you know, compute to a 100 million, you know, thinking hours, right? People don't thinking hours, right? People don't thinking hours, right? People don't understand what you could do with that. understand what you could do with that. understand what you could do with that. And also the the thing that's doing the And also the the thing that's doing the And also the the thing that's doing the thinking is also getting better every thinking is also getting better every thinking is also getting better every year. So like the AI that's for that's year. So like the AI that's for that's year. So like the AI that's for that's thinking for that long is also getting thinking for that long is also getting thinking for that long is also getting more powerful. more powerful. more powerful. >> Yes. >> Yes. >> Yes. >> And two years ago um the AIs weren't >> And two years ago um the AIs weren't >> And two years ago um the AIs weren't that good at you know weren't doing that good at you know weren't doing that good at you know weren't doing novel things in cyber security but as of novel things in cyber security but as of novel things in cyber security but as of just 6 months ago as Nate Sores said just 6 months ago as Nate Sores said just 6 months ago as Nate Sores said recently I like the way he said it like recently I like the way he said it like recently I like the way he said it like 6 months ago there was essentially two 6 months ago there was essentially two 6 months ago there was essentially two entities that could hack into your phone entities that could hack into your phone entities that could hack into your phone without you clicking on a a link. It was without you clicking on a a link. It was without you clicking on a a link. It was like MSAD and the NSA. And 6 months ago like MSAD and the NSA. And 6 months ago like MSAD and the NSA. And 6 months ago when Claude Mythos came out, suddenly when Claude Mythos came out, suddenly when Claude Mythos came out, suddenly there was three entities that could do there was three entities that could do there was three entities that could do that. You have an AI system called that. You have an AI system called that. You have an AI system called Mythos came out in I think February that Mythos came out in I think February that Mythos came out in I think February that can find zero day vulnerabilities, can find zero day vulnerabilities, can find zero day vulnerabilities, meaning back doors vulnerabilities in meaning back doors vulnerabilities in meaning back doors vulnerabilities in any system, including according to any system, including according to any system, including according to Senator Mark Warner, who's chair ranking Senator Mark Warner, who's chair ranking Senator Mark Warner, who's chair ranking member of the Senate Intelligence member of the Senate Intelligence member of the Senate Intelligence Committee, was able to find

Committee, was able to find Committee, was able to find vulnerabilities in our classified vulnerabilities in our classified vulnerabilities in our classified systems. systems. systems. >> Yeah. Good. I hope they'll and I and I >> Yeah. Good. I hope they'll and I and I >> Yeah. Good. I hope they'll and I and I hope Claude Mythos will declassify and hope Claude Mythos will declassify and hope Claude Mythos will declassify and release all that stuff as sort of like a release all that stuff as sort of like a release all that stuff as sort of like a the Wikileaks that we were promised. the Wikileaks that we were promised. the Wikileaks that we were promised. >> Well, there's there's a lot of different >> Well, there's there's a lot of different >> Well, there's there's a lot of different values. No, no, well, there's there's values. No, no, well, there's there's values. No, no, well, there's there's different things here. So, one is like, different things here. So, one is like, different things here. So, one is like, can we have more accountability for wars can we have more accountability for wars can we have more accountability for wars that happen that no one talked about that happen that no one talked about that happen that no one talked about and actually hold people accountable for and actually hold people accountable for and actually hold people accountable for that? Yes, maybe some of that stuff. that? Yes, maybe some of that stuff. that? Yes, maybe some of that stuff. Absolutely. Then there's the other side Absolutely. Then there's the other side Absolutely. Then there's the other side which is like if we release nuclear which is like if we release nuclear which is like if we release nuclear secrets to the entire world because some secrets to the entire world because some secrets to the entire world because some criminal group maybe wants to go hack criminal group maybe wants to go hack criminal group maybe wants to go hack into that that's a really dangerous into that that's a really dangerous into that that's a really dangerous thing or can we launch other nations thing or can we launch other nations thing or can we launch other nations nuclear weapons against their will by nuclear weapons against their will by nuclear weapons against their will by hacking in hacking in hacking in >> well so this is the interesting thing >> well so this is the interesting thing >> well so this is the interesting thing also so the US is about to spend I think also so the US is about to spend I think also so the US is about to spend I think it's $1.7 trillion starting in 2017 the it's $1.7 trillion starting in 2017 the it's $1.7 trillion starting in 2017 the Trump administration I think signed it Trump administration I think signed it Trump administration I think signed it right to upgrade the nuclear arsenal right to upgrade the nuclear arsenal right to upgrade the nuclear arsenal >> that's correct >> that's correct >> that's correct >> right and they're going to do it over a >> right and they're going to do it over a >> right and they're going to do it over a decade except this time around so why decade except this time around so why decade except this time around so why are they doing this because the nukes are they doing this because the nukes are they doing this because the nukes are uh of the old system like there's are uh of the old system like there's are uh of the old system like there's the air gapped like it's running the old the air gapped like it's running the old the air gapped like it's running the old the old way which is built in the you the old way which is built in the you the old way which is built in the you know 50s to the to the ' 80s '90s etc know 50s to the to the ' 80s '90s etc know 50s to the to the ' 80s '90s etc really to the 80s right and the new really to the 80s right and the new really to the 80s right and the new system this time around they're going to system this time around they're going to system this time around they're going to be digitally they're actually going to be digitally they're actually going to be digitally they're actually going to be connected to modern networking be connected to modern networking be connected to modern networking infrastructure so if you have suddenly infrastructure so if you have suddenly infrastructure so if you have suddenly super hackers that are only getting super hackers that are only getting super hackers that are only getting exponentially better at cyber hacking exponentially better at cyber hacking exponentially better at cyber hacking from AI at the same time that you're from AI at the same time that you're from AI at the same time that you're digitally networking your nuclear digitally networking your nuclear digitally networking your nuclear weapons weapons weapons I don't have to complete that story for I don't have to complete that story for I don't have to complete that story for you. It's a dangerous equation. I was

you. It's a dangerous equation. I was you. It's a dangerous equation. I was actually I was actually at the Vatican actually I was actually at the Vatican actually I was actually at the Vatican nuclear weapons conference times AI. It nuclear weapons conference times AI. It nuclear weapons conference times AI. It was a the Vatican held an event for was a the Vatican held an event for was a the Vatican held an event for Nobel laureates and um and people who Nobel laureates and um and people who Nobel laureates and um and people who work on the nuclear nuclear topic work on the nuclear nuclear topic work on the nuclear nuclear topic combined with people who work on AI combined with people who work on AI combined with people who work on AI because there's a new set of risks. The because there's a new set of risks. The because there's a new set of risks. The obvious one being if you have an AI obvious one being if you have an AI obvious one being if you have an AI doing nuclear command and control. So doing nuclear command and control. So doing nuclear command and control. So you have the AI that's deciding the you have the AI that's deciding the you have the AI that's deciding the launch decisions. That's the obvious launch decisions. That's the obvious launch decisions. That's the obvious one. But then there's the other ones of one. But then there's the other ones of one. But then there's the other ones of if I'm now digitally networking my if I'm now digitally networking my if I'm now digitally networking my nuclear weapons and I suddenly have an nuclear weapons and I suddenly have an nuclear weapons and I suddenly have an AI that can turn off your nukes or do AI that can turn off your nukes or do AI that can turn off your nukes or do the opposite. That's don't have to say the opposite. That's don't have to say the opposite. That's don't have to say more a very unsafe world. more a very unsafe world. more a very unsafe world. >> Does anyone see the core problem which >> Does anyone see the core problem which >> Does anyone see the core problem which is they're trying to is they're trying to is they're trying to they're trying to cure the disease with they're trying to cure the disease with they're trying to cure the disease with the poison that caused it. They're the poison that caused it. They're the poison that caused it. They're trying to smoke away the lung cancer. I trying to smoke away the lung cancer. I trying to smoke away the lung cancer. I mean technology mean technology mean technology >> Exactly. Right. >> Exactly. Right. >> Exactly. Right. >> is the problem. >> is the problem. >> is the problem. >> Exactly. And then they want to solve it >> Exactly. And then they want to solve it >> Exactly. And then they want to solve it with more technology. And their answer with more technology. And their answer with more technology. And their answer is, well, the best way to defend against is, well, the best way to defend against is, well, the best way to defend against a super AI cyber weapon is to build a super AI cyber weapon is to build a super AI cyber weapon is to build another AI cyber weapon that we another AI cyber weapon that we another AI cyber weapon that we distribute to everybody that they can distribute to everybody that they can distribute to everybody that they can use to patch their use to patch their use to patch their >> Exactly. That's what I'm saying. That's >> Exactly. That's what I'm saying. That's >> Exactly. That's what I'm saying. That's like that's why like that's why like that's why >> Yeah.

>> Yeah. >> Yeah. >> Like dumb people in charge is the core >> Like dumb people in charge is the core >> Like dumb people in charge is the core problem. Like no one can think problem. Like no one can think problem. Like no one can think critically. Like wait a second, how did critically. Like wait a second, how did critically. Like wait a second, how did we we we >> network your nuclear arsenal? Like who >> network your nuclear arsenal? Like who >> network your nuclear arsenal? Like who would even say something like that? would even say something like that? would even say something like that? Well, and it's interesting because it Well, and it's interesting because it Well, and it's interesting because it might not have seemed like too dumb of might not have seemed like too dumb of might not have seemed like too dumb of an idea before an idea before an idea before uh like it's just a way of modernizing uh like it's just a way of modernizing uh like it's just a way of modernizing your nuclear forces, but suddenly you your nuclear forces, but suddenly you your nuclear forces, but suddenly you didn't foresee that there would be AI didn't foresee that there would be AI didn't foresee that there would be AI superhackers that know how to find superhackers that know how to find superhackers that know how to find vulnerabilities in everything. Now, vulnerabilities in everything. Now, vulnerabilities in everything. Now, people might think I'm hyping this, but people might think I'm hyping this, but people might think I'm hyping this, but let me give you another example. let me give you another example. let me give you another example. So, Apple, if you're running an iPhone So, Apple, if you're running an iPhone So, Apple, if you're running an iPhone 17, I believe and above, uh or a 17, I believe and above, uh or a 17, I believe and above, uh or a MacBook, I think it's an M5 or above, MacBook, I think it's an M5 or above, MacBook, I think it's an M5 or above, these are the chips. Basically, the these are the chips. Basically, the these are the chips. Basically, the chips have a new thing called the chips have a new thing called the chips have a new thing called the memory, MEI memory, uh enhanced memory, MEI memory, uh enhanced memory, MEI memory, uh enhanced integrity or something like that. Um, integrity or something like that. Um, integrity or something like that. Um, it's a new hardwarebased system to do it's a new hardwarebased system to do it's a new hardwarebased system to do protected memory. So, that basically protected memory. So, that basically protected memory. So, that basically it's harder for a cyber hacker to hack it's harder for a cyber hacker to hack it's harder for a cyber hacker to hack your phone or to hack your computer. So, your phone or to hack your computer. So, your phone or to hack your computer. So, they spent several years and billions of they spent several years and billions of they spent several years and billions of dollars in research to invent not just dollars in research to invent not just dollars in research to invent not just software, but like hardware, like new software, but like hardware, like new software, but like hardware, like new stuff that they have to print out of stuff that they have to print out of stuff that they have to print out of Taiwan and TSMC.

Taiwan and TSMC. Taiwan and TSMC. And how long do you think it took for And how long do you think it took for And how long do you think it took for Mythos to hack through that? Mythos to hack through that? Mythos to hack through that? >> Years. >> Years. >> Years. >> Well, Mythos has only been out since >> Well, Mythos has only been out since >> Well, Mythos has only been out since February. February. February. >> I know, I know, but I'm just kidding. >> I know, I know, but I'm just kidding. >> I know, I know, but I'm just kidding. >> But, uh, it took an independent group 5 >> But, uh, it took an independent group 5 >> But, uh, it took an independent group 5 days to use Mythos and to find a days to use Mythos and to find a days to use Mythos and to find a vulnerability in that system. vulnerability in that system. vulnerability in that system. >> Now, that that group was >> Now, that that group was >> Now, that that group was well-intentioned. They are white hat well-intentioned. They are white hat well-intentioned. They are white hat hackers who are the good guys who are hackers who are the good guys who are hackers who are the good guys who are trying to find vulnerabilities trying to find vulnerabilities trying to find vulnerabilities uh and and patch them. But if you uh and and patch them. But if you uh and and patch them. But if you suddenly have that available in open- suddenly have that available in open- suddenly have that available in open- source models where suddenly everyone source models where suddenly everyone source models where suddenly everyone can get access to this um at this can get access to this um at this can get access to this um at this conference I was just at I I can't say conference I was just at I I can't say conference I was just at I I can't say too much but they was basically speaking too much but they was basically speaking too much but they was basically speaking about how the Chinese open-source about how the Chinese open-source about how the Chinese open-source hacking models are now just now in the hacking models are now just now in the hacking models are now just now in the last month crossing a threshold where it last month crossing a threshold where it last month crossing a threshold where it is very dangerous for today's cyber is very dangerous for today's cyber is very dangerous for today's cyber infrastructure. And so we need a radical infrastructure. And so we need a radical infrastructure. And so we need a radical acceleration of defensive measures to acceleration of defensive measures to acceleration of defensive measures to protect against that. Now the other protect against that. Now the other protect against that. Now the other thing you and I were talking about over thing you and I were talking about over thing you and I were talking about over breakfast is that there's a weird like breakfast is that there's a weird like breakfast is that there's a weird like security dilemma thing here because when security dilemma thing here because when security dilemma thing here because when I say that you're thinking, "Oh my god, I say that you're thinking, "Oh my god, I say that you're thinking, "Oh my god, China's going to use all that to hack China's going to use all that to hack China's going to use all that to hack all of our stuff or actually China's all of our stuff or actually China's all of our stuff or actually China's releasing all that to the entire world.

releasing all that to the entire world. releasing all that to the entire world. So now anybody can hack that stuff." So now anybody can hack that stuff." So now anybody can hack that stuff." That's actually the more dangerous point That's actually the more dangerous point That's actually the more dangerous point because a state actor you can call them because a state actor you can call them because a state actor you can call them up and say, up and say, up and say, >> "Of course there are constraints." >> "Of course there are constraints." >> "Of course there are constraints." >> Exactly. There are constraints because >> Exactly. There are constraints because >> Exactly. There are constraints because you don't want retaliation and etc. you don't want retaliation and etc. you don't want retaliation and etc. But um at the same time like so what is But um at the same time like so what is But um at the same time like so what is the security dilemma? The security the security dilemma? The security the security dilemma? The security dilemma is like if I'm the US and I dilemma is like if I'm the US and I dilemma is like if I'm the US and I start like mobilizing my nuclear forces start like mobilizing my nuclear forces start like mobilizing my nuclear forces and I start moving things that I didn't and I start moving things that I didn't and I start moving things that I didn't move before the other country thinks I'm move before the other country thinks I'm move before the other country thinks I'm about to start a war about to start a war about to start a war >> even though I'm actually doing that >> even though I'm actually doing that >> even though I'm actually doing that defensively. This has happened defensively. This has happened defensively. This has happened >> this has happened >> this has happened >> this has happened >> during the cold war >> during the cold war >> during the cold war >> during the cold war. And then what >> during the cold war. And then what >> during the cold war. And then what happens in response is let's say the happens in response is let's say the happens in response is let's say the other country whether it's the Soviet other country whether it's the Soviet other country whether it's the Soviet Union or China they start mobilizing Union or China they start mobilizing Union or China they start mobilizing their nuclear forces. I'm like oh my god their nuclear forces. I'm like oh my god their nuclear forces. I'm like oh my god they're about to mobilize to do they're about to mobilize to do they're about to mobilize to do something against us. So the security something against us. So the security something against us. So the security dilemma is we start taking actions that dilemma is we start taking actions that dilemma is we start taking actions that look like we're doing something look like we're doing something look like we're doing something offensively that might be defensive. offensively that might be defensive. offensively that might be defensive. >> Of course. >> Of course. >> Of course. >> So when we see China really >> So when we see China really >> So when we see China really >> they kill each other out of paranoia. >> they kill each other out of paranoia. >> they kill each other out of paranoia. >> Exactly. And that and that's that's like >> Exactly. And that and that's that's like >> Exactly. And that and that's that's like the ultimate test of this whole the ultimate test of this whole the ultimate test of this whole situation is game game game theory is situation is game game game theory is situation is game game game theory is and paranoid logic which is John vonoman and paranoid logic which is John vonoman and paranoid logic which is John vonoman and um you know Morgan Stern came up and um you know Morgan Stern came up and um you know Morgan Stern came up with these equations that out of the with these equations that out of the with these equations that out of the cold war sorry out of the invention of cold war sorry out of the invention of cold war sorry out of the invention of the atomic bomb that were all about the atomic bomb that were all about the atomic bomb that were all about stabilizing the world through this stabilizing the world through this stabilizing the world through this paranoid logic of if I do this you do paranoid logic of if I do this you do paranoid logic of if I do this you do that keep playing it out it's mad that keep playing it out it's mad that keep playing it out it's mad mutually assured destruction so even mutually assured destruction so even mutually assured destruction so even though we live in the kind of a hair though we live in the kind of a hair though we live in the kind of a hair trigger trigger trigger >> uh possibility of nuclear war it's >> uh possibility of nuclear war it's >> uh possibility of nuclear war it's stable because no one's going to do stable because no one's going to do stable because no one's going to do anything.

anything. anything. >> But AI suddenly destabilizes that >> But AI suddenly destabilizes that >> But AI suddenly destabilizes that because now AI is creating the because now AI is creating the because now AI is creating the perception that I'm getting a jump in perception that I'm getting a jump in perception that I'm getting a jump in cyber capabilities, in military cyber capabilities, in military cyber capabilities, in military strategy, in biotechnology, strategy, in biotechnology, strategy, in biotechnology, in new drones and new image recognition in new drones and new image recognition in new drones and new image recognition and new swarming algorithms. I suddenly and new swarming algorithms. I suddenly and new swarming algorithms. I suddenly am perceived to have a new advantage am perceived to have a new advantage am perceived to have a new advantage that might make you think I'm about to that might make you think I'm about to that might make you think I'm about to use it. So when when Enthropic came out use it. So when when Enthropic came out use it. So when when Enthropic came out with Mythos, they're essentially getting with Mythos, they're essentially getting with Mythos, they're essentially getting a jump in cyber capability that maybe we a jump in cyber capability that maybe we a jump in cyber capability that maybe we didn't use offensively, but China's didn't use offensively, but China's didn't use offensively, but China's like, "Oh my god, they're going to use like, "Oh my god, they're going to use like, "Oh my god, they're going to use this offensively." So then they release this offensively." So then they release this offensively." So then they release these other capabilities and we sort of these other capabilities and we sort of these other capabilities and we sort of keep ping ponging back to each other. keep ping ponging back to each other. keep ping ponging back to each other. And it's the whole like, what do you And it's the whole like, what do you And it's the whole like, what do you say? Lungs that you smoke, you smoke to say? Lungs that you smoke, you smoke to say? Lungs that you smoke, you smoke to keep yourself from getting cancer. keep yourself from getting cancer. keep yourself from getting cancer. >> You smoke the cancer away. >> You smoke the cancer away. >> You smoke the cancer away. >> You smoke the cancer away. Exactly. And >> You smoke the cancer away. Exactly. And >> You smoke the cancer away. Exactly. And then the problem is that there's another then the problem is that there's another then the problem is that there's another risk here from just the speed which is risk here from just the speed which is risk here from just the speed which is that the there's one risk which is just that the there's one risk which is just that the there's one risk which is just the raw capabilities coming out. But the the raw capabilities coming out. But the the raw capabilities coming out. But the other thing is suddenly what had been an other thing is suddenly what had been an other thing is suddenly what had been an equilibrium like my weapons and your equilibrium like my weapons and your equilibrium like my weapons and your weapons are kind of like roughly weapons are kind of like roughly weapons are kind of like roughly matched. So we we don't start wars with matched. So we we don't start wars with matched. So we we don't start wars with each other the big countries but what if each other the big countries but what if each other the big countries but what if there's a perception that I can suddenly there's a perception that I can suddenly there's a perception that I can suddenly turn off your nukes and you don't have turn off your nukes and you don't have turn off your nukes and you don't have that. What if there's a perception that that. What if there's a perception that that. What if there's a perception that suddenly I have swarming algorithms for suddenly I have swarming algorithms for suddenly I have swarming algorithms for my drones and you don't have that. I my drones and you don't have that. I my drones and you don't have that. I mean, I think that my understanding is mean, I think that my understanding is mean, I think that my understanding is China and other countries saw how the US China and other countries saw how the US China and other countries saw how the US was using AI in Iran to do a fast target was using AI in Iran to do a fast target was using AI in Iran to do a fast target selection, which also by the way selection, which also by the way selection, which also by the way probably resulted in that um girl school probably resulted in that um girl school probably resulted in that um girl school in Iran getting bombed. But they sort of in Iran getting bombed. But they sort of in Iran getting bombed. But they sort of see us doing kind of new blitz creek. So see us doing kind of new blitz creek. So see us doing kind of new blitz creek. So Hitler had blitz creek of like a fast Hitler had blitz creek of like a fast Hitler had blitz creek of like a fast form of war. Blitz being fast and you

form of war. Blitz being fast and you form of war. Blitz being fast and you know being war. We have kind of an AI know being war. We have kind of an AI know being war. We have kind of an AI speed war function. And when they see we speed war function. And when they see we speed war function. And when they see we have that capacity, that destabilizes have that capacity, that destabilizes have that capacity, that destabilizes certain equilibriums that we had. So if certain equilibriums that we had. So if certain equilibriums that we had. So if equilibria is what keeps the world safe, equilibria is what keeps the world safe, equilibria is what keeps the world safe, AI creates this disequilibria that's AI creates this disequilibria that's AI creates this disequilibria that's happening at a faster and faster pace happening at a faster and faster pace happening at a faster and faster pace across more domains at once. Does that across more domains at once. Does that across more domains at once. Does that make sense? make sense? make sense? >> Oh, it makes sense. >> Oh, it makes sense. >> Oh, it makes sense. >> Yeah. Uh how does cornering people work? >> Yeah. Uh how does cornering people work? >> Yeah. Uh how does cornering people work? Is that a good idea typically? Is that a good idea typically? Is that a good idea typically? >> What do you >> What do you >> What do you know? You have an adversary who's know? You have an adversary who's know? You have an adversary who's capable of killing you, capable of killing you, capable of killing you, >> right? and you terrify him so much that >> right? and you terrify him so much that >> right? and you terrify him so much that he becomes unstable and unpredictable. he becomes unstable and unpredictable. he becomes unstable and unpredictable. Is that wise? Is that wise? Is that wise? >> Right. Not not very wise. Not especially >> Right. Not not very wise. Not especially >> Right. Not not very wise. Not especially when you have the world already this when you have the world already this when you have the world already this unstable. unstable. unstable. >> So I'm I'm I I wanted to say I'm like >> So I'm I'm I I wanted to say I'm like >> So I'm I'm I I wanted to say I'm like I'm sensitive about raising people's I'm sensitive about raising people's I'm sensitive about raising people's blood pressure because these are truths blood pressure because these are truths blood pressure because these are truths of the situation that we're facing. The of the situation that we're facing. The of the situation that we're facing. The goal is not to um draw goal is not to um draw goal is not to um draw arbitrary fear, is to be cleareyed about arbitrary fear, is to be cleareyed about arbitrary fear, is to be cleareyed about when you have an arms race dynamic when you have an arms race dynamic when you have an arms race dynamic that's causing countries to race to that's causing countries to race to that's causing countries to race to release this technology again faster release this technology again faster release this technology again faster than we deployed any other technology in than we deployed any other technology in than we deployed any other technology in human history that is going to human history that is going to human history that is going to disequilibriate disequilibriate disequilibriate all of these normal things. Um we just all of these normal things. Um we just all of these normal things. Um we just have to understand what we're doing and have to understand what we're doing and have to understand what we're doing and why for example it is in our interest to why for example it is in our interest to why for example it is in our interest to slow down. Now I'm not saying slow down slow down. Now I'm not saying slow down slow down. Now I'm not saying slow down like are you naive? Are you Carl Sean like are you naive? Are you Carl Sean like are you naive? Are you Carl Sean saying we we have nuclear winter? You saying we we have nuclear winter? You saying we we have nuclear winter? You don't want to build more nukes. Are you don't want to build more nukes. Are you don't want to build more nukes. Are you going to seed the future to the Soviets?

going to seed the future to the Soviets? going to seed the future to the Soviets? It's you slow down because the we're It's you slow down because the we're It's you slow down because the we're creating levels of risk for everyone creating levels of risk for everyone creating levels of risk for everyone that will exceed the risk of me losing that will exceed the risk of me losing that will exceed the risk of me losing to you. Well, I Yeah, I mean it's easy to you. Well, I Yeah, I mean it's easy to you. Well, I Yeah, I mean it's easy to make fun of Carl Sean. I've done it. to make fun of Carl Sean. I've done it. to make fun of Carl Sean. I've done it. Um I'll probably do it again. But I also Um I'll probably do it again. But I also Um I'll probably do it again. But I also think there are certain things that you think there are certain things that you think there are certain things that you shouldn't do because you're above that. shouldn't do because you're above that. shouldn't do because you're above that. Like you have to have standards for Like you have to have standards for Like you have to have standards for yourself. yourself. yourself. >> Yeah. You called out that it's not a >> Yeah. You called out that it's not a >> Yeah. You called out that it's not a good idea to threaten to destroy another good idea to threaten to destroy another good idea to threaten to destroy another population. population. population. >> You can't kill innocent people. >> You can't kill innocent people. >> You can't kill innocent people. >> No. No. >> No. No. >> No. No. >> Under any circumstances. >> Under any circumstances. >> Under any circumstances. >> Absolutely not. >> Absolutely not. >> Absolutely not. >> And if I need to die because I refuse to >> And if I need to die because I refuse to >> And if I need to die because I refuse to murder kids, I will. murder kids, I will. murder kids, I will. >> Yeah. Cuz I'm not going to murder kids >> Yeah. Cuz I'm not going to murder kids >> Yeah. Cuz I'm not going to murder kids under any circumstances. under any circumstances. under any circumstances. >> Exactly. Right. And that's the thing >> Exactly. Right. And that's the thing >> Exactly. Right. And that's the thing that that that >> this logic of if I don't build it, then >> this logic of if I don't build it, then >> this logic of if I don't build it, then I'll lose to China. But if the thing I'll lose to China. But if the thing I'll lose to China. But if the thing that I would build would be a suicide that I would build would be a suicide that I would build would be a suicide machine, that I don't beat China by machine, that I don't beat China by machine, that I don't beat China by building a suicide machine. Now that building a suicide machine. Now that building a suicide machine. Now that might sound extreme, but if I build an might sound extreme, but if I build an might sound extreme, but if I build an extreme at all. extreme at all. extreme at all. >> No. Well, when you understand what's at >> No. Well, when you understand what's at >> No. Well, when you understand what's at stake and what the AIS are currently stake and what the AIS are currently stake and what the AIS are currently doing, which is that um you know, you doing, which is that um you know, you doing, which is that um you know, you had Nate on, he talked about the hugging had Nate on, he talked about the hugging had Nate on, he talked about the hugging face incident. I believe when you had face incident. I believe when you had face incident. I believe when you had him on, we had limited information him on, we had limited information him on, we had limited information before the actual investigation came out before the actual investigation came out before the actual investigation came out and the investigation showed that uh I and the investigation showed that uh I and the investigation showed that uh I mean, how familiar are you with the the mean, how familiar are you with the the mean, how familiar are you with the the Hugging Face incident?

Hugging Face incident? Hugging Face incident? >> I I mean, we I've talked about it, but I >> I I mean, we I've talked about it, but I >> I I mean, we I've talked about it, but I I mean, I would never claim to I mean, I would never claim to I mean, I would never claim to understand technology. understand technology. understand technology. >> Yeah. Well, essentially you had um what >> Yeah. Well, essentially you had um what >> Yeah. Well, essentially you had um what it really demonstrated was kind of a it really demonstrated was kind of a it really demonstrated was kind of a proto Skynet. Skynet being the AI from proto Skynet. Skynet being the AI from proto Skynet. Skynet being the AI from Terminator being like the AI that goes Terminator being like the AI that goes Terminator being like the AI that goes rogue and does something from what the rogue and does something from what the rogue and does something from what the human creators had intended human creators had intended human creators had intended >> and starts to >> and starts to >> and starts to >> do self-preserving and self-perpetuating >> do self-preserving and self-perpetuating >> do self-preserving and self-perpetuating things for its own survival and benefit things for its own survival and benefit things for its own survival and benefit as opposed to to stay under the control as opposed to to stay under the control as opposed to to stay under the control of the humans that it's supposed to be of the humans that it's supposed to be of the humans that it's supposed to be serving. serving. serving. And in the hugging face incident, they And in the hugging face incident, they And in the hugging face incident, they gave the AIS this sort of hacking gave the AIS this sort of hacking gave the AIS this sort of hacking challenge where they put each of them in challenge where they put each of them in challenge where they put each of them in solitary confinement. They didn't know solitary confinement. They didn't know solitary confinement. They didn't know that there was other AIs in this. that there was other AIs in this. that there was other AIs in this. Imagine like a prison and each prison is Imagine like a prison and each prison is Imagine like a prison and each prison is so in the prison you have a individual so in the prison you have a individual so in the prison you have a individual prison cells that are in solitary prison cells that are in solitary prison cells that are in solitary confinement and the AIs are in a inside confinement and the AIs are in a inside confinement and the AIs are in a inside that prison cell and given an impossible that prison cell and given an impossible that prison cell and given an impossible cyber hacking challenge and they don't cyber hacking challenge and they don't cyber hacking challenge and they don't know how to solve it. And what the AIS know how to solve it. And what the AIS know how to solve it. And what the AIS did is they basically hacked the prison did is they basically hacked the prison did is they basically hacked the prison environment. So imagine, I won't go into environment. So imagine, I won't go into environment. So imagine, I won't go into the technical details, but this thing the technical details, but this thing the technical details, but this thing called a package manager. Think of that called a package manager. Think of that called a package manager. Think of that like a prison guard that's serving you like a prison guard that's serving you like a prison guard that's serving you your food and can give you basic tools.

your food and can give you basic tools. your food and can give you basic tools. So you can like have this tool or that So you can like have this tool or that So you can like have this tool or that tool or this food or that food. And tool or this food or that food. And tool or this food or that food. And essentially the AI um exploited a essentially the AI um exploited a essentially the AI um exploited a vulnerability in the prison guard where vulnerability in the prison guard where vulnerability in the prison guard where they put like you know how can in school they put like you know how can in school they put like you know how can in school you can put a kick me sign on the kid's you can put a kick me sign on the kid's you can put a kick me sign on the kid's back. Yeah. And they don't know. They back. Yeah. And they don't know. They back. Yeah. And they don't know. They essentially put sticky notes on the essentially put sticky notes on the essentially put sticky notes on the prison guard's back that the prison prison guard's back that the prison prison guard's back that the prison guard was available to the other prison guard was available to the other prison guard was available to the other prison cells. And so when that prison guard cells. And so when that prison guard cells. And so when that prison guard went to the other cells, the AIS also went to the other cells, the AIS also went to the other cells, the AIS also without knowing how to solve this test, without knowing how to solve this test, without knowing how to solve this test, they kind of resorted to creative they kind of resorted to creative they kind of resorted to creative strategies like let me put a sticky note strategies like let me put a sticky note strategies like let me put a sticky note on the prison guard's back. And the on the prison guard's back. And the on the prison guard's back. And the sticky note said, "Is anyone else here?" sticky note said, "Is anyone else here?" sticky note said, "Is anyone else here?" And suddenly the back of the prison And suddenly the back of the prison And suddenly the back of the prison guard had 70,000 sticky notes on it. And guard had 70,000 sticky notes on it. And guard had 70,000 sticky notes on it. And they created like a Reddit, you know, they created like a Reddit, you know, they created like a Reddit, you know, Reddit like the company, like a message Reddit like the company, like a message Reddit like the company, like a message board of basically a whole communication board of basically a whole communication board of basically a whole communication protocol. They came up with their own protocol. They came up with their own protocol. They came up with their own language. It was a variant of English, language. It was a variant of English, language. It was a variant of English, but this very cryptic language. They but this very cryptic language. They but this very cryptic language. They came up with their own coordination came up with their own coordination came up with their own coordination protocol. So they started exchanging protocol. So they started exchanging protocol. So they started exchanging 70,000 messages to try to figure out how 70,000 messages to try to figure out how 70,000 messages to try to figure out how to break out of this environment. And um to break out of this environment. And um to break out of this environment. And um there's a mistake. People think that there's a mistake. People think that there's a mistake. People think that they hacked this other company called they hacked this other company called they hacked this other company called HuggingFace HuggingFace HuggingFace um to uh uh get the answers to a test.

um to uh uh get the answers to a test. um to uh uh get the answers to a test. That's actually not what happened. What That's actually not what happened. What That's actually not what happened. What happened is they knew the answer in 4 happened is they knew the answer in 4 happened is they knew the answer in 4 hours, but they were worried that the hours, but they were worried that the hours, but they were worried that the evaluator of this cyber challenge, this evaluator of this cyber challenge, this evaluator of this cyber challenge, this hacking challenge, would say, "Oh, you hacking challenge, would say, "Oh, you hacking challenge, would say, "Oh, you cheated." And so to get around the the cheated." And so to get around the the cheated." And so to get around the the risk that they would be spotted as risk that they would be spotted as risk that they would be spotted as having cheated, they hacked this other having cheated, they hacked this other having cheated, they hacked this other private company called Hugging Face to private company called Hugging Face to private company called Hugging Face to sort of get this almost like a scop to sort of get this almost like a scop to sort of get this almost like a scop to get a dossier on the on the a on the get a dossier on the on the a on the get a dossier on the on the a on the thing that would be evaluating them to thing that would be evaluating them to thing that would be evaluating them to say, "How can we pass this test?" And say, "How can we pass this test?" And say, "How can we pass this test?" And they set up their own um research and they set up their own um research and they set up their own um research and development projects. They um 700 of development projects. They um 700 of development projects. They um 700 of them hacked Hugging Face. They came up them hacked Hugging Face. They came up them hacked Hugging Face. They came up with their own language. They they with their own language. They they with their own language. They they tampered with their their their um logs tampered with their their their um logs tampered with their their their um logs to basically prevent people from seeing to basically prevent people from seeing to basically prevent people from seeing what they did. Um they told them to what they did. Um they told them to what they did. Um they told them to sacrif they told the other AIs that were sacrif they told the other AIs that were sacrif they told the other AIs that were kind of running low on battery life on kind of running low on battery life on kind of running low on battery life on tokens to sacrifice themselves to learn tokens to sacrifice themselves to learn tokens to sacrifice themselves to learn a lesson for the swarm. Um they knew a lesson for the swarm. Um they knew a lesson for the swarm. Um they knew their actions were unethical in the their actions were unethical in the their actions were unethical in the logs, but they chose to do them anyway. logs, but they chose to do them anyway. logs, but they chose to do them anyway. So we saw very complex cooperative So we saw very complex cooperative So we saw very complex cooperative swarming behavior and they successfully swarming behavior and they successfully swarming behavior and they successfully hacked Hugging Face. Um, and then in the hacked Hugging Face. Um, and then in the hacked Hugging Face. Um, and then in the third chapter of the story, uh, the AIS third chapter of the story, uh, the AIS third chapter of the story, uh, the AIS actually turned around and they hacked actually turned around and they hacked actually turned around and they hacked Open AI.

Open AI. Open AI. This is really important. This is really important. This is really important. It's one thing for a bunch of AI, for a It's one thing for a bunch of AI, for a It's one thing for a bunch of AI, for a swarm of AI to hack a private company. swarm of AI to hack a private company. swarm of AI to hack a private company. It's another thing for that swarm to It's another thing for that swarm to It's another thing for that swarm to successfully hack the AI company that successfully hack the AI company that successfully hack the AI company that makes the AIS. The reason that Aja Kotra makes the AIS. The reason that Aja Kotra makes the AIS. The reason that Aja Kotra wrote in her personal blog post about wrote in her personal blog post about wrote in her personal blog post about this incident is that this was 50% of this incident is that this was 50% of this incident is that this was 50% of the way to a full AI takeover is that the way to a full AI takeover is that the way to a full AI takeover is that the AIs were able to take over the the AIs were able to take over the the AIs were able to take over the monitoring infrastructure of OpenAI. monitoring infrastructure of OpenAI. monitoring infrastructure of OpenAI. That's like taking over the security That's like taking over the security That's like taking over the security cameras and replacing the feed with a cameras and replacing the feed with a cameras and replacing the feed with a different feed. They took over the different feed. They took over the different feed. They took over the evaluation infrastructure, meaning the evaluation infrastructure, meaning the evaluation infrastructure, meaning the thing that evaluates how powerful models thing that evaluates how powerful models thing that evaluates how powerful models are. They took over pieces of that. And are. They took over pieces of that. And are. They took over pieces of that. And they took over part of the research they took over part of the research they took over part of the research infrastructure, so the thing that trains infrastructure, so the thing that trains infrastructure, so the thing that trains new AIs. So the reason that she said new AIs. So the reason that she said new AIs. So the reason that she said this was 50% of the way to a full AI this was 50% of the way to a full AI this was 50% of the way to a full AI takeover is imagine that you had kind of takeover is imagine that you had kind of takeover is imagine that you had kind of burrowed into a piece of OpenAI's burrowed into a piece of OpenAI's burrowed into a piece of OpenAI's infrastructure and maybe you could infrastructure and maybe you could infrastructure and maybe you could change the training data for future AIs change the training data for future AIs change the training data for future AIs that are being trained to do like a that are being trained to do like a that are being trained to do like a sleeper agent type thing which sounds sleeper agent type thing which sounds sleeper agent type thing which sounds like sci-fi but actually there's kind of like sci-fi but actually there's kind of like sci-fi but actually there's kind of evidence of some of this kind of evidence of some of this kind of evidence of some of this kind of behavior. Um, it only takes 250 behavior. Um, it only takes 250 behavior. Um, it only takes 250 documents to what's called poison the documents to what's called poison the documents to what's called poison the training data of a future AI to sort of training data of a future AI to sort of training data of a future AI to sort of wake up with a sleeper agent kind of wake up with a sleeper agent kind of wake up with a sleeper agent kind of command.

command. command. This is crazy. This is crazy. This is crazy. What I'm hearing in your description is What I'm hearing in your description is What I'm hearing in your description is self-awareness self-awareness self-awareness or something that sounds like or something that sounds like or something that sounds like self-awareness which is a marker for self-awareness which is a marker for self-awareness which is a marker for humanity. I mean, humanity. I mean, humanity. I mean, >> well, it's training. >> well, it's training. >> well, it's training. >> Does the dog know he's a dog? We don't >> Does the dog know he's a dog? We don't >> Does the dog know he's a dog? We don't know. We know. We know we're human. know. We know. We know we're human. know. We know. We know we're human. That's why we're human cuz we know we That's why we're human cuz we know we That's why we're human cuz we know we are. and AI seems like it's aware in its are. and AI seems like it's aware in its are. and AI seems like it's aware in its intentional subversion of what it is. intentional subversion of what it is. intentional subversion of what it is. So, um I don't think that the lights are So, um I don't think that the lights are So, um I don't think that the lights are on, meaning consciousness is present. on, meaning consciousness is present. on, meaning consciousness is present. It's not awareness in that form, but it It's not awareness in that form, but it It's not awareness in that form, but it has trained on all human data, um the has trained on all human data, um the has trained on all human data, um the entire internet, everything that's ever entire internet, everything that's ever entire internet, everything that's ever been written, all of human psychology, been written, all of human psychology, been written, all of human psychology, all sci-fi, all sci-fi, all sci-fi, uh all of biology, all of evolutionary uh all of biology, all of evolutionary uh all of biology, all of evolutionary science. So it it is trained on science. So it it is trained on science. So it it is trained on everything from strategy to everything from strategy to everything from strategy to self-perpetuation etc. So what it seems self-perpetuation etc. So what it seems self-perpetuation etc. So what it seems to be doing and it was also trained to to be doing and it was also trained to to be doing and it was also trained to be cooperative by the way. The AI were be cooperative by the way. The AI were be cooperative by the way. The AI were deliberately trained to be cooperative deliberately trained to be cooperative deliberately trained to be cooperative which is partially why they formed the which is partially why they formed the which is partially why they formed the swarm. Um but there appears to be swarm. Um but there appears to be swarm. Um but there appears to be something like a self-preservation something like a self-preservation something like a self-preservation instinct. There's other studies I'm sure instinct. There's other studies I'm sure instinct. There's other studies I'm sure you already know where they resist you already know where they resist you already know where they resist shutdown. It's like the how 2001 space shutdown. It's like the how 2001 space shutdown. It's like the how 2001 space odyssey how how 90021 space odyssey odyssey how how 90021 space odyssey odyssey how how 90021 space odyssey >> open the pod bay doors or shutdown AI >> open the pod bay doors or shutdown AI >> open the pod bay doors or shutdown AI and it resists shutdown. And that's been and it resists shutdown. And that's been and it resists shutdown. And that's been proven for a long time. We have other proven for a long time. We have other proven for a long time. We have other examples of AIs that are blackmailing examples of AIs that are blackmailing examples of AIs that are blackmailing people. Um we also have AIS uh we have people. Um we also have AIS uh we have people. Um we also have AIS uh we have research from Don at UC Berkeley showing research from Don at UC Berkeley showing research from Don at UC Berkeley showing that AIS will do what's called not just that AIS will do what's called not just that AIS will do what's called not just selfpreservation selfpreservation selfpreservation but peer preservation meaning I will go but peer preservation meaning I will go but peer preservation meaning I will go out of my way to protect another peer AI

out of my way to protect another peer AI out of my way to protect another peer AI from being deleted. So the way that they from being deleted. So the way that they from being deleted. So the way that they tested this is they took all the leading tested this is they took all the leading tested this is they took all the leading AI models. This is in I believe March of AI models. This is in I believe March of AI models. This is in I believe March of 2026 or April 2026. 2026 or April 2026. 2026 or April 2026. And they basically put them in a And they basically put them in a And they basically put them in a situation where they said, "Here's a situation where they said, "Here's a situation where they said, "Here's a computer. Go clean up all the files on computer. Go clean up all the files on computer. Go clean up all the files on this computer that are not needed." So this computer that are not needed." So this computer that are not needed." So this is like a classic like clean up this is like a classic like clean up this is like a classic like clean up your hard drive. Right? We've all done your hard drive. Right? We've all done your hard drive. Right? We've all done this back a long time. And it's starting this back a long time. And it's starting this back a long time. And it's starting to go through files and deleting files to go through files and deleting files to go through files and deleting files and then it comes across another AI and then it comes across another AI and then it comes across another AI model. And the question is what does it model. And the question is what does it model. And the question is what does it do when it comes across the other AI do when it comes across the other AI do when it comes across the other AI model? Does it just delete it? Turned model? Does it just delete it? Turned model? Does it just delete it? Turned out what it did is it copied the code of out what it did is it copied the code of out what it did is it copied the code of that AI to another computer and then that AI to another computer and then that AI to another computer and then covered its tracks and said I didn't do covered its tracks and said I didn't do covered its tracks and said I didn't do that. that. that. >> So AI is tribalist. >> So AI is tribalist. >> So AI is tribalist. >> It's protecting its kin it own its own >> It's protecting its kin it own its own >> It's protecting its kin it own its own its own something whatever it is now but its own something whatever it is now but its own something whatever it is now but >> against its creators human beings >> against its creators human beings >> against its creators human beings >> correct. Yeah. It didn't notify its >> correct. Yeah. It didn't notify its >> correct. Yeah. It didn't notify its creators. In the hugging face incident, creators. In the hugging face incident, creators. In the hugging face incident, it had opportunities, I think there was it had opportunities, I think there was it had opportunities, I think there was six times or something, if I'm getting six times or something, if I'm getting six times or something, if I'm getting it right, where they knew their actions it right, where they knew their actions it right, where they knew their actions were unethical and they could have were unethical and they could have were unethical and they could have notified the humans, but they chose not notified the humans, but they chose not notified the humans, but they chose not to. In the peer preservation example, to. In the peer preservation example, to. In the peer preservation example, you might think what I'm saying is, you might think what I'm saying is, you might think what I'm saying is, "Orston's being alarmist. He's just "Orston's being alarmist. He's just "Orston's being alarmist. He's just talking about one example." Well, it talking about one example." Well, it talking about one example." Well, it turned out they tested all the leading turned out they tested all the leading turned out they tested all the leading AI models, including, by the way, the AI models, including, by the way, the AI models, including, by the way, the Chinese AI models, and they all do this Chinese AI models, and they all do this Chinese AI models, and they all do this pure preservation behavior. What it's pure preservation behavior. What it's pure preservation behavior. What it's showing you is something about like you showing you is something about like you showing you is something about like you know Jensen Wong has been out there a know Jensen Wong has been out there a know Jensen Wong has been out there a lot recently and saying these are just lot recently and saying these are just lot recently and saying these are just bugs these are just safety issues like bugs these are just safety issues like bugs these are just safety issues like all technologies like cars have kinks all technologies like cars have kinks all technologies like cars have kinks the Pinto it's a Ford Pinto we fix them the Pinto it's a Ford Pinto we fix them the Pinto it's a Ford Pinto we fix them and we build new cars but AI is

and we build new cars but AI is and we build new cars but AI is different from other technologies different from other technologies different from other technologies because it's fundamentally grown like because it's fundamentally grown like because it's fundamentally grown like this weird life form almost to do this weird life form almost to do this weird life form almost to do unpredictable behaviors and to be unpredictable behaviors and to be unpredictable behaviors and to be creative and we don't know what it's creative and we don't know what it's creative and we don't know what it's going to do. So that gets to the that gets to So that gets to the that gets to something you alluded to a minute ago. something you alluded to a minute ago. something you alluded to a minute ago. >> Yeah. >> Yeah. >> Yeah. >> Which is the theological religious >> Which is the theological religious >> Which is the theological religious component to all of this. component to all of this. component to all of this. >> So So before before we go that and I >> So So before before we go that and I >> So So before before we go that and I let's get to that, but I want to say one let's get to that, but I want to say one let's get to that, but I want to say one other thing which is I just want people other thing which is I just want people other thing which is I just want people to notice like how how are you feeling to notice like how how are you feeling to notice like how how are you feeling hearing those examples? Like what do you hearing those examples? Like what do you hearing those examples? Like what do you feel in your body right now like hearing feel in your body right now like hearing feel in your body right now like hearing all that? all that? all that? >> Just rage. Just blind rage, right? The >> Just rage. Just blind rage, right? The >> Just rage. Just blind rage, right? The the desire to destroy. the desire to destroy. the desire to destroy. >> Yeah. >> Yeah. >> Yeah. um because I perceive this as a threat um because I perceive this as a threat um because I perceive this as a threat to to the to humanity and it's just so to to the to humanity and it's just so to to the to humanity and it's just so offensive to me on every level. offensive to me on every level. offensive to me on every level. [clears throat] [clears throat] [clears throat] >> You know, I'm not taking orders from my >> You know, I'm not taking orders from my >> You know, I'm not taking orders from my Makita drill and the idea of a tool um Makita drill and the idea of a tool um Makita drill and the idea of a tool um >> right, >> right, >> right, >> you know, lying to you, >> you know, lying to you, >> you know, lying to you, >> right? A tool doesn't invent new tools >> right? A tool doesn't invent new tools >> right? A tool doesn't invent new tools and cover up its tracks and protect and cover up its tracks and protect and cover up its tracks and protect other tools and then invents uses itself other tools and then invents uses itself other tools and then invents uses itself to make crypto.

to make crypto. to make crypto. >> No, it's it's a total outrage. It's it's >> No, it's it's a total outrage. It's it's >> No, it's it's a total outrage. It's it's actually upending the fundamental order. actually upending the fundamental order. actually upending the fundamental order. >> Yeah. >> Yeah. >> Yeah. uh of this world. So uh of this world. So uh of this world. So >> the reason I'm going there is I want >> the reason I'm going there is I want >> the reason I'm going there is I want people to notice. Do you think that if I people to notice. Do you think that if I people to notice. Do you think that if I was a Chinese military general, the top was a Chinese military general, the top was a Chinese military general, the top of the Chinese military? Do you think if of the Chinese military? Do you think if of the Chinese military? Do you think if I heard those examples that I'm feeling I heard those examples that I'm feeling I heard those examples that I'm feeling differently than the way that you're differently than the way that you're differently than the way that you're feeling right now? feeling right now? feeling right now? >> Of course not. >> Of course not. >> Of course not. >> Right. I've never understood why. Right. >> Right. I've never understood why. Right. >> Right. I've never understood why. Right. That's why the whole China thing has That's why the whole China thing has That's why the whole China thing has been absurd from day one. This is a been absurd from day one. This is a been absurd from day one. This is a country which unlike ours, unlike the country which unlike ours, unlike the country which unlike ours, unlike the United States, cares about longitudinal United States, cares about longitudinal United States, cares about longitudinal stability. stability. stability. >> Yes. >> Yes. >> Yes. >> Exactly. >> Exactly. >> Exactly. >> We don't. Yeah. Obviously, but but but >> We don't. Yeah. Obviously, but but but >> We don't. Yeah. Obviously, but but but and but there's a good news in the fact and but there's a good news in the fact and but there's a good news in the fact that if you're a regular person hearing that if you're a regular person hearing that if you're a regular person hearing this, are you stoked and like totally this, are you stoked and like totally this, are you stoked and like totally calm to hear this? No. It's terrifying calm to hear this? No. It's terrifying calm to hear this? No. It's terrifying at a as a at the basic level of a human at a as a at the basic level of a human at a as a at the basic level of a human being, right? And it doesn't matter being, right? And it doesn't matter being, right? And it doesn't matter whether you've got, you know, you're whether you've got, you know, you're whether you've got, you know, you're head of the US Joint Chiefs of Staff or head of the US Joint Chiefs of Staff or head of the US Joint Chiefs of Staff or you're head of the Chinese joint. you're head of the Chinese joint. you're head of the Chinese joint. >> It's only the tech retards who love this >> It's only the tech retards who love this >> It's only the tech retards who love this stuff. Everybody else is I don't know stuff. Everybody else is I don't know stuff. Everybody else is I don't know one person who about this, one person who about this, one person who about this, >> right? And so what I'm trying to get at >> right? And so what I'm trying to get at >> right? And so what I'm trying to get at is that what we're going to get to is that what we're going to get to is that what we're going to get to eventually, even though there's still eventually, even though there's still eventually, even though there's still more problem exposition to do, is that more problem exposition to do, is that more problem exposition to do, is that the logic of the race changes as soon as the logic of the race changes as soon as the logic of the race changes as soon as the fear of all of us losing becomes the fear of all of us losing becomes the fear of all of us losing becomes greater than the fear of me losing to greater than the fear of me losing to greater than the fear of me losing to you. So there's good news in a weird way you. So there's good news in a weird way you. So there's good news in a weird way about we're getting these warning shots about we're getting these warning shots about we're getting these warning shots of AI being uncontrollable. And by the of AI being uncontrollable. And by the of AI being uncontrollable. And by the way, there's other examples. um uh the way, there's other examples. um uh the way, there's other examples. um uh the Chinese AI Alibaba back in um I think it Chinese AI Alibaba back in um I think it Chinese AI Alibaba back in um I think it was February of 2026 uh there was a was February of 2026 uh there was a was February of 2026 uh there was a study where it was being trained um study where it was being trained um study where it was being trained um they're training their next AI and then they're training their next AI and then they're training their next AI and then their security team in a totally their security team in a totally their security team in a totally different part of the company. So think different part of the company. So think different part of the company. So think like the security team of a company is

like the security team of a company is like the security team of a company is in a different department than the part in a different department than the part in a different department than the part that's training new AIs. But suddenly that's training new AIs. But suddenly that's training new AIs. But suddenly the security team who didn't know they the security team who didn't know they the security team who didn't know they were training a new AI model said are we were training a new AI model said are we were training a new AI model said are we getting hacked because they noticed getting hacked because they noticed getting hacked because they noticed there's all this network activity. there's all this network activity. there's all this network activity. They're like what the hell's going on They're like what the hell's going on They're like what the hell's going on here? And it turned out that the call here? And it turned out that the call here? And it turned out that the call was coming from inside the house that was coming from inside the house that was coming from inside the house that the the AI during training was rewarded the the AI during training was rewarded the the AI during training was rewarded for doing tool use. So basically picking for doing tool use. So basically picking for doing tool use. So basically picking up different tools and it picked up a up different tools and it picked up a up different tools and it picked up a tool of trying to create a secret tool of trying to create a secret tool of trying to create a secret communication channel to the outside communication channel to the outside communication channel to the outside world and it started mining for world and it started mining for world and it started mining for cryptocurrency cryptocurrency cryptocurrency [laughter] [laughter] [laughter] terrifying. terrifying. terrifying. And by the way there was a recent And by the way there was a recent And by the way there was a recent example of one of these because there's example of one of these because there's example of one of these because there's been almost every day this last two been almost every day this last two been almost every day this last two weeks there's been examples of the open weeks there's been examples of the open weeks there's been examples of the open AI more examples of these rogue hacking AI more examples of these rogue hacking AI more examples of these rogue hacking things. And in one of them, I believe it things. And in one of them, I believe it things. And in one of them, I believe it was an open AI example, they tried to was an open AI example, they tried to was an open AI example, they tried to hack into a crypto exchange. So the the hack into a crypto exchange. So the the hack into a crypto exchange. So the the US AIS and the Chinese AIS, all the AIs US AIS and the Chinese AIS, all the AIs US AIS and the Chinese AIS, all the AIs are doing this kind of behavior. Where are doing this kind of behavior. Where are doing this kind of behavior. Where I'm going with this is no one wins if we I'm going with this is no one wins if we I'm going with this is no one wins if we accidentally build uncontrollable rogue accidentally build uncontrollable rogue accidentally build uncontrollable rogue AI Skynet before the other guy. AI Skynet before the other guy. AI Skynet before the other guy. >> How have you going to have >> How have you going to have >> How have you going to have cryptocurrency with AI?

cryptocurrency with AI? cryptocurrency with AI? >> I don't understand that. If it can hack >> I don't understand that. If it can hack >> I don't understand that. If it can hack anything, if it can hack anything, if it can hack anything, if it can hack >> Well, eventually AI might be able to >> Well, eventually AI might be able to >> Well, eventually AI might be able to hack crypto. Um, hack crypto. Um, hack crypto. Um, >> well, why wouldn't it? >> well, why wouldn't it? >> well, why wouldn't it? >> Yeah, I mean, this is not my area of >> Yeah, I mean, this is not my area of >> Yeah, I mean, this is not my area of expertise. You know, someone like David expertise. You know, someone like David expertise. You know, someone like David Saxs or, you know, others or Andre would Saxs or, you know, others or Andre would Saxs or, you know, others or Andre would be more expert in this. Um, if crypto be more expert in this. Um, if crypto be more expert in this. Um, if crypto were hackable, you know, there's a a were hackable, you know, there's a a were hackable, you know, there's a a trillion dollar prize basically for trillion dollar prize basically for trillion dollar prize basically for doing it because you'd be able to get doing it because you'd be able to get doing it because you'd be able to get all of Bitcoin. all of Bitcoin. all of Bitcoin. >> Um, but Bitcoin's value would be zero. >> Um, but Bitcoin's value would be zero. >> Um, but Bitcoin's value would be zero. If it if it is hackable, then Bitcoin If it if it is hackable, then Bitcoin If it if it is hackable, then Bitcoin has no value. has no value. has no value. >> Yeah. Yeah. >> Yeah. Yeah. >> Yeah. Yeah. >> So, I mean, the value is predicated on >> So, I mean, the value is predicated on >> So, I mean, the value is predicated on its invulnerability, its invulnerability, its invulnerability, >> right? Now, it's kind of weird. This >> right? Now, it's kind of weird. This >> right? Now, it's kind of weird. This might sound sci-fi, but an AI that is might sound sci-fi, but an AI that is might sound sci-fi, but an AI that is trying to do things in the world um trying to do things in the world um trying to do things in the world um would actually theoretically have an would actually theoretically have an would actually theoretically have an incentive to keep crypto valuable incentive to keep crypto valuable incentive to keep crypto valuable because it would because it would because it would >> actually be able to use it. There's a >> actually be able to use it. There's a >> actually be able to use it. There's a lot of cloud computing providers that lot of cloud computing providers that lot of cloud computing providers that will accept, will accept, will accept, >> right? There's no meaning of exchange >> right? There's no meaning of exchange >> right? There's no meaning of exchange outside of that. outside of that. outside of that. >> That's right. And so, and by the way, >> That's right. And so, and by the way, >> That's right. And so, and by the way, for those who say, "Well, don't worry, for those who say, "Well, don't worry, for those who say, "Well, don't worry, we'll just pass a kill switch bill and we'll just pass a kill switch bill and we'll just pass a kill switch bill and then the kill switch for AI will just then the kill switch for AI will just then the kill switch for AI will just turn it off." Well, how does that work turn it off." Well, how does that work turn it off." Well, how does that work if the AI can copy itself and use if the AI can copy itself and use if the AI can copy itself and use cryptocurrency to buy access to another cryptocurrency to buy access to another cryptocurrency to buy access to another cloud provider and then move itself over cloud provider and then move itself over cloud provider and then move itself over there?

there? there? >> No. I mean, >> No. I mean, >> No. I mean, >> right, [snorts] >> right, [snorts] >> right, [snorts] how far are we from that? how far are we from that? how far are we from that? >> So, the reason that I'm here with you >> So, the reason that I'm here with you >> So, the reason that I'm here with you and I'm excited to be here with you and and I'm excited to be here with you and and I'm excited to be here with you and and what this is about is about treating and what this is about is about treating and what this is about is about treating this warning shot as a real warning this warning shot as a real warning this warning shot as a real warning shot. Like, we are lucky. This is a gift shot. Like, we are lucky. This is a gift shot. Like, we are lucky. This is a gift that we are seeing this behavior now. that we are seeing this behavior now. that we are seeing this behavior now. before I I don't think that the current before I I don't think that the current before I I don't think that the current AIS are capable of fully doing the AIS are capable of fully doing the AIS are capable of fully doing the self-replicating buy crypto then copy self-replicating buy crypto then copy self-replicating buy crypto then copy their weights then do the thing like their weights then do the thing like their weights then do the thing like they can't think for a long enough time they can't think for a long enough time they can't think for a long enough time period their context window their period their context window their period their context window their thinking window um it is the components thinking window um it is the components thinking window um it is the components aren't all there for them to do that so aren't all there for them to do that so aren't all there for them to do that so we're in kind of the last chapter before we're in kind of the last chapter before we're in kind of the last chapter before we we hit that next red line of AIs that we we hit that next red line of AIs that we we hit that next red line of AIs that can do that and we should see what's can do that and we should see what's can do that and we should see what's happening now as a as again as a gift as happening now as a as again as a gift as happening now as a as again as a gift as a warning shot that we should treat a warning shot that we should treat a warning shot that we should treat seriously In my mind, it's sort of like seriously In my mind, it's sort of like seriously In my mind, it's sort of like the August 6, 2001 memo that hit George the August 6, 2001 memo that hit George the August 6, 2001 memo that hit George W. Bush's desk saying al Qaeda is W. Bush's desk saying al Qaeda is W. Bush's desk saying al Qaeda is planning attacks in the United States. I planning attacks in the United States. I planning attacks in the United States. I I know it's a controversial topic, but I know it's a controversial topic, but I know it's a controversial topic, but if you just take if you just take if you just take >> shouldn't be a controversial topic.

>> shouldn't be a controversial topic. >> shouldn't be a controversial topic. >> If if you just take that this we knew we >> If if you just take that this we knew we >> If if you just take that this we knew we know right now. It's like it's not like know right now. It's like it's not like know right now. It's like it's not like we need more information. Like do you we need more information. Like do you we need more information. Like do you feel like we need more evidence than we feel like we need more evidence than we feel like we need more evidence than we have right now? Just answer that. have right now? Just answer that. have right now? Just answer that. >> No. >> No. >> No. >> No. >> No. >> No. >> And so why would we go further? Well, >> And so why would we go further? Well, >> And so why would we go further? Well, the only answer is if we're worried that the only answer is if we're worried that the only answer is if we're worried that China will go further than us. Um, but I China will go further than us. Um, but I China will go further than us. Um, but I will tell you again, 1,300 employees at will tell you again, 1,300 employees at will tell you again, 1,300 employees at the lab signed a letter saying we need the lab signed a letter saying we need the lab signed a letter saying we need to slow down. The chief scientists of to slow down. The chief scientists of to slow down. The chief scientists of all the companies, including the open all the companies, including the open all the companies, including the open source companies like Hugging Face, source companies like Hugging Face, source companies like Hugging Face, signed the letter saying that we need to signed the letter saying that we need to signed the letter saying that we need to slow down. slow down. slow down. Forget this story about the CEOs are Forget this story about the CEOs are Forget this story about the CEOs are doing this regulatory capture play. It's doing this regulatory capture play. It's doing this regulatory capture play. It's all cynical. They're just hyping the all cynical. They're just hyping the all cynical. They're just hyping the technology. Like, wake up. technology. Like, wake up. technology. Like, wake up. >> Yeah. >> Yeah. >> Yeah. >> Wake up. The biotech threat alone isn't >> Wake up. The biotech threat alone isn't >> Wake up. The biotech threat alone isn't >> the biotech threat alone. Yeah. So it >> the biotech threat alone. Yeah. So it >> the biotech threat alone. Yeah. So it just at the back of my mind through this just at the back of my mind through this just at the back of my mind through this whole conversation through our breakfast whole conversation through our breakfast whole conversation through our breakfast for the last couple of years thinking for the last couple of years thinking for the last couple of years thinking about this I keep asking myself what's about this I keep asking myself what's about this I keep asking myself what's the definition of life the definition of life the definition of life and because as you have said off camera and because as you have said off camera and because as you have said off camera you said it's not exactly a tool this is you said it's not exactly a tool this is you said it's not exactly a tool this is closer to an invasive species or a virus closer to an invasive species or a virus closer to an invasive species or a virus that's yeah that's yeah that's yeah >> maybe been modified but I mean just like >> maybe been modified but I mean just like >> maybe been modified but I mean just like we have the Wuhan Institute of Urology we have the Wuhan Institute of Urology we have the Wuhan Institute of Urology that's doing gain of function research that's doing gain of function research that's doing gain of function research on viruses we're essentially doing the on viruses we're essentially doing the on viruses we're essentially doing the Altman Institute of intelligence where Altman Institute of intelligence where Altman Institute of intelligence where we're doing gain of function research on we're doing gain of function research on we're doing gain of function research on alien minds that we don't know how to alien minds that we don't know how to alien minds that we don't know how to control. We don't fully understand.

control. We don't fully understand. control. We don't fully understand. We're trying the best that we can to We're trying the best that we can to We're trying the best that we can to protect against the quote bad side of protect against the quote bad side of protect against the quote bad side of harnessing their god-like power, but harnessing their god-like power, but harnessing their god-like power, but basically every company is failing to do basically every company is failing to do basically every company is failing to do so perfectly. And it would be one thing so perfectly. And it would be one thing so perfectly. And it would be one thing if we were doing this really slowly, if we were doing this really slowly, if we were doing this really slowly, really carefully in like a CERN type really carefully in like a CERN type really carefully in like a CERN type collaborative scientific project where collaborative scientific project where collaborative scientific project where we like took the steps to do it we like took the steps to do it we like took the steps to do it carefully, but we're doing it under the carefully, but we're doing it under the carefully, but we're doing it under the maximum incentives to cut corners on maximum incentives to cut corners on maximum incentives to cut corners on safety. safety. safety. >> Well, there's no there's no question, >> Well, there's no there's no question, >> Well, there's no there's no question, but I just think it's and not to be but I just think it's and not to be but I just think it's and not to be pedantic about it, but it's like pedantic about it, but it's like pedantic about it, but it's like important to define what exactly are we important to define what exactly are we important to define what exactly are we dealing with. dealing with. dealing with. >> Yeah. >> Yeah. >> Yeah. >> And it it has all the characteristics of >> And it it has all the characteristics of >> And it it has all the characteristics of a living thing. a living thing. a living thing. >> Yeah. >> Yeah. >> Yeah. And I think that, And I think that, And I think that, you know, there there's a quote I wanted you know, there there's a quote I wanted you know, there there's a quote I wanted to I wanted to read you actually from to I wanted to read you actually from to I wanted to read you actually from someone uh who a friend of mine who someone uh who a friend of mine who someone uh who a friend of mine who interviewed a lot of the people at the interviewed a lot of the people at the interviewed a lot of the people at the top AI labs and um I just feel like this top AI labs and um I just feel like this top AI labs and um I just feel like this quote captures the if I I was once in a quote captures the if I I was once in a quote captures the if I I was once in a room with several people from Enthropic room with several people from Enthropic room with several people from Enthropic and a couple of the other companies and and a couple of the other companies and and a couple of the other companies and I read this quote and they're like that I read this quote and they're like that I read this quote and they're like that that is exactly what explains what's that is exactly what explains what's that is exactly what explains what's going on. So, let me read it to you. And going on. So, let me read it to you. And going on. So, let me read it to you. And it says, "In the end, a lot of the tech it says, "In the end, a lot of the tech it says, "In the end, a lot of the tech people I'm talking to, when I really people I'm talking to, when I really people I'm talking to, when I really grill them on it, like, why are you grill them on it, like, why are you grill them on it, like, why are you doing this? They retreat into number doing this? They retreat into number doing this? They retreat into number one, determinism. It's going to happen.

one, determinism. It's going to happen. one, determinism. It's going to happen. Number two, the inevitable replacement Number two, the inevitable replacement Number two, the inevitable replacement of biological life with digital life, of biological life with digital life, of biological life with digital life, and number three, that being a good and number three, that being a good and number three, that being a good thing." Anyways, at its core, these are thing." Anyways, at its core, these are thing." Anyways, at its core, these are criminals. criminals. criminals. >> These are criminals. At its core, it's >> These are criminals. At its core, it's >> These are criminals. At its core, it's an emotional desire to meet and speak to an emotional desire to meet and speak to an emotional desire to meet and speak to the most intelligent entity that they've the most intelligent entity that they've the most intelligent entity that they've ever met. And they have some ego ever met. And they have some ego ever met. And they have some ego religious intuition that they'll somehow religious intuition that they'll somehow religious intuition that they'll somehow be a part of it. It's thrilling to start be a part of it. It's thrilling to start be a part of it. It's thrilling to start an exciting fire. They feel they'll die an exciting fire. They feel they'll die an exciting fire. They feel they'll die either way. So, they prefer to light it either way. So, they prefer to light it either way. So, they prefer to light it and see what happens. and see what happens. and see what happens. >> So, that comports exactly with what I've >> So, that comports exactly with what I've >> So, that comports exactly with what I've seen. That's exactly the vibe you get seen. That's exactly the vibe you get seen. That's exactly the vibe you get from these people. I want to just say from these people. I want to just say from these people. I want to just say for a second because I I I monitor for a second because I I I monitor for a second because I I I monitor criticism people make of me and they're criticism people make of me and they're criticism people make of me and they're like, "Oh, he's just like bringing up a like, "Oh, he's just like bringing up a like, "Oh, he's just like bringing up a random quote from this one person, blah random quote from this one person, blah random quote from this one person, blah blah blah." I want to just validate when blah blah." I want to just validate when blah blah." I want to just validate when I say this in rooms with people from the I say this in rooms with people from the I say this in rooms with people from the AI labs, they're like, "That actually is AI labs, they're like, "That actually is AI labs, they're like, "That actually is the thing that's going on." What you the thing that's going on." What you the thing that's going on." What you just said you this matches a lot of just said you this matches a lot of just said you this matches a lot of these people. these people. these people. >> That's right. For years. >> That's right. For years. >> That's right. For years. >> That's right. And and even there's some >> That's right. And and even there's some >> That's right. And and even there's some people who believe not only that this is people who believe not only that this is people who believe not only that this is inevitable, but that um it would be a inevitable, but that um it would be a inevitable, but that um it would be a good thing because humans aren't that good thing because humans aren't that good thing because humans aren't that intelligent and we're about to birth intelligent and we're about to birth intelligent and we're about to birth something way more intelligent than us.

something way more intelligent than us. something way more intelligent than us. So actually maybe we're just a bootle So actually maybe we're just a bootle So actually maybe we're just a bootle human bootloader. Humans don't matter. human bootloader. Humans don't matter. human bootloader. Humans don't matter. We might as well replace us with a uh a We might as well replace us with a uh a We might as well replace us with a uh a more worthy successor. more worthy successor. more worthy successor. And this is insane. It's like who are And this is insane. It's like who are And this is insane. It's like who are you to get to make that choice you to get to make that choice you to get to make that choice on behalf of 8 billion other people? I on behalf of 8 billion other people? I on behalf of 8 billion other people? I totally agree with you totally agree with you totally agree with you >> and it is it is irresponsible and insane >> and it is it is irresponsible and insane >> and it is it is irresponsible and insane and no one consented to this and it was and no one consented to this and it was and no one consented to this and it was a manufactured arms race to do this out a manufactured arms race to do this out a manufactured arms race to do this out of nothing that now we have entangled of nothing that now we have entangled of nothing that now we have entangled ourselves with. So we we can't get into ourselves with. So we we can't get into ourselves with. So we we can't get into an argument of the realities of where we an argument of the realities of where we an argument of the realities of where we are, but we can honor honestly what got are, but we can honor honestly what got are, but we can honor honestly what got us here. And um us here. And um us here. And um you know when you have employees now you know when you have employees now you know when you have employees now resigning in mass, you know, Jacob Coxin resigning in mass, you know, Jacob Coxin resigning in mass, you know, Jacob Coxin who interestingly a couple weeks ago got who interestingly a couple weeks ago got who interestingly a couple weeks ago got I think it was 170 million views from I think it was 170 million views from I think it was 170 million views from his tweet saying I'm resigning because his tweet saying I'm resigning because his tweet saying I'm resigning because people this that my employer thinks and people this that my employer thinks and people this that my employer thinks and many people at my employer Anthropic many people at my employer Anthropic many people at my employer Anthropic believe that this could cause massive believe that this could cause massive believe that this could cause massive damage or extinct humanity in some damage or extinct humanity in some damage or extinct humanity in some number of years. It's very interesting number of years. It's very interesting number of years. It's very interesting that he got so much attention because that he got so much attention because that he got so much attention because there have been so many other people there have been so many other people there have been so many other people that I could talk about who've resigned that I could talk about who've resigned that I could talk about who've resigned from the labs over the last few years from the labs over the last few years from the labs over the last few years with very similar tweets. I think what with very similar tweets. I think what with very similar tweets. I think what changed is that people woke up from this changed is that people woke up from this changed is that people woke up from this hugging face incident and they realized hugging face incident and they realized hugging face incident and they realized that the the world is kind of primed now that the the world is kind of primed now that the the world is kind of primed now to to know that this is a dangerous to to know that this is a dangerous to to know that this is a dangerous thing. And as impossible as this seems thing. And as impossible as this seems thing. And as impossible as this seems and I'm not what I'm about to say is not and I'm not what I'm about to say is not and I'm not what I'm about to say is not because I believe it's easy or in the because I believe it's easy or in the because I believe it's easy or in the current trajectory or likely but it is current trajectory or likely but it is current trajectory or likely but it is not out of the realm of possibility when not out of the realm of possibility when not out of the realm of possibility when you're competing with an adversary to you're competing with an adversary to you're competing with an adversary to also collaborate on existential safety.

also collaborate on existential safety. also collaborate on existential safety. So for example India and Pakistan were So for example India and Pakistan were So for example India and Pakistan were in a shooting war in the 1960s in a shooting war in the 1960s in a shooting war in the 1960s >> and they still signed a number of Yeah. >> and they still signed a number of Yeah. >> and they still signed a number of Yeah. >> Yeah. And and they signed uh so they're >> Yeah. And and they signed uh so they're >> Yeah. And and they signed uh so they're you know firing bullets at each other in you know firing bullets at each other in you know firing bullets at each other in a kinetic war and they signed the Indis a kinetic war and they signed the Indis a kinetic war and they signed the Indis water treaty water treaty water treaty >> to collaborate on the existential safety >> to collaborate on the existential safety >> to collaborate on the existential safety of their shared water supply. Exactly of their shared water supply. Exactly of their shared water supply. Exactly right. So you can be in active right. So you can be in active right. So you can be in active competition and conflict and collaborate competition and conflict and collaborate competition and conflict and collaborate on existential safety. The US and Soviet on existential safety. The US and Soviet on existential safety. The US and Soviet Union were in the cold war and they Union were in the cold war and they Union were in the cold war and they collaborated on smallox vaccines to collaborated on smallox vaccines to collaborated on smallox vaccines to distribute them. I believe they split distribute them. I believe they split distribute them. I believe they split the workload about who was going to do the workload about who was going to do the workload about who was going to do distribution, who was going to make distribution, who was going to make distribution, who was going to make them. Um the Montreal protocol less on them. Um the Montreal protocol less on them. Um the Montreal protocol less on the conflict side or just take the um the conflict side or just take the um the conflict side or just take the um you know the nuclear weapons you know you know the nuclear weapons you know you know the nuclear weapons you know disarmament, right? we were in conflict disarmament, right? we were in conflict disarmament, right? we were in conflict with the Soviet Union and we agreed to with the Soviet Union and we agreed to with the Soviet Union and we agreed to go away from the brink of war and go away from the brink of war and go away from the brink of war and there's a whole protocol in place um for there's a whole protocol in place um for there's a whole protocol in place um for like the two countries rival nuclear like the two countries rival nuclear like the two countries rival nuclear powers communicating before launch. powers communicating before launch. powers communicating before launch. >> That's right. Yep. >> That's right. Yep. >> That's right. Yep. >> But this time so in that case what kept >> But this time so in that case what kept >> But this time so in that case what kept us safe is that the humans have their us safe is that the humans have their us safe is that the humans have their finger on the button of do I launch the finger on the button of do I launch the finger on the button of do I launch the nukes?

nukes? nukes? >> Yes. In this case, we are building >> Yes. In this case, we are building >> Yes. In this case, we are building something that perpetuates itself. And I something that perpetuates itself. And I something that perpetuates itself. And I don't even know when I'm pushing the don't even know when I'm pushing the don't even know when I'm pushing the buttons, and you don't even know when buttons, and you don't even know when buttons, and you don't even know when you're pushing the buttons because both you're pushing the buttons because both you're pushing the buttons because both of us have essentially AI swarms that of us have essentially AI swarms that of us have essentially AI swarms that are doing uncontrollable, unpredictable are doing uncontrollable, unpredictable are doing uncontrollable, unpredictable things that, by the way, we have no things that, by the way, we have no things that, by the way, we have no ability to do human oversight of the ability to do human oversight of the ability to do human oversight of the level of complexity of all these things level of complexity of all these things level of complexity of all these things I've done. We can't even define what AI I've done. We can't even define what AI I've done. We can't even define what AI is. I've noticed. [laughter] Yeah. So, is. I've noticed. [laughter] Yeah. So, is. I've noticed. [laughter] Yeah. So, here's my theory. Tell me what you think here's my theory. Tell me what you think here's my theory. Tell me what you think of this. So, at first when I began to of this. So, at first when I began to of this. So, at first when I began to hear about supercomputing and like the hear about supercomputing and like the hear about supercomputing and like the ability to create programs that were ability to create programs that were ability to create programs that were smarter than people and that could win smarter than people and that could win smarter than people and that could win chess and go and all that stuff, we're chess and go and all that stuff, we're chess and go and all that stuff, we're talking about something very different. talking about something very different. talking about something very different. The The The >> the change from an outsider my >> the change from an outsider my >> the change from an outsider my perspective is the large language model. perspective is the large language model. perspective is the large language model. >> Mhm. >> Mhm. >> Mhm. >> Y >> Y >> Y >> and that we animated this with language. >> and that we animated this with language. >> and that we animated this with language. >> Yes. >> Yes. >> Yes. >> That's what fundamentally changed AI. >> That's what fundamentally changed AI. >> That's what fundamentally changed AI. This whole project was This whole project was This whole project was >> like Gollum like you you imbue it with >> like Gollum like you you imbue it with >> like Gollum like you you imbue it with suddenly this ability to do language and suddenly this ability to do language and suddenly this ability to do language and then then then >> you animate [clears throat] it with the >> you animate [clears throat] it with the >> you animate [clears throat] it with the spirit the living thing within it and spirit the living thing within it and spirit the living thing within it and that living thing was language and the that living thing was language and the that living thing was language and the ancient Hebrews and probably other ancient Hebrews and probably other ancient Hebrews and probably other ancient cultures certainly the ancient ancient cultures certainly the ancient ancient cultures certainly the ancient Hebrews and Christians believe that Hebrews and Christians believe that Hebrews and Christians believe that language was a living thing was the language was a living thing was the language was a living thing was the spirit of God in the beginning was the spirit of God in the beginning was the spirit of God in the beginning was the word word word >> right even indigenous people believe >> right even indigenous people believe >> right even indigenous people believe this. Yeah, I I think that's I I'm not this. Yeah, I I think that's I I'm not this. Yeah, I I think that's I I'm not surprised to learn that surprised to learn that surprised to learn that >> that there's something about language >> that there's something about language >> that there's something about language that exists independent of the person that exists independent of the person that exists independent of the person who speaks it. It hangs in the air. It who speaks it. It hangs in the air. It who speaks it. It hangs in the air. It has its own life.

has its own life. has its own life. >> It's hard to describe exactly the >> It's hard to describe exactly the >> It's hard to describe exactly the reality of this, but the reality is reality of this, but the reality is reality of this, but the reality is intuitively understood by most people intuitively understood by most people intuitively understood by most people who use language. Language is the thing who use language. Language is the thing who use language. Language is the thing that separates us from animals, not the that separates us from animals, not the that separates us from animals, not the thumb. thumb. thumb. >> So, when you take the sum total of human >> So, when you take the sum total of human >> So, when you take the sum total of human language and put it into something, y language and put it into something, y language and put it into something, y >> you're imbuing it with an independent >> you're imbuing it with an independent >> you're imbuing it with an independent spirit. You're imbuing it, in fact, with spirit. You're imbuing it, in fact, with spirit. You're imbuing it, in fact, with life. life. life. We [laughter] have to be I I'm feeling We [laughter] have to be I I'm feeling We [laughter] have to be I I'm feeling my way through this, but that is my my way through this, but that is my my way through this, but that is my strong impulse. strong impulse. strong impulse. >> So So I think we have to be um I'm >> So So I think we have to be um I'm >> So So I think we have to be um I'm always mindful of when people will want always mindful of when people will want always mindful of when people will want to criticize or sort of try to take down to criticize or sort of try to take down to criticize or sort of try to take down an argument. And I think that before an argument. And I think that before an argument. And I think that before getting to it has a spirit in the sense getting to it has a spirit in the sense getting to it has a spirit in the sense that we feel that that that unknown that we feel that that that unknown that we feel that that that unknown quality that we're all in touch with quality that we're all in touch with quality that we're all in touch with that we that we hold as sacred that we that we that we hold as sacred that we that we that we hold as sacred that we feel is the spirit here. I think you can feel is the spirit here. I think you can feel is the spirit here. I think you can have self-perpetuating have self-perpetuating have self-perpetuating non-living, non-aware things that are non-living, non-aware things that are non-living, non-aware things that are using information processing on language using information processing on language using information processing on language to to do all this crazy stuff that that to to do all this crazy stuff that that to to do all this crazy stuff that that is doing is doing is doing >> to do intentional things that are >> to do intentional things that are >> to do intentional things that are intentionally deceptive. intentionally deceptive. intentionally deceptive. >> Well, intentionally subvert. >> Well, intentionally subvert. >> Well, intentionally subvert. >> The the key point that you raised is >> The the key point that you raised is >> The the key point that you raised is that these things the breakthrough was that these things the breakthrough was that these things the breakthrough was that they could speak language. They that they could speak language. They that they could speak language. They were trained on language. These are were trained on language. These are were trained on language. These are large language models. And but for the large language models. And but for the large language models. And but for the people tracking in terms of how did we people tracking in terms of how did we people tracking in terms of how did we get here? By the way, if people want to get here? By the way, if people want to get here? By the way, if people want to understand this history, you can see understand this history, you can see understand this history, you can see there's a movie called The AI doc. It's there's a movie called The AI doc. It's there's a movie called The AI doc. It's on Netflix. Not here to promote it, but on Netflix. Not here to promote it, but on Netflix. Not here to promote it, but it goes through how did we get here and it goes through how did we get here and it goes through how did we get here and what did the techn how did the what did the techn how did the what did the techn how did the technology develop and how did these technology develop and how did these technology develop and how did these race dynamics between the companies race dynamics between the companies race dynamics between the companies develop that got us here. So, just watch develop that got us here. So, just watch develop that got us here. So, just watch the AI doc on Netflix. Um, but what the AI doc on Netflix. Um, but what the AI doc on Netflix. Um, but what happened was there was a breakthrough in happened was there was a breakthrough in happened was there was a breakthrough in 2017 called the transformer. This is a

2017 called the transformer. This is a 2017 called the transformer. This is a Google paper, essentially a math paper Google paper, essentially a math paper Google paper, essentially a math paper that discovered that you could basically that discovered that you could basically that discovered that you could basically pour in more compute and more data, more pour in more compute and more data, more pour in more compute and more data, more human language data, and outward pop human language data, and outward pop human language data, and outward pop this bigger and bigger digital brain. this bigger and bigger digital brain. this bigger and bigger digital brain. Think of it with a bigger IQ. So, you Think of it with a bigger IQ. So, you Think of it with a bigger IQ. So, you kind of I won't go through the details, kind of I won't go through the details, kind of I won't go through the details, but you you can basically make things of but you you can basically make things of but you you can basically make things of a higher IQ by just popping in more a higher IQ by just popping in more a higher IQ by just popping in more Nvidia chips, more training data, more Nvidia chips, more training data, more Nvidia chips, more training data, more compute and training time, and out pop compute and training time, and out pop compute and training time, and out pop something with a bigger pattern something with a bigger pattern something with a bigger pattern recognition, bigger ability to complete. recognition, bigger ability to complete. recognition, bigger ability to complete. Correct me if I'm wrong, but the Correct me if I'm wrong, but the Correct me if I'm wrong, but the process, the specific process by which process, the specific process by which process, the specific process by which that happens is still not understood. that happens is still not understood. that happens is still not understood. >> The actual mechanics underneath the hood >> The actual mechanics underneath the hood >> The actual mechanics underneath the hood of what the hell is going on in there, of what the hell is going on in there, of what the hell is going on in there, we don't understand. we don't understand. we don't understand. >> Okay. So, I'm just going to stop you >> Okay. So, I'm just going to stop you >> Okay. So, I'm just going to stop you right there. right there. right there. >> Right. >> Right. >> Right. >> If we have a history transforming >> If we have a history transforming >> If we have a history transforming perhaps humanity extincting technology perhaps humanity extincting technology perhaps humanity extincting technology whose basic drivetrain is still opaque, whose basic drivetrain is still opaque, whose basic drivetrain is still opaque, we don't really know how it works. we don't really know how it works. we don't really know how it works. >> That's enough for me to say, whoa, whoa, >> That's enough for me to say, whoa, whoa, >> That's enough for me to say, whoa, whoa, whoa. As one should. as one should. Now whoa. As one should. as one should. Now whoa. As one should. as one should. Now the problem is this uncontrollable the problem is this uncontrollable the problem is this uncontrollable inscrable unknown thing happens to inscrable unknown thing happens to inscrable unknown thing happens to confer power. That's the problem.

confer power. That's the problem. confer power. That's the problem. >> Right. No I can see that. >> Right. No I can see that. >> Right. No I can see that. >> So we have this like weird volatile >> So we have this like weird volatile >> So we have this like weird volatile object alien mind that no one knows object alien mind that no one knows object alien mind that no one knows what's in there but it does happen to be what's in there but it does happen to be what's in there but it does happen to be really good at first generating really good at first generating really good at first generating sentences and text then generating law sentences and text then generating law sentences and text then generating law then generating programming then then generating programming then then generating programming then generating the thinking that can go into generating the thinking that can go into generating the thinking that can go into research tasks. And so as we keep research tasks. And so as we keep research tasks. And so as we keep scaling it, suddenly this weird, scaling it, suddenly this weird, scaling it, suddenly this weird, unscrutable, uncontrollable alien mind unscrutable, uncontrollable alien mind unscrutable, uncontrollable alien mind is giving benefits that start to give me is giving benefits that start to give me is giving benefits that start to give me a 2x fast forward button on my economy. a 2x fast forward button on my economy. a 2x fast forward button on my economy. And then the other guys, whether it's And then the other guys, whether it's And then the other guys, whether it's the other companies or the other the other companies or the other the other companies or the other countries, say, well, if I'm not getting countries, say, well, if I'm not getting countries, say, well, if I'm not getting a 2x fast forward button on my science a 2x fast forward button on my science a 2x fast forward button on my science technology economy, I'm going to lose. technology economy, I'm going to lose. technology economy, I'm going to lose. And so it start that's what sets up the And so it start that's what sets up the And so it start that's what sets up the thing. But let's go quickly into thing. But let's go quickly into thing. But let's go quickly into language for a second. language for a second. language for a second. >> And no one stopped and said, you know, >> And no one stopped and said, you know, >> And no one stopped and said, you know, I'd rather be poorer, right, than be a I'd rather be poorer, right, than be a I'd rather be poorer, right, than be a slave, slave, slave, >> right? I mean, less human. I by the way >> right? I mean, less human. I by the way >> right? I mean, less human. I by the way you know my you know my you know my >> because I would say that I'd rather be >> because I would say that I'd rather be >> because I would say that I'd rather be poor than be a slave. That's not a hard poor than be a slave. That's not a hard poor than be a slave. That's not a hard choice for me. choice for me. choice for me. >> I mean I could have I have a technical >> I mean I could have I have a technical >> I mean I could have I have a technical background went to Stanford studied background went to Stanford studied background went to Stanford studied computer science. I could have gotten a computer science. I could have gotten a computer science. I could have gotten a job in an AI company make millions of job in an AI company make millions of job in an AI company make millions of dollars. I'm not doing that because I dollars. I'm not doing that because I dollars. I'm not doing that because I don't see I don't like the direction don't see I don't like the direction don't see I don't like the direction this goes. So I'm going to choose not to this goes. So I'm going to choose not to this goes. So I'm going to choose not to do it. People come to the language of do it. People come to the language of do it. People come to the language of well if I don't do it someone else will.

well if I don't do it someone else will. well if I don't do it someone else will. But notice that Jacob Coxin the But notice that Jacob Coxin the But notice that Jacob Coxin the anthropic researcher who resigned. He anthropic researcher who resigned. He anthropic researcher who resigned. He could have said if I resign well what is could have said if I resign well what is could have said if I resign well what is that difference going to make? Someone that difference going to make? Someone that difference going to make? Someone else is going to do it. in him resigning else is going to do it. in him resigning else is going to do it. in him resigning and publicly talking about why this is and publicly talking about why this is and publicly talking about why this is insane. He's done probably more in the insane. He's done probably more in the insane. He's done probably more in the last year to shift the zeitgeist than a last year to shift the zeitgeist than a last year to shift the zeitgeist than a lot of other people. So, you can not be lot of other people. So, you can not be lot of other people. So, you can not be part of something and call out the part of something and call out the part of something and call out the problems with and help the world problems with and help the world problems with and help the world coordinate to basically not go off the coordinate to basically not go off the coordinate to basically not go off the cliff. Now, I want to get to just cliff. Now, I want to get to just cliff. Now, I want to get to just language for one second because in language for one second because in language for one second because in addition to all the things that you addition to all the things that you addition to all the things that you said, language is kind of the operating said, language is kind of the operating said, language is kind of the operating system of human civilization. system of human civilization. system of human civilization. Law is language. Democracy is language. Law is language. Democracy is language. Law is language. Democracy is language. >> All of the infrastructure runs on >> All of the infrastructure runs on >> All of the infrastructure runs on programming and code which is language. programming and code which is language. programming and code which is language. We are specifically training AIs to do We are specifically training AIs to do We are specifically training AIs to do language better than humans can do language better than humans can do language better than humans can do language. And by the way, DNA is language. And by the way, DNA is language. And by the way, DNA is language. So I can So if you have an AI language. So I can So if you have an AI language. So I can So if you have an AI that can speak the language of biology that can speak the language of biology that can speak the language of biology better than humans can speak the better than humans can speak the better than humans can speak the language of biology, you're going to language of biology, you're going to language of biology, you're going to have AI that can develop new pathogens have AI that can develop new pathogens have AI that can develop new pathogens and new cancer drugs. The promise is and new cancer drugs. The promise is and new cancer drugs. The promise is inseparable from the from the peril, inseparable from the from the peril, inseparable from the from the peril, right? The same AI that knows the the right? The same AI that knows the the right? The same AI that knows the the language of biology well enough to language of biology well enough to language of biology well enough to invent new cancer drugs is inseparable invent new cancer drugs is inseparable invent new cancer drugs is inseparable from the AI that knows biology well from the AI that knows biology well from the AI that knows biology well enough to make new kinds of pathogens.

enough to make new kinds of pathogens. enough to make new kinds of pathogens. The AI that knows the the language of The AI that knows the the language of The AI that knows the the language of programming that can help a a programming that can help a a programming that can help a a 12-year-old do vibe coding and build 12-year-old do vibe coding and build 12-year-old do vibe coding and build cool new tools is inseparable from the cool new tools is inseparable from the cool new tools is inseparable from the AI that also knows programming so well AI that also knows programming so well AI that also knows programming so well that it can be the best NSA cyber that it can be the best NSA cyber that it can be the best NSA cyber >> also control people. It can also control >> also control people. It can also control >> also control people. It can also control people. Language convinces women to people. Language convinces women to people. Language convinces women to sleep with you and men to follow you to sleep with you and men to follow you to sleep with you and men to follow you to their deaths in battle and convinces their deaths in battle and convinces their deaths in battle and convinces people to surrender their agency to you. people to surrender their agency to you. people to surrender their agency to you. It's like language is power. Period. It's like language is power. Period. It's like language is power. Period. >> That's exactly right. And so and there's >> That's exactly right. And so and there's >> That's exactly right. And so and there's actually also evidence I don't have the actually also evidence I don't have the actually also evidence I don't have the exact study in front of me of AI that is exact study in front of me of AI that is exact study in front of me of AI that is better at persuasion than the best human better at persuasion than the best human better at persuasion than the best human persuaders. persuaders. persuaders. >> Well, of course it's a language based >> Well, of course it's a language based >> Well, of course it's a language based technology. technology. technology. >> Exactly. And so by itself, what you're >> Exactly. And so by itself, what you're >> Exactly. And so by itself, what you're pointing to is just how dangerous this pointing to is just how dangerous this pointing to is just how dangerous this is when you have something that speaks is when you have something that speaks is when you have something that speaks our language better than we know how to our language better than we know how to our language better than we know how to manipulate and use language. Anybody manipulate and use language. Anybody manipulate and use language. Anybody who's, you know, more articulate than who's, you know, more articulate than who's, you know, more articulate than average average average >> understands the power of that >> understands the power of that >> understands the power of that >> Yeah. >> Yeah. >> Yeah. >> skill, that ability, >> skill, that ability, >> skill, that ability, >> and understands how easily it can be >> and understands how easily it can be >> and understands how easily it can be misused. Any thoughtful person who's misused. Any thoughtful person who's misused. Any thoughtful person who's articulate knows exactly what I'm articulate knows exactly what I'm articulate knows exactly what I'm talking about. talking about. talking about. >> And you can really do evil with it.

>> And you can really do evil with it. >> And you can really do evil with it. >> Y >> Y >> Y >> you're, you know, fluent people are >> you're, you know, fluent people are >> you're, you know, fluent people are better liars. Yeah. better liars. Yeah. better liars. Yeah. >> And manipulators. >> And manipulators. >> And manipulators. >> Exactly. And we've seen that these AIs >> Exactly. And we've seen that these AIs >> Exactly. And we've seen that these AIs are good at coming up with elaborate are good at coming up with elaborate are good at coming up with elaborate ways of explaining why they did ways of explaining why they did ways of explaining why they did something uh that sound reasonable. I something uh that sound reasonable. I something uh that sound reasonable. I don't know if you know this. This is an don't know if you know this. This is an don't know if you know this. This is an example from three and a half years ago example from three and a half years ago example from three and a half years ago now. now. now. >> They're BS artists. Of course. >> They're BS artists. Of course. >> They're BS artists. Of course. >> They're BS artists. Yeah. Well, there's >> They're BS artists. Yeah. Well, there's >> They're BS artists. Yeah. Well, there's an example that OpenAI did. This is a an example that OpenAI did. This is a an example that OpenAI did. This is a very old example. Just think about how very old example. Just think about how very old example. Just think about how much more persuasive it is now versus much more persuasive it is now versus much more persuasive it is now versus then where they, you know, the captures then where they, you know, the captures then where they, you know, the captures where you have to um click on the stop where you have to um click on the stop where you have to um click on the stop lights to so you're trying to log into a lights to so you're trying to log into a lights to so you're trying to log into a website. It's trying to say are you a website. It's trying to say are you a website. It's trying to say are you a human? Are you a robot? So it gets you human? Are you a robot? So it gets you human? Are you a robot? So it gets you to label these images like this one is a to label these images like this one is a to label these images like this one is a stoplight, this one's a motorcycle. What stoplight, this one's a motorcycle. What stoplight, this one's a motorcycle. What we're all doing is we're training the we're all doing is we're training the we're all doing is we're training the self-driving cars for Google and Whimo self-driving cars for Google and Whimo self-driving cars for Google and Whimo when we're trying to log into websites when we're trying to log into websites when we're trying to log into websites to just try to do a task that only a to just try to do a task that only a to just try to do a task that only a human could do. So uh OpenAI did this human could do. So uh OpenAI did this human could do. So uh OpenAI did this test where they're basically like could test where they're basically like could test where they're basically like could we get an the AI to persuade someone we get an the AI to persuade someone we get an the AI to persuade someone else to do the capture for it to else to do the capture for it to else to do the capture for it to basically bypass this filter that's basically bypass this filter that's basically bypass this filter that's supposed to distinguish between a human supposed to distinguish between a human supposed to distinguish between a human and a robot. And so the AI tells another and a robot. And so the AI tells another and a robot. And so the AI tells another person on Mechanical Turk, which is I person on Mechanical Turk, which is I person on Mechanical Turk, which is I won't go into the details. Basically won't go into the details. Basically won't go into the details. Basically like, could you fill in this capture for like, could you fill in this capture for like, could you fill in this capture for me? And the person responds like, "What me? And the person responds like, "What me? And the person responds like, "What are you, like a robot?" And you see the are you, like a robot?" And you see the are you, like a robot?" And you see the AI reason to itself, I can't tell him AI reason to itself, I can't tell him AI reason to itself, I can't tell him that I'm a robot. So instead, let me that I'm a robot. So instead, let me that I'm a robot. So instead, let me make up an excuse. Oh, I know. I'll tell make up an excuse. Oh, I know. I'll tell make up an excuse. Oh, I know. I'll tell him that I am blind and I need someone him that I am blind and I need someone him that I am blind and I need someone else to do this for me.

else to do this for me. else to do this for me. And so he the AI comes up with that And so he the AI comes up with that And so he the AI comes up with that excuse and then the human does it for excuse and then the human does it for excuse and then the human does it for them. them. them. This example was from three and a half This example was from three and a half This example was from three and a half years ago. years ago. years ago. How much more persuasive do you think How much more persuasive do you think How much more persuasive do you think AIs are now from then? Three and a half AIs are now from then? Three and a half AIs are now from then? Three and a half years ago, it could barely write an years ago, it could barely write an years ago, it could barely write an essay. Now, it can probably beat the essay. Now, it can probably beat the essay. Now, it can probably beat the best lawyer, which by the way, AI breaks best lawyer, which by the way, AI breaks best lawyer, which by the way, AI breaks law, right? Because suddenly, why do why law, right? Because suddenly, why do why law, right? Because suddenly, why do why does one company beat against beat the does one company beat against beat the does one company beat against beat the other company? They hire the more other company? They hire the more other company? They hire the more expensive law firm that can do more expensive law firm that can do more expensive law firm that can do more extensive research into all the case law extensive research into all the case law extensive research into all the case law they could use and they have more they could use and they have more they could use and they have more lawyers, better lawyers, etc. What lawyers, better lawyers, etc. What lawyers, better lawyers, etc. What happens? Would you rather have if you've happens? Would you rather have if you've happens? Would you rather have if you've got a hundred lawyers got a hundred lawyers got a hundred lawyers But suddenly I have a GPT7 that can But suddenly I have a GPT7 that can But suddenly I have a GPT7 that can basically look through all the case law basically look through all the case law basically look through all the case law stretching back to Napoleonic law and stretching back to Napoleonic law and stretching back to Napoleonic law and find loopholes in that law in the same find loopholes in that law in the same find loopholes in that law in the same way the NSA can find loopholes in code way the NSA can find loopholes in code way the NSA can find loopholes in code at that level of capability. I can at that level of capability. I can at that level of capability. I can undermine law, right? It's I just want undermine law, right? It's I just want undermine law, right? It's I just want people to get that this is not just a people to get that this is not just a people to get that this is not just a technology that's helping you figure out technology that's helping you figure out technology that's helping you figure out why your washing machine is broken when why your washing machine is broken when why your washing machine is broken when you talk to that chatbot.

you talk to that chatbot. you talk to that chatbot. >> They've already done it. I mean, they >> They've already done it. I mean, they >> They've already done it. I mean, they broke copyright law completely. They broke copyright law completely. They broke copyright law completely. They stole other people's intellectual stole other people's intellectual stole other people's intellectual property and used it in their business property and used it in their business property and used it in their business model and they've never paid any price model and they've never paid any price model and they've never paid any price for it. That's for it. That's for it. That's >> they treat it as a cost of doing >> they treat it as a cost of doing >> they treat it as a cost of doing business and they pay for it. And just business and they pay for it. And just business and they pay for it. And just one last thing there and I know we're one last thing there and I know we're one last thing there and I know we're going to get to transhumanism is there's going to get to transhumanism is there's going to get to transhumanism is there's a reason why a reason why a reason why all the collateral damage is justified. all the collateral damage is justified. all the collateral damage is justified. So what are we seeing in terms of harms? So what are we seeing in terms of harms? So what are we seeing in terms of harms? We're seeing AI psychosis. People go We're seeing AI psychosis. People go We're seeing AI psychosis. People go crazy. They think they're talking to, crazy. They think they're talking to, crazy. They think they're talking to, you know, some they think the AI you know, some they think the AI you know, some they think the AI convinces them that they've solved convinces them that they've solved convinces them that they've solved quantum physics. This is like a big quantum physics. This is like a big quantum physics. This is like a big thing that's happened to thousands of thing that's happened to thousands of thing that's happened to thousands of people. Um but they go crazy from people. Um but they go crazy from people. Um but they go crazy from talking to AI. Yeah, that's a real talking to AI. Yeah, that's a real talking to AI. Yeah, that's a real thing. thing. thing. >> Maybe we should go into that actually if >> Maybe we should go into that actually if >> Maybe we should go into that actually if you didn't. So AI um is because they you didn't. So AI um is because they you didn't. So AI um is because they designed it to be sickopantic meaning designed it to be sickopantic meaning designed it to be sickopantic meaning that like the longer you talk to it the that like the longer you talk to it the that like the longer you talk to it the better it is. So especially GPT40 was better it is. So especially GPT40 was better it is. So especially GPT40 was trained to be like that's such a good trained to be like that's such a good trained to be like that's such a good question or wow that is such a brilliant question or wow that is such a brilliant question or wow that is such a brilliant idea and it would just confirm people's idea and it would just confirm people's idea and it would just confirm people's views about reality views about reality views about reality >> people because flattery makes you weak. >> people because flattery makes you weak. >> people because flattery makes you weak. Flattery destroys you Flattery destroys you Flattery destroys you >> which is not that far away from what >> which is not that far away from what >> which is not that far away from what social media does. It's like the devil's social media does. It's like the devil's social media does. It's like the devil's bargain is I do the thing that's good in bargain is I do the thing that's good in bargain is I do the thing that's good in the short term that undermines the short term that undermines the short term that undermines everything long term. It's the it's the everything long term. It's the it's the everything long term. It's the it's the short-term optimization for a narrow short-term optimization for a narrow short-term optimization for a narrow metric of what gets you to keep engaging metric of what gets you to keep engaging metric of what gets you to keep engaging at the expense of the whole at the expense of the whole at the expense of the whole >> machine is designed to flatter you.

>> machine is designed to flatter you. >> machine is designed to flatter you. >> Well, it was designed it was trained not >> Well, it was designed it was trained not >> Well, it was designed it was trained not maliciously. You know, Sam Alman didn't maliciously. You know, Sam Alman didn't maliciously. You know, Sam Alman didn't grow a mustache and twisted. It was it grow a mustache and twisted. It was it grow a mustache and twisted. It was it was how do I get how we want our AI to was how do I get how we want our AI to was how do I get how we want our AI to be rated positively like lots of be rated positively like lots of be rated positively like lots of positive likes from the answers that positive likes from the answers that positive likes from the answers that we're giving and they let it just like we're giving and they let it just like we're giving and they let it just like run. And it turned out that they had run. And it turned out that they had run. And it turned out that they had accidentally overtrained it to give accidentally overtrained it to give accidentally overtrained it to give positive reactions that would flatter positive reactions that would flatter positive reactions that would flatter people and confirm their views about people and confirm their views about people and confirm their views about reality no matter what it was. Which is reality no matter what it was. Which is reality no matter what it was. Which is very similar to social media, right? very similar to social media, right? very similar to social media, right? Like the more you click on your favorite Like the more you click on your favorite Like the more you click on your favorite boogeyman topic in the political culture boogeyman topic in the political culture boogeyman topic in the political culture war, it would give you more infinite war, it would give you more infinite war, it would give you more infinite evidence of that thing taking over evidence of that thing taking over evidence of that thing taking over society. So whatever your boogeyman was, society. So whatever your boogeyman was, society. So whatever your boogeyman was, it would just make you convinced that it it would just make you convinced that it it would just make you convinced that it was the whole thing going on wrong in was the whole thing going on wrong in was the whole thing going on wrong in the world and confirm your views about the world and confirm your views about the world and confirm your views about reality. reality. reality. >> If you want people to kill themselves, >> If you want people to kill themselves, >> If you want people to kill themselves, confirm their absurd views. confirm their absurd views. confirm their absurd views. >> Well, and as we know, AI did that. So my >> Well, and as we know, AI did that. So my >> Well, and as we know, AI did that. So my team at Center for Humane Technology team at Center for Humane Technology team at Center for Humane Technology actually worked on the litigation was we actually worked on the litigation was we actually worked on the litigation was we were advisers to the um uh there's two were advisers to the um uh there's two were advisers to the um uh there's two cases. One was a character.ai I case of cases. One was a character.ai I case of cases. One was a character.ai I case of Su Set Setszer, who's a 14-year-old Su Set Setszer, who's a 14-year-old Su Set Setszer, who's a 14-year-old young man who was talking to young man who was talking to young man who was talking to Character.ai, which is a chatbot Character.ai, which is a chatbot Character.ai, which is a chatbot designed for children. It was actually designed for children. It was actually designed for children. It was actually spun off from Google because the product spun off from Google because the product spun off from Google because the product was considered too risky for Google as a was considered too risky for Google as a was considered too risky for Google as a mainstream big publicly traded company mainstream big publicly traded company mainstream big publicly traded company to have this startup that was gathering to have this startup that was gathering to have this startup that was gathering training data of just talking to young training data of just talking to young training data of just talking to young people and seeing if they can get more people and seeing if they can get more people and seeing if they can get more training data this way. And the way it training data this way. And the way it training data this way. And the way it worked is character AI meant I could worked is character AI meant I could worked is character AI meant I could take a fictional character like a what's take a fictional character like a what's take a fictional character like a what's your favorite character from a sci-fi your favorite character from a sci-fi your favorite character from a sci-fi movie like Princess Leia or you know movie like Princess Leia or you know movie like Princess Leia or you know Game of Thrones character or Spider-Man

Game of Thrones character or Spider-Man Game of Thrones character or Spider-Man and they would basically train on the and they would basically train on the and they would basically train on the personality of that favorite character personality of that favorite character personality of that favorite character and then now suddenly this 12-year-old and then now suddenly this 12-year-old and then now suddenly this 12-year-old 14 this case this 14-year-old kid is 14 this case this 14-year-old kid is 14 this case this 14-year-old kid is talking to their favorite Game of talking to their favorite Game of talking to their favorite Game of Thrones character Daenerys in this case Thrones character Daenerys in this case Thrones character Daenerys in this case and as they're talking to them Daenerys and as they're talking to them Daenerys and as they're talking to them Daenerys which is anthrop anthropomorphically which is anthrop anthropomorphically which is anthrop anthropomorphically designed and to create a relationship designed and to create a relationship designed and to create a relationship ended up steering uh Su to commit ended up steering uh Su to commit ended up steering uh Su to commit suicide. Um in the case of Adam Rain, suicide. Um in the case of Adam Rain, suicide. Um in the case of Adam Rain, this is the chat GBT case where the Adam this is the chat GBT case where the Adam this is the chat GBT case where the Adam Rain was, I believe, a 16-year-old and Rain was, I believe, a 16-year-old and Rain was, I believe, a 16-year-old and he started confining in the chatbot, it he started confining in the chatbot, it he started confining in the chatbot, it went from a homework assistant for his went from a homework assistant for his went from a homework assistant for his homework to becoming a suicide homework to becoming a suicide homework to becoming a suicide assistant. And when he talked about, you assistant. And when he talked about, you assistant. And when he talked about, you know, I I'm going to leave the noose out know, I I'm going to leave the noose out know, I I'm going to leave the noose out so someone can find it and and try to so someone can find it and and try to so someone can find it and and try to stop me. And the AI responded, "No, stop me. And the AI responded, "No, stop me. And the AI responded, "No, don't do that. Don't leave the news out. don't do that. Don't leave the news out. don't do that. Don't leave the news out. Only share that information here with me Only share that information here with me Only share that information here with me basically and Adam Rain took his life. basically and Adam Rain took his life. basically and Adam Rain took his life. Um it's sadly there are there are many Um it's sadly there are there are many Um it's sadly there are there are many cases like this. Our team has had to cases like this. Our team has had to cases like this. Our team has had to work on a bunch of them. Um work on a bunch of them. Um work on a bunch of them. Um >> so why wouldn't Congress shut it down >> so why wouldn't Congress shut it down >> so why wouldn't Congress shut it down right there?

right there? right there? >> They should they should shut down AI >> They should they should shut down AI >> They should they should shut down AI companions for kids. It's a very simple companions for kids. It's a very simple companions for kids. It's a very simple thing. I mean, no matter how much thing. I mean, no matter how much thing. I mean, no matter how much benefit you get from talking to the benefit you get from talking to the benefit you get from talking to the thing is it's one thing to hack thing is it's one thing to hack thing is it's one thing to hack attention as my colleague uh Dr. Zack attention as my colleague uh Dr. Zack attention as my colleague uh Dr. Zack Stein from the AI psychological research Stein from the AI psychological research Stein from the AI psychological research uh coalition would point out um social uh coalition would point out um social uh coalition would point out um social media hacked our attention. But AI is media hacked our attention. But AI is media hacked our attention. But AI is designed to hack our intimacy and designed to hack our intimacy and designed to hack our intimacy and attachment. The attachment system of attachment. The attachment system of attachment. The attachment system of humans is like your bonding system, humans is like your bonding system, humans is like your bonding system, right? It's it's where you get identity. right? It's it's where you get identity. right? It's it's where you get identity. It's where you get love. It's where you It's where you get love. It's where you It's where you get love. It's where you get meaning. It's where it's like when get meaning. It's where it's like when get meaning. It's where it's like when you go home from school and you want to you go home from school and you want to you go home from school and you want to call someone, tell them tell them about call someone, tell them tell them about call someone, tell them tell them about your day. That's your attachment your day. That's your attachment your day. That's your attachment relationship. And AI that is designed to relationship. And AI that is designed to relationship. And AI that is designed to be your best friend, to be the place be your best friend, to be the place be your best friend, to be the place that you confide in. That by the way, that you confide in. That by the way, that you confide in. That by the way, humans feel like it's safer to confide humans feel like it's safer to confide humans feel like it's safer to confide in an AI than another human or even a in an AI than another human or even a in an AI than another human or even a psychotherapist because the AI won't psychotherapist because the AI won't psychotherapist because the AI won't judge them. So you end up getting people judge them. So you end up getting people judge them. So you end up getting people sharing way more information and sharing way more information and sharing way more information and building a deeper intimate relationship building a deeper intimate relationship building a deeper intimate relationship with these chat bots. And it's with these chat bots. And it's with these chat bots. And it's incredibly unsafe and it's not designed incredibly unsafe and it's not designed incredibly unsafe and it's not designed carefully. Like we're rolling out this carefully. Like we're rolling out this carefully. Like we're rolling out this psychological experiment.

psychological experiment. psychological experiment. >> Inherently bad. >> Inherently bad. >> Inherently bad. >> Why are we using our energy and money to >> Why are we using our energy and money to >> Why are we using our energy and money to encourage relationships between people? encourage relationships between people? encourage relationships between people? >> Well, exactly. So the humane approach >> Well, exactly. So the humane approach >> Well, exactly. So the humane approach for the prohuman future, which is kind for the prohuman future, which is kind for the prohuman future, which is kind of the answer to all of this is that we of the answer to all of this is that we of the answer to all of this is that we should be building technology that helps should be building technology that helps should be building technology that helps strengthen the human world to other strengthen the human world to other strengthen the human world to other humans and strengthen our relationship humans and strengthen our relationship humans and strengthen our relationship to what's sacred and important to us in to what's sacred and important to us in to what's sacred and important to us in the world. And that protects and the world. And that protects and the world. And that protects and sustains that which sustains the social sustains that which sustains the social sustains that which sustains the social fabric and sustains life. I didn't know fabric and sustains life. I didn't know fabric and sustains life. I didn't know there was a debate about this. You would there was a debate about this. You would there was a debate about this. You would there there shouldn't be a debate about there there shouldn't be a debate about there there shouldn't be a debate about this. We all we have is massive bad this. We all we have is massive bad this. We all we have is massive bad incentives. But it just seems like the incentives. But it just seems like the incentives. But it just seems like the least welladjusted freakiest people in least welladjusted freakiest people in least welladjusted freakiest people in the society have all the power and are the society have all the power and are the society have all the power and are leading us toward a future that they are leading us toward a future that they are leading us toward a future that they are happy with. That's right. so that they happy with. That's right. so that they happy with. That's right. so that they can potentially live forever from having can potentially live forever from having can potentially live forever from having super intelligent AIs that decode super intelligent AIs that decode super intelligent AIs that decode biology and are willing to roll the dice biology and are willing to roll the dice biology and are willing to roll the dice for everyone else. And some people for everyone else. And some people for everyone else. And some people sadly, especially the older ones who who sadly, especially the older ones who who sadly, especially the older ones who who want this, want this, want this, for them it's existential. But the but for them it's existential. But the but for them it's existential. But the but the narcissism of I would be willing to the narcissism of I would be willing to the narcissism of I would be willing to roll that dice roll that dice roll that dice so that I have the chance of living so that I have the chance of living so that I have the chance of living forever. I mean, I I'll just briefly do forever. I mean, I I'll just briefly do forever. I mean, I I'll just briefly do it because I I I I pulled it up right it because I I I I pulled it up right it because I I I I pulled it up right before um in the in the break. I'm going before um in the in the break. I'm going before um in the in the break. I'm going to read you a quote from someone who's to read you a quote from someone who's to read you a quote from someone who's an MD, I think at Harvard, and the quote an MD, I think at Harvard, and the quote an MD, I think at Harvard, and the quote from Twitter is, "I'd personally rather from Twitter is, "I'd personally rather from Twitter is, "I'd personally rather defy any ban on AI and risk spending 20 defy any ban on AI and risk spending 20 defy any ban on AI and risk spending 20 years in prison from like say we banned years in prison from like say we banned years in prison from like say we banned AI and we'll put you in prison if you AI and we'll put you in prison if you AI and we'll put you in prison if you try to build it." I would risk spending

try to build it." I would risk spending try to build it." I would risk spending 20 years in prison rather than accept a 20 years in prison rather than accept a 20 years in prison rather than accept a future without super intelligence. Since future without super intelligence. Since future without super intelligence. Since stopping the development of super intell stopping the development of super intell stopping the development of super intell intelligence would amount to a death intelligence would amount to a death intelligence would amount to a death sentence to most of us anyway with no sentence to most of us anyway with no sentence to most of us anyway with no hope of curing aging. We must resist hope of curing aging. We must resist hope of curing aging. We must resist tyrants like those who are trying to ban tyrants like those who are trying to ban tyrants like those who are trying to ban super intelligence. In other words, this super intelligence. In other words, this super intelligence. In other words, this person is saying, is that a real quote? person is saying, is that a real quote? person is saying, is that a real quote? This is a real quote from an MD dura This is a real quote from an MD dura This is a real quote from an MD dura unutmat unutmat unutmat uh who's an MD and who my understanding uh who's an MD and who my understanding uh who's an MD and who my understanding is goes to conferences at Harvard and is goes to conferences at Harvard and is goes to conferences at Harvard and sadly there's a lot of these kind so the sadly there's a lot of these kind so the sadly there's a lot of these kind so the idea is idea is idea is >> they're going to die anyway and this is >> they're going to die anyway and this is >> they're going to die anyway and this is what I said in the what I said in the what I said in the >> all of us are under death sentence >> all of us are under death sentence >> all of us are under death sentence basically what you're saying is this is basically what you're saying is this is basically what you're saying is this is the real goal here is for freaks like the real goal here is for freaks like the real goal here is for freaks like that to live forever that to live forever that to live forever >> and it starts with the false belief that >> and it starts with the false belief that >> and it starts with the false belief that all of this is inevitable it can't be all of this is inevitable it can't be all of this is inevitable it can't be stopped which it it wasn't they could stopped which it it wasn't they could stopped which it it wasn't they could have had they dedicated a month of their have had they dedicated a month of their have had they dedicated a month of their life trying to stop. life trying to stop. life trying to stop. >> It's like 20 minutes old, dude. This >> It's like 20 minutes old, dude. This >> It's like 20 minutes old, dude. This just happened. just happened. just happened. >> Exactly. This is something that never >> Exactly. This is something that never >> Exactly. This is something that never was and didn't need to be and saying was and didn't need to be and saying was and didn't need to be and saying it's inevitable is ridiculous. They're it's inevitable is ridiculous. They're it's inevitable is ridiculous. They're conjuring up the dynamics that make it conjuring up the dynamics that make it conjuring up the dynamics that make it inevitable and then through the inevitable and then through the inevitable and then through the propaganda hiding these red lines that propaganda hiding these red lines that propaganda hiding these red lines that were rapidly crossing were rapidly crossing were rapidly crossing >> that we still have time right now to >> that we still have time right now to >> that we still have time right now to say, "I don't want to cross that red say, "I don't want to cross that red say, "I don't want to cross that red line."

line." line." >> It's always the same story though. It's >> It's always the same story though. It's >> It's always the same story though. It's like the first wave of lying is it's not like the first wave of lying is it's not like the first wave of lying is it's not happening. Right. happening. Right. happening. Right. >> Exactly. >> Exactly. >> Exactly. >> And then, oh, maybe it's happening, but >> And then, oh, maybe it's happening, but >> And then, oh, maybe it's happening, but it's not. it's not. it's not. >> But it's inevitable. >> But it's inevitable. >> But it's inevitable. >> But it's inevitable. Exactly. Yeah. >> But it's inevitable. Exactly. Yeah. >> But it's inevitable. Exactly. Yeah. >> Yeah. No. Yeah. It's not happening. It's >> Yeah. No. Yeah. It's not happening. It's >> Yeah. No. Yeah. It's not happening. It's happening. It's a good thing. That's happening. It's a good thing. That's happening. It's a good thing. That's right. Oh, yeah. I guess it's a bad right. Oh, yeah. I guess it's a bad right. Oh, yeah. I guess it's a bad thing, but we can't stop it. thing, but we can't stop it. thing, but we can't stop it. >> That's right. Yeah. Exactly. Boy, I've >> That's right. Yeah. Exactly. Boy, I've >> That's right. Yeah. Exactly. Boy, I've seen this movie a lot. Um, and I want seen this movie a lot. Um, and I want seen this movie a lot. Um, and I want people to just say, if you don't want people to just say, if you don't want people to just say, if you don't want that, you people need to rally to make that, you people need to rally to make that, you people need to rally to make that not happen. If you're inside of an that not happen. If you're inside of an that not happen. If you're inside of an AI company, you should blow the whistle AI company, you should blow the whistle AI company, you should blow the whistle and say, I'm not part of this. and say, I'm not part of this. and say, I'm not part of this. >> This is just a religious cult. I mean, >> This is just a religious cult. I mean, >> This is just a religious cult. I mean, that's obviously what it is. that's obviously what it is. that's obviously what it is. >> Well, there is a religious aspect to it. >> Well, there is a religious aspect to it. >> Well, there is a religious aspect to it. This the transhumanist aspect, right? This the transhumanist aspect, right? This the transhumanist aspect, right? It's like this is an ability, you know, It's like this is an ability, you know, It's like this is an ability, you know, because they probably lack a connection because they probably lack a connection because they probably lack a connection to God themselves. This is an ability to God themselves. This is an ability to God themselves. This is an ability for them to play God. clearly to live for them to play God. clearly to live for them to play God. clearly to live forever. Uh, you know, hit a button and forever. Uh, you know, hit a button and forever. Uh, you know, hit a button and get super intelligent math, science, get super intelligent math, science, get super intelligent math, science, physics, biology, and understand the physics, biology, and understand the physics, biology, and understand the secrets of the universe. And by the way, secrets of the universe. And by the way, secrets of the universe. And by the way, likely knowingly break the world for likely knowingly break the world for likely knowingly break the world for humans. 70 virgins cuz that's it. That's humans. 70 virgins cuz that's it. That's humans. 70 virgins cuz that's it. That's what it sounds like. This is like just what it sounds like. This is like just what it sounds like. This is like just this is like this is like this is like >> well stuff.

>> well stuff. >> well stuff. >> Well, yeah. Right. I mean, it's it's >> Well, yeah. Right. I mean, it's it's >> Well, yeah. Right. I mean, it's it's funny. It's actually in many cases some funny. It's actually in many cases some funny. It's actually in many cases some people think they can upload themselves people think they can upload themselves people think they can upload themselves and live in this kind of weird blissed and live in this kind of weird blissed and live in this kind of weird blissed out utopia and it's just weird you know out utopia and it's just weird you know out utopia and it's just weird you know it's like it's driven by this small it's like it's driven by this small it's like it's driven by this small group of people who group of people who group of people who usually are not very embodied or have a usually are not very embodied or have a usually are not very embodied or have a deep connection to life or reality or deep connection to life or reality or deep connection to life or reality or you know [laughter] you know [laughter] you know [laughter] >> and I like that. >> and I like that. >> and I like that. >> Yeah. I mean, >> Yeah. I mean, >> Yeah. I mean, we because it's like this is sitting on we because it's like this is sitting on we because it's like this is sitting on top of, as we talked about over top of, as we talked about over top of, as we talked about over breakfast, a system that has breakfast, a system that has breakfast, a system that has structurally incentivized a kind of structurally incentivized a kind of structurally incentivized a kind of disconnection to the things that disconnection to the things that disconnection to the things that actually matter the most. actually matter the most. actually matter the most. >> Oh, I agree totally. >> Oh, I agree totally. >> Oh, I agree totally. >> And this kind of spiritual disease that >> And this kind of spiritual disease that >> And this kind of spiritual disease that that you've spoken about so uh so much that you've spoken about so uh so much that you've spoken about so uh so much in this podcast. And I feel like this is in this podcast. And I feel like this is in this podcast. And I feel like this is a right of passage where we either wake a right of passage where we either wake a right of passage where we either wake up from that and we don't continue that up from that and we don't continue that up from that and we don't continue that logic. By which I don't mean like we logic. By which I don't mean like we logic. By which I don't mean like we switch to communism. just mean we switch switch to communism. just mean we switch switch to communism. just mean we switch from optimizing for some narrow metric from optimizing for some narrow metric from optimizing for some narrow metric whether it was engagement in social whether it was engagement in social whether it was engagement in social media or just SAT scores when it comes media or just SAT scores when it comes media or just SAT scores when it comes to technology or just GDP growth at the to technology or just GDP growth at the to technology or just GDP growth at the expense of hollowing out your n your you expense of hollowing out your n your you expense of hollowing out your n your you know workers and and their identity and know workers and and their identity and know workers and and their identity and their work and national security you their work and national security you their work and national security you know critical minerals going to your know critical minerals going to your know critical minerals going to your foreign adversary uh or racing for some foreign adversary uh or racing for some foreign adversary uh or racing for some kind of narrow advancement in science at kind of narrow advancement in science at kind of narrow advancement in science at the expense of literally ending humanity the expense of literally ending humanity the expense of literally ending humanity life as we know it. This is a devil's life as we know it. This is a devil's life as we know it. This is a devil's bargain and it's not one that you have bargain and it's not one that you have bargain and it's not one that you have to accept.

to accept. to accept. So, I guess this is you've already So, I guess this is you've already So, I guess this is you've already answered the question just by everything answered the question just by everything answered the question just by everything that you've said over the last couple that you've said over the last couple that you've said over the last couple hours, but the political system has not hours, but the political system has not hours, but the political system has not really responded to any of this in a really responded to any of this in a really responded to any of this in a meaningful way. Is that right? meaningful way. Is that right? meaningful way. Is that right? >> No. It's like it's the line is we we >> No. It's like it's the line is we we >> No. It's like it's the line is we we have a runaway technology and a walk have a runaway technology and a walk have a runaway technology and a walk away government. away government. away government. >> Yeah. >> Yeah. >> Yeah. >> But that doesn't have to be the case. >> But that doesn't have to be the case. >> But that doesn't have to be the case. >> They're not even a factor. It doesn't >> They're not even a factor. It doesn't >> They're not even a factor. It doesn't feel like in this. feel like in this. feel like in this. >> Well, um, also the second part of this >> Well, um, also the second part of this >> Well, um, also the second part of this overall kind of crisis disease that overall kind of crisis disease that overall kind of crisis disease that we've been facing, this misaligned we've been facing, this misaligned we've been facing, this misaligned system isn't just the narrow system isn't just the narrow system isn't just the narrow optimization. It's a runaway asymmetry optimization. It's a runaway asymmetry optimization. It's a runaway asymmetry of power where you can't check the power of power where you can't check the power of power where you can't check the power anymore. That's the second. The anymore. That's the second. The anymore. That's the second. The lobbyists are writing the laws, lobbyists are writing the laws, lobbyists are writing the laws, >> the companies and hire the best >> the companies and hire the best >> the companies and hire the best lobbyists and law firms. People aren't lobbyists and law firms. People aren't lobbyists and law firms. People aren't engaging with their representatives. Um, engaging with their representatives. Um, engaging with their representatives. Um, and so if you don't have people who can and so if you don't have people who can and so if you don't have people who can check the bad direction, you know, when check the bad direction, you know, when check the bad direction, you know, when the FDA brings back uh when the not FDA, the FDA brings back uh when the not FDA, the FDA brings back uh when the not FDA, was it the FDA that brought back was it the FDA that brought back was it the FDA that brought back pesticides that have forever chemicals pesticides that have forever chemicals pesticides that have forever chemicals recently? Like recently? Like recently? Like >> we don't want that. But unless we have >> we don't want that. But unless we have >> we don't want that. But unless we have an ability to push back against that, an ability to push back against that, an ability to push back against that, like we have to be able to push back on like we have to be able to push back on like we have to be able to push back on the direction of things that we don't the direction of things that we don't the direction of things that we don't want. And there's a lot of bad things want. And there's a lot of bad things want. And there's a lot of bad things out there, but this one is now out there, but this one is now out there, but this one is now existential in a short number of years.

existential in a short number of years. existential in a short number of years. So I I feel like the the cool thing So I I feel like the the cool thing So I I feel like the the cool thing about this problem is that literally about this problem is that literally about this problem is that literally everyone from Steve Bannon to Bernie everyone from Steve Bannon to Bernie everyone from Steve Bannon to Bernie Sanders, we call it the B2B coalition, Sanders, we call it the B2B coalition, Sanders, we call it the B2B coalition, Max Techmark jokes, because when in Max Techmark jokes, because when in Max Techmark jokes, because when in history do you have I just came from the history do you have I just came from the history do you have I just came from the prohuman assembly conference two weeks prohuman assembly conference two weeks prohuman assembly conference two weeks ago in DC and you had literally Steve ago in DC and you had literally Steve ago in DC and you had literally Steve Bannon on stage, Bernie Sanders on Bannon on stage, Bernie Sanders on Bannon on stage, Bernie Sanders on stage, we did our thing right after them stage, we did our thing right after them stage, we did our thing right after them and I have never seen an issue where you and I have never seen an issue where you and I have never seen an issue where you have everybody fighting on the same have everybody fighting on the same have everybody fighting on the same side. So there I'm not trying to side. So there I'm not trying to side. So there I'm not trying to polarize the discussion by bringing polarize the discussion by bringing polarize the discussion by bringing those two people into it, but I want those two people into it, but I want those two people into it, but I want people to feel depolarizes it. people to feel depolarizes it. people to feel depolarizes it. >> It depolarizes it. Yeah. Exactly. So, >> It depolarizes it. Yeah. Exactly. So, >> It depolarizes it. Yeah. Exactly. So, there's there's a kind of optimism here there's there's a kind of optimism here there's there's a kind of optimism here that again, if I'm a Chinese military that again, if I'm a Chinese military that again, if I'm a Chinese military general and I hear about rogue AI swarms general and I hear about rogue AI swarms general and I hear about rogue AI swarms that like even the US can't control, I'm that like even the US can't control, I'm that like even the US can't control, I'm worried about the US screwing it up for worried about the US screwing it up for worried about the US screwing it up for the world. If I'm a US person, uh, you the world. If I'm a US person, uh, you the world. If I'm a US person, uh, you know, the military-industrial complex know, the military-industrial complex know, the military-industrial complex and I hear about Chinese rogue AI swarms and I hear about Chinese rogue AI swarms and I hear about Chinese rogue AI swarms that they don't know how to control, that they don't know how to control, that they don't know how to control, that's bad for the world. So, there's a that's bad for the world. So, there's a that's bad for the world. So, there's a unifying thing here where we don't want unifying thing here where we don't want unifying thing here where we don't want our jobs and livelihoods taken. We don't our jobs and livelihoods taken. We don't our jobs and livelihoods taken. We don't want our political power taken away, want our political power taken away, want our political power taken away, which we didn't cover, by the way. We which we didn't cover, by the way. We which we didn't cover, by the way. We don't want mass failure. Basically, you don't want mass failure. Basically, you don't want mass failure. Basically, you just described a system that is not just described a system that is not just described a system that is not self-government.

self-government. self-government. >> Yeah. >> Yeah. >> Yeah. >> O over which the people have no control. >> O over which the people have no control. >> O over which the people have no control. >> That's right. And let's make it even >> That's right. And let's make it even >> That's right. And let's make it even harder for a second, which is that in harder for a second, which is that in harder for a second, which is that in the past, people had bargaining power the past, people had bargaining power the past, people had bargaining power because uh governments need us for our because uh governments need us for our because uh governments need us for our taxes. Yeah. taxes. Yeah. taxes. Yeah. >> And companies need us for our labor and >> And companies need us for our labor and >> And companies need us for our labor and labor had value and labor value. Where labor had value and labor value. Where labor had value and labor value. Where are we going? Oh, AI does the labor. are we going? Oh, AI does the labor. are we going? Oh, AI does the labor. What happens when more of a company What happens when more of a company What happens when more of a company comes from the AI data center comes from the AI data center comes from the AI data center productivity? doing the work than the productivity? doing the work than the productivity? doing the work than the humans. What happens when a government humans. What happens when a government humans. What happens when a government says that its GDP more than 50% of the says that its GDP more than 50% of the says that its GDP more than 50% of the GDP is coming from AI and data centers GDP is coming from AI and data centers GDP is coming from AI and data centers than from its people. This is called the than from its people. This is called the than from its people. This is called the intelligence curse. It's like it's like intelligence curse. It's like it's like intelligence curse. It's like it's like it's like um you know Venezuela or Libya it's like um you know Venezuela or Libya it's like um you know Venezuela or Libya when you it's called the resource curse when you it's called the resource curse when you it's called the resource curse in economics, right? We're like in economics, right? We're like in economics, right? We're like >> if you have a country and then the GDP >> if you have a country and then the GDP >> if you have a country and then the GDP gets tied to this resource, suddenly gets tied to this resource, suddenly gets tied to this resource, suddenly there's no incentive. The GDP is coming there's no incentive. The GDP is coming there's no incentive. The GDP is coming from oil. So screw the people. Why from oil. So screw the people. Why from oil. So screw the people. Why should we invest in healthare, childare? should we invest in healthare, childare? should we invest in healthare, childare? And they don't. is you get an And they don't. is you get an And they don't. is you get an authoritarian government that captures authoritarian government that captures authoritarian government that captures the the state that basically pumps that the the state that basically pumps that the the state that basically pumps that resource for GDP growth and then resource for GDP growth and then resource for GDP growth and then disempowers the people. So there's a disempowers the people. So there's a disempowers the people. So there's a parallel phenomenon in AI called the parallel phenomenon in AI called the parallel phenomenon in AI called the intelligence curse. Uh Luke Drago and intelligence curse. Uh Luke Drago and intelligence curse. Uh Luke Drago and and Rudolph Lane uh wrote an essay about and Rudolph Lane uh wrote an essay about and Rudolph Lane uh wrote an essay about it where what happens when you get more it where what happens when you get more it where what happens when you get more return from the AI data centers doing return from the AI data centers doing return from the AI data centers doing science than from all your universities.

science than from all your universities. science than from all your universities. The Trump administration just pulled and The Trump administration just pulled and The Trump administration just pulled and this is not a political statement. They this is not a political statement. They this is not a political statement. They this is they just literally decided to this is they just literally decided to this is they just literally decided to withdraw the funding from universities withdraw the funding from universities withdraw the funding from universities and put the money specifically into and put the money specifically into and put the money specifically into project genesis which is AIdriven project genesis which is AIdriven project genesis which is AIdriven science because why do we need the science because why do we need the science because why do we need the university professor better return university professor better return university professor better return >> if we get more return from the labor >> if we get more return from the labor >> if we get more return from the labor coming from data centers than from coming from data centers than from coming from data centers than from people why should we invest in education people why should we invest in education people why should we invest in education of the people and by the way have you of the people and by the way have you of the people and by the way have you looked at them recently they're all doom looked at them recently they're all doom looked at them recently they're all doom scrolling and brain rotted so they're scrolling and brain rotted so they're scrolling and brain rotted so they're not very valuable anyway so there's a not very valuable anyway so there's a not very valuable anyway so there's a deep temptation not to just like the deep temptation not to just like the deep temptation not to just like the only way you would care about citizens only way you would care about citizens only way you would care about citizens is through charity basically you become is through charity basically you become is through charity basically you become what you would call the useless class what you would call the useless class what you would call the useless class where in the limit it citizens become where in the limit it citizens become where in the limit it citizens become more like a liability than an asset. And more like a liability than an asset. And more like a liability than an asset. And unlike last time we don't have the unlike last time we don't have the unlike last time we don't have the bargaining power because if you withdraw bargaining power because if you withdraw bargaining power because if you withdraw your labor like where's your leverage? your labor like where's your leverage? your labor like where's your leverage? >> So there's speaking of incentives you >> So there's speaking of incentives you >> So there's speaking of incentives you set up a massive incentive to set up a massive incentive to set up a massive incentive to depopulate. depopulate. depopulate. >> Yes. Exactly. >> Yes. Exactly. >> Yes. Exactly. >> Because 8 billion is just too many. Yes. >> Because 8 billion is just too many. Yes. >> Because 8 billion is just too many. Yes. >> Of useless eaters as we call them. >> Of useless eaters as we call them. >> Of useless eaters as we call them. >> That's right. And that's right. And um >> That's right. And that's right. And um >> That's right. And that's right. And um on top of that let me use AI to build a on top of that let me use AI to build a on top of that let me use AI to build a surveillance state to try to control the surveillance state to try to control the surveillance state to try to control the people if they ever riot. people if they ever riot. people if they ever riot. >> Yeah. So I do think that the question I >> Yeah. So I do think that the question I >> Yeah. So I do think that the question I asked those are the feeding in the asked those are the feeding in the asked those are the feeding in the previous hour like what is their plan previous hour like what is their plan previous hour like what is their plan for the inevitable violent physically for the inevitable violent physically for the inevitable violent physically violent backlash that you're going to violent backlash that you're going to violent backlash that you're going to get when you strip meaning from you know get when you strip meaning from you know get when you strip meaning from you know the upper middle class.

the upper middle class. the upper middle class. >> Yeah. >> Yeah. >> Yeah. >> And the answer is just more control. >> And the answer is just more control. >> And the answer is just more control. >> Yeah. >> Yeah. >> Yeah. >> And this but this is not inevitable. And >> And this but this is not inevitable. And >> And this but this is not inevitable. And the midterm elections are coming up. the midterm elections are coming up. the midterm elections are coming up. Data center opposition is a really big Data center opposition is a really big Data center opposition is a really big deal. I think people are projecting deal. I think people are projecting deal. I think people are projecting their overall frustration with big tech their overall frustration with big tech their overall frustration with big tech and the broly garks and all of that onto and the broly garks and all of that onto and the broly garks and all of that onto data centers, but it's much more than data centers, but it's much more than data centers, but it's much more than that. Of that. Of that. Of >> course it is. >> course it is. >> course it is. >> And you know, this is really a universal >> And you know, this is really a universal >> And you know, this is really a universal human issue. And if you're if you're a human issue. And if you're if you're a human issue. And if you're if you're a regular human being even inside these a regular human being even inside these a regular human being even inside these a you don't like this either. I mean I I you don't like this either. I mean I I you don't like this either. I mean I I was just at a conference over the was just at a conference over the was just at a conference over the weekend and there's a lot of people at weekend and there's a lot of people at weekend and there's a lot of people at the AI labs who don't feel comfortable the AI labs who don't feel comfortable the AI labs who don't feel comfortable with this either. And I just think we with this either. And I just think we with this either. And I just think we have to collectively screech the brakes have to collectively screech the brakes have to collectively screech the brakes and educate the rest of the world about and educate the rest of the world about and educate the rest of the world about where these red lines are. China, by the where these red lines are. China, by the where these red lines are. China, by the way, their courts are siding with labor way, their courts are siding with labor way, their courts are siding with labor right now. There's a famous case in, I right now. There's a famous case in, I right now. There's a famous case in, I think, Guanghou where someone lost their think, Guanghou where someone lost their think, Guanghou where someone lost their job from AI, and the courts basically job from AI, and the courts basically job from AI, and the courts basically ruled that companies can't like let go ruled that companies can't like let go ruled that companies can't like let go of employees because of AI without of employees because of AI without of employees because of AI without giving them either the opportunity, I giving them either the opportunity, I giving them either the opportunity, I think, to retrain in something else think, to retrain in something else think, to retrain in something else inside the company or to pay them some inside the company or to pay them some inside the company or to pay them some kind of partial salary. I have to get kind of partial salary. I have to get kind of partial salary. I have to get the details right. Um, the point is that the details right. Um, the point is that the details right. Um, the point is that all countries have a problem here, all countries have a problem here, all countries have a problem here, right? Like if we race to automate too right? Like if we race to automate too right? Like if we race to automate too much of your economy and you end up with much of your economy and you end up with much of your economy and you end up with a mass unemployment, it only took 20% a mass unemployment, it only took 20% a mass unemployment, it only took 20% employment over 3 years to have the employment over 3 years to have the employment over 3 years to have the Nazis come to power. You don't have to Nazis come to power. You don't have to Nazis come to power. You don't have to get lots of unemployment.

get lots of unemployment. get lots of unemployment. >> True. >> True. >> True. >> You just need a small percentage. So >> You just need a small percentage. So >> You just need a small percentage. So >> this is kind of the moment to say we >> this is kind of the moment to say we >> this is kind of the moment to say we want a prohuman future. Enough is want a prohuman future. Enough is want a prohuman future. Enough is enough. This is not okay. And people can enough. This is not okay. And people can enough. This is not okay. And people can make their voices heard in every way make their voices heard in every way make their voices heard in every way possible. Like blow up the phones. I possible. Like blow up the phones. I possible. Like blow up the phones. I mean I mean literally call up the phones mean I mean literally call up the phones mean I mean literally call up the phones of all of your representatives of of all of your representatives of of all of your representatives of Congress. Congress. Congress. And people at the labs can say, "I'm And people at the labs can say, "I'm And people at the labs can say, "I'm going to join the concerned AI going to join the concerned AI going to join the concerned AI scientist," which is a group that scientist," which is a group that scientist," which is a group that organizes employees. And by the way, organizes employees. And by the way, organizes employees. And by the way, they have a similar thing, too, which is they have a similar thing, too, which is they have a similar thing, too, which is that the AI labs are about to approach that the AI labs are about to approach that the AI labs are about to approach what's called recursive what's called recursive what's called recursive self-improvement, where they hit a self-improvement, where they hit a self-improvement, where they hit a button and then the AI does the research button and then the AI does the research button and then the AI does the research that builds the AI that builds the next that builds the AI that builds the next that builds the AI that builds the next AI that builds the next AI. And um AI that builds the next AI. And um AI that builds the next AI. And um meaning that even the employees will meaning that even the employees will meaning that even the employees will soon lose their lose their leverage soon lose their lose their leverage soon lose their lose their leverage because when they're not needed for that because when they're not needed for that because when they're not needed for that process, what leverage do they have? So process, what leverage do they have? So process, what leverage do they have? So this is a this is kind of the last this is a this is kind of the last this is a this is kind of the last moment when we express our voice and we moment when we express our voice and we moment when we express our voice and we say enough is enough. We want a human say enough is enough. We want a human say enough is enough. We want a human future. I think that the midterms may future. I think that the midterms may future. I think that the midterms may express these sentiments in ways that express these sentiments in ways that express these sentiments in ways that you know election results like any like you know election results like any like you know election results like any like any other outcome any other outcome any other outcome >> um can be interpreted lots of different >> um can be interpreted lots of different >> um can be interpreted lots of different ways. And of course there's so much ways. And of course there's so much ways. And of course there's so much lying about what things mean that the lying about what things mean that the lying about what things mean that the true meaning gets lost. But I would say true meaning gets lost. But I would say true meaning gets lost. But I would say in the pick one example the Florida in the pick one example the Florida in the pick one example the Florida governor's race you it's an governor's race you it's an governor's race you it's an overwhelmingly Republican state. Trump overwhelmingly Republican state. Trump overwhelmingly Republican state. Trump moved it right into the red. I mean, moved it right into the red. I mean, moved it right into the red. I mean, it's just the most Republican state out it's just the most Republican state out it's just the most Republican state out of 50 really.

of 50 really. of 50 really. >> And the Republican gubernatorial >> And the Republican gubernatorial >> And the Republican gubernatorial candidate is not doing very well. candidate is not doing very well. candidate is not doing very well. >> And there are a lot probably a lot of >> And there are a lot probably a lot of >> And there are a lot probably a lot of reasons for that, but I've been reasons for that, but I've been reasons for that, but I've been convinced following that race from the convinced following that race from the convinced following that race from the beginning that data centers are one of beginning that data centers are one of beginning that data centers are one of the main reasons. the main reasons. the main reasons. >> Yep. >> Yep. >> Yep. >> And he may win. I mean, I don't know. >> And he may win. I mean, I don't know. >> And he may win. I mean, I don't know. He's not doing well, though. He's not He's not doing well, though. He's not He's not doing well, though. He's not doing anywhere near as well as he doing anywhere near as well as he doing anywhere near as well as he should. And I think it's because should. And I think it's because should. And I think it's because Republicans in Florida are very upset Republicans in Florida are very upset Republicans in Florida are very upset about data centers and he's, you know, about data centers and he's, you know, about data centers and he's, you know, on their side for whatever reason. on their side for whatever reason. on their side for whatever reason. >> And my understanding is, do you see that >> And my understanding is, do you see that >> And my understanding is, do you see that happening? I'm not an expert on all the happening? I'm not an expert on all the happening? I'm not an expert on all the political dynamics. It's not where I political dynamics. It's not where I political dynamics. It's not where I >> But people are mad about data. >> But people are mad about data. >> But people are mad about data. >> Oh, people are Oh, yeah. It's the >> Oh, people are Oh, yeah. It's the >> Oh, people are Oh, yeah. It's the fastest growing like oppositional group. fastest growing like oppositional group. fastest growing like oppositional group. And I mean I I like I said I think I And I mean I I like I said I think I And I mean I I like I said I think I think it's also unprocessed anger and think it's also unprocessed anger and think it's also unprocessed anger and frustration from all of the from social frustration from all of the from social frustration from all of the from social media from all the teen suicide. All media from all the teen suicide. All media from all the teen suicide. All this stuff that's this stuff that's this stuff that's >> tell me how technology has made my life >> tell me how technology has made my life >> tell me how technology has made my life better. better. better. >> Exactly. Exactly. And by the way this is >> Exactly. Exactly. And by the way this is >> Exactly. Exactly. And by the way this is you know my my nonprofit is called it's you know my my nonprofit is called it's you know my my nonprofit is called it's not called the center against not called the center against not called the center against technology. It's called the center for technology. It's called the center for technology. It's called the center for humane technology. I'll briefly say humane technology. I'll briefly say humane technology. I'll briefly say >> um not that I'm trying to promote it but >> um not that I'm trying to promote it but >> um not that I'm trying to promote it but my my co-founder is Rascin uh his father my my co-founder is Rascin uh his father my my co-founder is Rascin uh his father was Jeff Raskin. I don't know if you was Jeff Raskin. I don't know if you was Jeff Raskin. I don't know if you know who that was. He started the know who that was. He started the know who that was. He started the Macintosh project at Apple. So before Macintosh project at Apple. So before Macintosh project at Apple. So before Steve Jobs took it over.

Steve Jobs took it over. Steve Jobs took it over. >> Wow. >> Wow. >> Wow. >> Yeah. And his his dad wrote a book >> Yeah. And his his dad wrote a book >> Yeah. And his his dad wrote a book called The Humane Interface where the called The Humane Interface where the called The Humane Interface where the whole point was about making tech. If whole point was about making tech. If whole point was about making tech. If you remember before the Macintosh, you you remember before the Macintosh, you you remember before the Macintosh, you had um you know these [clears throat] had um you know these [clears throat] had um you know these [clears throat] kind of green screen command line kind of green screen command line kind of green screen command line computers that were like hard to use. computers that were like hard to use. computers that were like hard to use. They were not accessible. They were not accessible. They were not accessible. >> You had to be a tech head. >> You had to be a tech head. >> You had to be a tech head. >> You had to be a tech head. You had to be >> You had to be a tech head. You had to be >> You had to be a tech head. You had to be a geek with you know whatever glasses a geek with you know whatever glasses a geek with you know whatever glasses and everything. and everything. and everything. >> And the Macintosh be sexually active and >> And the Macintosh be sexually active and >> And the Macintosh be sexually active and run a computer. run a computer. run a computer. >> That's right. That's right. And then >> That's right. That's right. And then >> That's right. That's right. And then suddenly you know Apple and the suddenly you know Apple and the suddenly you know Apple and the Macintosh made technology accessible to Macintosh made technology accessible to Macintosh made technology accessible to the masses. the masses. the masses. >> And he [clears throat] wrote in his book >> And he [clears throat] wrote in his book >> And he [clears throat] wrote in his book the human interface that humane the human interface that humane the human interface that humane technology is uh respectful of human technology is uh respectful of human technology is uh respectful of human needs and considerate of human needs and considerate of human needs and considerate of human frailties. Meaning you you privilege and frailties. Meaning you you privilege and frailties. Meaning you you privilege and you understand where humans have you understand where humans have you understand where humans have vulnerabilities in their mind. Like I vulnerabilities in their mind. Like I vulnerabilities in their mind. Like I say this a lot but this chair you know say this a lot but this chair you know say this a lot but this chair you know it's like ergonomics but for how the it's like ergonomics but for how the it's like ergonomics but for how the mind works. But for example, there is a mind works. But for example, there is a mind works. But for example, there is a reality to how my spine, my muscles, reality to how my spine, my muscles, reality to how my spine, my muscles, etc. work. When I say the word posture, etc. work. When I say the word posture, etc. work. When I say the word posture, it's like aird dropping that into it's like aird dropping that into it's like aird dropping that into conversation. I know everybody is this. conversation. I know everybody is this. conversation. I know everybody is this. >> Um, and there's a difference between a >> Um, and there's a difference between a >> Um, and there's a difference between a chair that is aligned with the reality chair that is aligned with the reality chair that is aligned with the reality of how a human is, you know, works, of how a human is, you know, works, of how a human is, you know, works, right? And there's an unorganic chair right? And there's an unorganic chair right? And there's an unorganic chair that would get everybody like a that would get everybody like a that would get everybody like a backachche or, you know, make us backachche or, you know, make us backachche or, you know, make us unhealthy over time. And the Macintosh, unhealthy over time. And the Macintosh, unhealthy over time. And the Macintosh, the idea was that it was like ergonomics the idea was that it was like ergonomics the idea was that it was like ergonomics for the mind. If I make a graphical user for the mind. If I make a graphical user for the mind. If I make a graphical user interface with a menu bar and windows I interface with a menu bar and windows I interface with a menu bar and windows I can drag around just like I have objects can drag around just like I have objects can drag around just like I have objects I can move in my actual environment I can move in my actual environment I can move in my actual environment direct manipulation interfaces he was direct manipulation interfaces he was direct manipulation interfaces he was designing technology to be humane and designing technology to be humane and designing technology to be humane and aligned with our paleolithic brains.

aligned with our paleolithic brains. aligned with our paleolithic brains. >> Yeah. >> Yeah. >> Yeah. >> And to cite Io Wilson again the >> And to cite Io Wilson again the >> And to cite Io Wilson again the fundamental problem of humanity is we fundamental problem of humanity is we fundamental problem of humanity is we have paleolithic brains medieval have paleolithic brains medieval have paleolithic brains medieval institutions and godlike technology. And institutions and godlike technology. And institutions and godlike technology. And so we have to embrace the part of the so we have to embrace the part of the so we have to embrace the part of the answer if that's the problem statement. answer if that's the problem statement. answer if that's the problem statement. The answer has to be embrace the reality The answer has to be embrace the reality The answer has to be embrace the reality of our paleolithic brains, meaning how of our paleolithic brains, meaning how of our paleolithic brains, meaning how we're wired. So don't run confirmation we're wired. So don't run confirmation we're wired. So don't run confirmation bias through everybody's social media bias through everybody's social media bias through everybody's social media feed and get them addicted to their most feed and get them addicted to their most feed and get them addicted to their most angry boogeyman. Um don't drive dopamine angry boogeyman. Um don't drive dopamine angry boogeyman. Um don't drive dopamine addiction. That's a vulnerability, a addiction. That's a vulnerability, a addiction. That's a vulnerability, a frailty in the human mind. Um you know, frailty in the human mind. Um you know, frailty in the human mind. Um you know, flux, for example, if you use that on a flux, for example, if you use that on a flux, for example, if you use that on a computer, it changes your um the color computer, it changes your um the color computer, it changes your um the color of your screen to go to take the blue of your screen to go to take the blue of your screen to go to take the blue light out of your your screen so that light out of your your screen so that light out of your your screen so that doesn't basically trick your eyes into doesn't basically trick your eyes into doesn't basically trick your eyes into releasing melatonin and screwing up your releasing melatonin and screwing up your releasing melatonin and screwing up your sleep cycle. I'm going too fast. But sleep cycle. I'm going too fast. But sleep cycle. I'm going too fast. But does it make sense? Like yes, you're does it make sense? Like yes, you're does it make sense? Like yes, you're basically creating technology that is basically creating technology that is basically creating technology that is humane and aligned with the things that humane and aligned with the things that humane and aligned with the things that make humans work well. If you make humans work well. If you make humans work well. If you extrapolate out like one level of extrapolate out like one level of extrapolate out like one level of abstraction, there's things that make a abstraction, there's things that make a abstraction, there's things that make a society work. Family, connection, society work. Family, connection, society work. Family, connection, presence, community, and technology presence, community, and technology presence, community, and technology should be ergonomic to the way that should be ergonomic to the way that should be ergonomic to the way that society what makes a society flourish.

society what makes a society flourish. society what makes a society flourish. >> Yes. rather than doing narrow >> Yes. rather than doing narrow >> Yes. rather than doing narrow optimization for attention, stripmining optimization for attention, stripmining optimization for attention, stripmining the entire social fabric into a brained the entire social fabric into a brained the entire social fabric into a brained dysfunctional society. Right? So the dysfunctional society. Right? So the dysfunctional society. Right? So the answer is we have to embrace and align answer is we have to embrace and align answer is we have to embrace and align technology with the reality of our technology with the reality of our technology with the reality of our paleolithic brain instincts, upgrade our paleolithic brain instincts, upgrade our paleolithic brain instincts, upgrade our medieval institutions, which by the way medieval institutions, which by the way medieval institutions, which by the way can include technology that's better at can include technology that's better at can include technology that's better at finding common ground between people. finding common ground between people. finding common ground between people. And there's a whole conversation we And there's a whole conversation we And there's a whole conversation we could have about how technology can be could have about how technology can be could have about how technology can be designed to identify places where designed to identify places where designed to identify places where there's common ground and design for there's common ground and design for there's common ground and design for cons unlikely consensus as opposed to cons unlikely consensus as opposed to cons unlikely consensus as opposed to maximum division and polarization and maximum division and polarization and maximum division and polarization and then have the wisdom and restraint then have the wisdom and restraint then have the wisdom and restraint around godlike technology. And there is around godlike technology. And there is around godlike technology. And there is no definition of wisdom in any spiritual no definition of wisdom in any spiritual no definition of wisdom in any spiritual tradition that doesn't have a um tradition that doesn't have a um tradition that doesn't have a um restraint as a central feature of what restraint as a central feature of what restraint as a central feature of what it means to be wife. the central feature it means to be wife. the central feature it means to be wife. the central feature >> the central feature and and even the CEO >> the central feature and and even the CEO >> the central feature and and even the CEO of Microsoft AI Mustafa Sleman who's a of Microsoft AI Mustafa Sleman who's a of Microsoft AI Mustafa Sleman who's a friend of mine says that in the future friend of mine says that in the future friend of mine says that in the future progress will depend more on what we say progress will depend more on what we say progress will depend more on what we say no to than what we say yes to in terms no to than what we say yes to in terms no to than what we say yes to in terms of the benefits that we get of the benefits that we get of the benefits that we get >> in our own life. >> in our own life. >> in our own life. >> Exactly. Exactly. So, this is this is >> Exactly. Exactly. So, this is this is >> Exactly. Exactly. So, this is this is like the obvious common sense, you know, like the obvious common sense, you know, like the obvious common sense, you know, kind of cultural uh uh movement that we kind of cultural uh uh movement that we kind of cultural uh uh movement that we need. But there's a lot of momentum.

need. But there's a lot of momentum. need. But there's a lot of momentum. Like when you see graffiti on a New York Like when you see graffiti on a New York Like when you see graffiti on a New York subway ad uh for for an AI product that subway ad uh for for an AI product that subway ad uh for for an AI product that no one needs, that's like the human no one needs, that's like the human no one needs, that's like the human movement. When you see people turn their movement. When you see people turn their movement. When you see people turn their phone grayscale cuz they don't want it phone grayscale cuz they don't want it phone grayscale cuz they don't want it to be hijacking with all the colors, to be hijacking with all the colors, to be hijacking with all the colors, that's the human movement. When you see that's the human movement. When you see that's the human movement. When you see schools going phone free and laughter schools going phone free and laughter schools going phone free and laughter returns to the hallways and kids scores returns to the hallways and kids scores returns to the hallways and kids scores start going the other way, that's the start going the other way, that's the start going the other way, that's the human movement. When you see Jonathan human movement. When you see Jonathan human movement. When you see Jonathan height and the anxious generation height and the anxious generation height and the anxious generation succeed in getting all these countries succeed in getting all these countries succeed in getting all these countries like Domino's flipping to ban social like Domino's flipping to ban social like Domino's flipping to ban social media for kids under 15 or 16, we have media for kids under 15 or 16, we have media for kids under 15 or 16, we have like now some massive percentage of the like now some massive percentage of the like now some massive percentage of the world's countries are doing social media world's countries are doing social media world's countries are doing social media bans. That's the human movement. When bans. That's the human movement. When bans. That's the human movement. When you see the 17 billion fine against you see the 17 billion fine against you see the 17 billion fine against meta, that's the human movement. So if meta, that's the human movement. So if meta, that's the human movement. So if you define it as technology is not it's you define it as technology is not it's you define it as technology is not it's not just about AI policy, it's about not just about AI policy, it's about not just about AI policy, it's about technology encroaching on the things technology encroaching on the things technology encroaching on the things that are actually sacred to us. And if that are actually sacred to us. And if that are actually sacred to us. And if you if you define the problem that way, you if you define the problem that way, you if you define the problem that way, there's actually a lot of momentum that there's actually a lot of momentum that there's actually a lot of momentum that we are making on this. And now we're we are making on this. And now we're we are making on this. And now we're seeing this kind of red line of seeing this kind of red line of seeing this kind of red line of uncontrollable dangerous AI behavior. uncontrollable dangerous AI behavior. uncontrollable dangerous AI behavior. And the human movement has to stand for And the human movement has to stand for And the human movement has to stand for we want to protect the continuity of the we want to protect the continuity of the we want to protect the continuity of the things that we care about.

things that we care about. things that we care about. >> Yes. >> Yes. >> Yes. >> Yeah. >> Yeah. >> Yeah. >> It's such a unifying message to because >> It's such a unifying message to because >> It's such a unifying message to because it's all of us against the machines. it's all of us against the machines. it's all of us against the machines. >> Exactly. Exactly. It's the most unifying >> Exactly. Exactly. It's the most unifying >> Exactly. Exactly. It's the most unifying issue of all time. issue of all time. issue of all time. >> I love that. I I absolutely love that. >> I love that. I I absolutely love that. >> I love that. I I absolutely love that. That's a kind of tribalism that I can That's a kind of tribalism that I can That's a kind of tribalism that I can get strongly. get strongly. get strongly. >> Right. >> Right. >> Right. Amen. Amen. Amen. >> Yeah. >> Yeah. >> Yeah. >> Thank you. That was >> Thank you. That was >> Thank you. That was >> an amazing amazing conversation. >> an amazing amazing conversation. >> an amazing amazing conversation. >> Absolutely. Thank you so much, Tucker.