OpenAI Whistleblower FINALLY Speaks: “AI Has A 70% Chance Of Going Horribly Wrong!“

0:00 The scary open secrets in the AI industry right now is that it's possible that we'll end up essentially creating a new species that ends up ruling the world. With a seventy percent chance that this goes horribly wrong like human extinction. That's one possibility. There's many more. Yeah, it's uh It gets me down sometimes. I basically told my wife, like let's not have any more kids, it's too uncertain. I don't think they'll ever join the workforce.

0:24 Everybody should be afraid that their jobs are gonna be lost. And I know this because I went to open AI in twenty twenty two. What I did there was forecasting what the next couple of years might look like. Then unfortunately most of the world is kind of asleep at the wheel and doesn't really realize what's going on with AI. So I resigned. I read it somewhere. You lost two million dollars for not signing an anti disparagement clause, meaning you couldn't criticize the company. Yes, for reasons I'm happy to get into. But the main thing I've learned is that when I go talk to people at Anthropic and OpenAI about forecasting, they're like, It's not gonna take that long. You need to shorten them again. Get him back to twenty twenty seven or twenty twenty eight, because these powerful CEOs Ariel or Sam or Elon are racing you. each other to be in control of the most powerful AIs and are literally afraid that if the other guy gets there first he might become dictator. I mean Anthropica is on track to be the entire economy by twenty thirty. But none of these people should be trusted with that much power. So this is the most important thing happening in our lifetimes, probably in all of history in fact. And it's very important that it go well. So I think that there's a lot we can do to like steer things in a better direction. There's loads of benefits that we could get from AI if we do it right. And if we do solve the problems, then things could be absolutely amazing for everyone. Well this report here in twenty twenty-one, it was remarkably accurate. And then you just published this one. Yeah. So this is on your scenario. So let's go through these slowly and one at a time.

1:39 Guys, I've got a favor to ask before this episode begins. The algorithm, if you follow a show, will deliver you the best episodes from that show very prominently in your feed. So when we have our best episodes on this show The most shared episodes, the most rated episodes. I would love you to know. And a simple way for you to know that is to hit that follow button. But also it's the simple easy free thing that you can do to help us make this show better. And I would be hugely grateful if you could take a minute on the app you're listening to this one right now and hit that follow button. Thank you so, so so much. Uh Daniel Cocotello.

2:16 At the very heart of what you do. Um what is your mission? And why? So what would you do if you thought that superintelligence was coming in a few years? I guess it depends on the other.

2:28 What the consequences Well. Let's talk about it. So Superintelligence. AIs that are better than the best humans at everything, while also being faster and cheaper, also able to

2:39 operate robots that can do everything in the physical world that humans can do, but better, faster, and cheaper. If that really is coming in a few years. Then we need to prepare and we need to think about how to make it go well instead of poorly. So that's sort of my answer is like I'm doing that to the best of my ability. So you believe it's coming in a few years? Yes. How could you be so sure?

2:59 I spend a lot of time trying to forecast this sort of thing. My sort of median estimate, fifty percent chance. It's currently in twenty twenty nine, maybe it'll slip to twenty twenty eight. It's possible that'll take significantly longer, like maybe ten years or something like that. But

3:13 Uh You know, for reasons I'm happy to get into. Seems to me like it's probably happening by the end of the decade. What's less important is the The sense of how close we are?

3:22 What's more important is the Pace of the trends. Anthropic. This time last year was making something like a billion dollars a year. And now they're making something like sixty billion dollars a year.

3:35 So that's Sixty X growth in one year. Which is Extremely impressive even for very small startups. But for a company of their size, it might be the fastest growth in history.

3:47 Um We expect that rate of growth to slow down. But Even if it slows down. Quite a lot.

3:54 They're still on track to be You know. The entire economy by twenty thirty or so. Why should the average person care? For the whole world.

4:06 And including therefore for them and their families. Um Could change for the better, could change for the worse, depending on the details of how it's done. So for example, Everyone could die.

4:15 You know, um this is the classic loss of control. Scenario or one version of it. If we do build these Superintelligences and we Use them to automate all the jobs and

4:26 We put them in the military and we, you know, have them giving advice to politicians and so forth. They will eventually have accumulated enough real world power. that they don't need humans anymore. And they're smarter than us, they're more strategic. Exc.

4:40 At that point we sort of have to hope that they are virtuous, that they have Yeah, the goals that we wanted them to have, the values that we wanted them to have, et cetera. And the sort of scary open secrets in the AI industry right now is that right now that is kind of just a hope. It's not something that we can be at all confident in and in fact there's lots of evidence and arguments that

4:59 it we're not on track to achieve that. So there's lots of reasons like current AIs, for example. Will often lie. Uh to people. Or they were like You tell them to do something and they go do something else and then pretend that they did it, right? So

5:11 It's an inherently difficult problem to make something that's super intelligent and also Has the values and virtues that you want it to have. And it doesn't seem like we're on track to solve that problem. Also, it seems like the sort of problem that you could think you've solved when you haven't actually solved it, right? Uh that's a big reason why this is scary.

5:27 So for all those reasons, it's possible that we'll end up essentially creating A new species? That's Ends up ruling the world instead of us. And then maybe we go the way of other extinct species in the past. They were outcompeted by humans. That's one possibility.

5:41 There's many more. Even if you're not worried about that and you think that the AIs will be totally controlled. There's the question of who controls the AIs. Right. When there's a couple of corporations that have made these superintelligences and are

5:53 Using them to automate all the jobs. Well, that's a lot of power, you know. That's a lot of money. It's a lot of political power. They'll have the best strategists, the best advisors. You know. The they'll think faster. Militarily.

6:05 uh the countries that has these AIs will be able to absolutely wipe the floor with all the other countries. The AIs themselves, it's it's kind of a single point of failure, like central uh control system where You know, the CEO of Anthropic, Dario. He coined this phrase, the country of geniuses in the data data center. That was his Phrase to describe what they're trying to build.

6:26 Yeah. I think that's a little bit misleading. I think it would be more accurate to describe it as army of geniuses in the data center because It's not like it's a bunch of diverse different AIs. You know, living in their different parts of the data center. They're all copies. Of the same thing.

6:41 Big model. And they're owned by the company. And so They follow the orders. given by the company. Right. People should be asking questions of like who controls this army or these armies and what are they going to be doing with them. I think that we could very easily end up in a Sort of.

6:55 Uh a situation where Some tiny group of people are essentially oligarchs or dictators. And Ironically. Both of these risks, the loss of control and the constitution of power.

7:08 Are things that people in the industry have been thinking about for decades. Um even before the AI industry existed. Yeah, people. thinking about AI or talking and writing about these things.

7:18 And then part of the founding narrative or the founding myth. Of deep mind and open AI and anthropic. Is these problems are real. So We need to get there first so that we can handle it.

7:29 Responsibly. Those are I think the big two reasons. But then I can go on. There's lots more reasons as well. So one thing is Yeah, World War Three. Geopolitical conflict. Um if AI does in fact get incredibly powerful.

7:41 That's going to change the balance of power between nations. That's going to disrupt a lot of things. That puts us at increased risk of crisis more generally. Right. Another one. What about those jobs? You're you're gonna lose your taxi job. But not just the taxi driver, everybody.

7:55 Pretty much. Um there might be a few exceptions, like people whose jobs For legal reasons are only allowed to be done by humans? But For the most part.

8:04 Everybody should be afraid that their jobs are gonna be lost, even if we manage to avoid all the other problems. Right. This narrative has started to emerge and I've had several interviews on the show where I've interviewed people who are very, very scared and anxious about AI, and these are people that have worked in the industry for sometimes decades. Yeah. Um the counter narrative coming over the hill is that this is Doomerism. that these people are, for whatever reason, just trying to scare people and that they don't really understand what they're talking about. How do you respond to that sort of counter narrative? And you must have seen this emerging yourself, especially from People who stand to benefit, dare I say.

8:35 Yeah, exactly. This counter narrative. Is fairly recent and it's been pushed by the people who stand to benefit. Um From it.

8:42 And it's not true. Like these These concerns have been around for decades since before the AI industry existed. They're actually pretty reasonable concerns. Like if you take the companies at their word and imagine that they are in fact going to build superintelligence. Well, it raises a lot of questions like who's gonna control it? Will anybody control it? What about the jobs?

9:02 Implications to be thinking about and worrying about. Who are you and what's your story? My name is Dion Cocatello. Um I currently run the AI Futures project, which is a small nonprofit.

9:13 That's Mostly focuses on forecasting the future. Okay. Before that I worked at Open AI?

9:20 AI forecasting. Yeah, so Think about how like You know, industry analysts who work for hedge funds and stuff will make these forecasts of like Here's you know, how many cars Tesla will be s selling five years from now. Or like

9:35 Here's what the price of electricity will be. In two years, right? That's forecasting. I was doing that, but specifically focused on AI. The reason I was doing it is because it's incredibly important to

9:45 To see where this is all headed. Why did you go to OpenAI? What did you do there? What did you observe? while you were there and how did it change your perspective on the future of AI, but also I guess OpenAI as a company. And for anybody that doesn't know, OpenAI are the company that produce chat GPT.

10:01 Yeah, so I went to Open AI in twenty twenty two. Uh a large part of what I did there was more forecasting. Yeah, Twenty Twenty Seven is a scenario that you may have heard of. I did like smaller You know lower effort versions of them internally for just internal circulation of like here's some guesses as to what the next couple of years might look like. I also worked on evaluations for dangerous capabilities. So Yeah, trying to measure the AI's cyber abilities or persuasion abilities or situational awareness.

10:27 And I also briefly was on a uh a capabilities team doing reinforcement learning to create agents. AI is in fact getting Uh a lot better. And I can ex say more about why, you know, scaling laws.

10:40 Um Deep neural nets bigger, trained on more data. become more efficient, more competent at those things. I also

10:49 A bit more disillusioned with the AI industry. So OpenAI, Enthropic, and DeepMind all had these sort of founding narratives of like, yes, these risks are real, but We've thought about them and we're going to try to handle them responsibly. And that's why it's important for us to Keep doing what we're doing. And

11:06 I increasingly came to think that these were rationalizations. To justify what they were doing, rather than sort of like deeply guiding their actual behavior and that when push comes to shove. They follow their incentives. Rather than

11:21 Do what's actually good. So you're inside OpenAI at the time. And you start to s believe that the following commercial incentives versus the I guess social inc or societal incentives that they founded themselves on. Sort of. I mean would I wouldn't actually describe it as commercial incentives. I think I would describe it as

11:38 Um Power seeking incentives. So Like it's true that The companies care a lot about making a lot of money. But especially at the very top of these companies.

11:48 Like the leaders. They understand that this is about more than just money. You know? There are these emails that came up in you know the the lawsuit between Musk And

11:58 And um open AI. A bunch of emails were surfaced in that last week, which you can go read. And And some of them. the founders of OpenAI were talking back in like twenty seventeen about how the reason why we made OpenAI It was because we were worried.

12:12 That's the Demis the side is that Google was gonna become dictator. With A GI. Even back then they were. This is obviously about more than just money.

12:19 Like these these powerful CEOs are Literally afraid that If the other guy gets there first, he might become dictator. And they Don't trust each other.

12:30 They are racing as hard as they can so that they're the ones who get there first, so to speak. Have you met Sam Altman? Yeah. And uh did did that shape your opinion of his incentives or wh why he's doing what he's doing?'Cause there's a lot, you know, speculated about what his incentives are. I mean his most recent narrative says uh

12:47 For the good of humanity. I think that's what I'm doing. Yeah. I mean, I think the main thing I've learned is don't pay attention to the nerds. You know, like uh What they say to one person is just different from what they can say to some other person at the same time, and what they say in public is a third thing entirely. I think you should judge people by their actions, not by their words. And why are you no longer open AI? Largely for the reason that I mentioned. So I became gradually disillusioned with how the company was going to behave.

13:12 For example When I first joined in twenty twenty two At least to the people I talked to, my colleagues at the company, there was this general sense of like, of course We went actually just build superintelligence as soon as possible. Once we started getting really close, like once we started getting to AIs that could

13:28 Maybe automate the AI research process. We would pause. And figure out how to make it safe. That's'cause we're the good guys and that's obviously the safe thing you should do rather than just going Full speed ahead.

13:39 But We're worried about other people who might not pause, you know, our competitors. Google, for example. And so that's why We need to be in the lead so that we have that room. to do the safe stuff, right?

13:50 That was sort of like a thing that seemed like Maybe like the median position or something among the colleagues I talked to when I was there when I started. Including people like Sam, you know. including the leadership.

14:01 And then by the time I left, I was like, Oh man, they're really not gonna do that, are they? Like Like they they've sort of. You know, partly because this has become more politicized and they've Become bigger and but under more scrutiny. People have started asking, like, why are you doing this in the first place if it's so risky? And so they're pivoted their narrative to being more like, Actually it's not that risky, you know?

14:19 Um And so yeah, I mean it seems like they're just going to keep going. Roughly as fast as they can and hope that they can figure it out on the way. How did your time at OpenAI come to an end? Uh I resigned. In twenty twenty four.

14:32 Had a nice goodbye party. What were the reasons you gave for quitting Open AI? I thought that we were rationalizing too much and that we needed to think more about what would actually be good for the world. Um I want it more. Freedom to publish.

14:45 So I'd open the eye as it became a bigger company. It became more of a normal tech company with incentives and you know a PR department and things like that.

14:55 And so it started becoming more difficult to Um To publish the sort of research that I was doing. For example, those scenarios that I mentioned. Couldn't uh couldn't publish those. Right.

15:05 They're just for internal use. I thought that that was a shame because Right now. Most of the world is kind of asleep at the wheel and doesn't really realize what's going on with AI and doesn't really realize what's coming in the pipeline a couple of years from now. And

15:18 the companies aren't really incentivized to tell people that much about it. I mean They say some vague stuff. In a sort of hypey way. But Um Yeah, well they didn't want me to publish the scenario, for example, laying out like here's

15:32 How things might actually look. I'm just I'm super curious as to what it's like being in a company like that when They you know, chat GPT three is released. You were there at that time, right? Mm-hmm. Um, which was a moment where I think the whole world stood up and realised that this technology was

15:46 Powerful. Yeah. Um and the conversation really began from a Society level. Um Company starts growing super quickly. Yeah.

15:54 Quicker than I think anybody could ever have imagined. And Wha what was it like inside there? What did you see change? Um over over that period of time. I remember one all hands meeting where Ilya said something like

16:05 Ilya being. Who was um head of research at that time. He said something like, Okay, now the world is starting to pay attention. Each of you is gonna be the most popular person at every party. Uh

16:16 For the next year. Don't let it get to your head. Focus on the mission. Gotta build AGI. The company grew a lot. It already wasn't really feeling like a nonprofit when I joined. But it definitely didn't feel like a nonprofit by the time I left. Um lots of new people came in.

16:32 Ironically the like Amount of conversation about Super intelligence. And the implications of superintelligence. Arguably you sort of went down.

16:43 Over time. Due to this growth, right. So because we the company would like double and then double again and then double again. All these new people were coming in from other parts of the tech industry who hadn't really been thinking about these things and were attracted by the high salaries. You lost two million dollars

16:58 for not signing an anti disparagement clause Which would mean you could speak You couldn't criticize the company. Uh yes. Well s I got to keep the money.

17:10 After I had left. Said my goodbyes, et cetera. Um I got the the exit paperwork. And it included this clause that said you basically have to agree not to criticize the company again. Um and also a clause saying you can't tell anyone about this.

17:23 And so I thought that was kind of Rich coming from a nonprofit that's supposed to be. You know, for the benefit of all humanity. So I didn't sign it. And

17:34 If you don't sign, you don't get to keep your equity. So Your compensation, you know, what what they pay you is a bunch of money. And then also a bunch of Stock, basically. But then they had this stuff in the contract that They get to yank back here.

17:48 Your stock. If you don't sign this thing. Um You know we're

17:55 Uh upset about this. We talked about it for like a month or two. consulted some lawyers, um, and then ultimately decided to just refuse to sign. Where mean you lost you would have lost two million dollars. That's right. Which was like eighty percent of our net worth at the time.

18:09 Um Fortunately. Uh it didn't go the way we expected. It blew up. Basically on the internet. Like when people heard that that we had done this and that we had

18:18 Said no. It became like this huge scandal. Employees at the company started like asking questions in Slack and like Asking leadership, like, wait, what? Like, why are you gonna take away our equity? What is this? You know, because a lot of people hadn't really noticed. This before it had been whispered about, but it hadn't been sort of like A thing that most employees knew about.

18:37 Um and so they back tracked and they said, Never mind, never mind, we'll change the paperwork, you can keep the equity. It's fine. And Sam Altman came out and said he was embarrassed that he didn't realise. Yeah, he had no idea, apparently. You don't believe him.

18:49 No. I think you probably know. And if he didn't know then people close to him probably did, such as his head lawyer. Why did you decide not to take the two million dollars I mean

19:00 Most people would have, I think. It's true, most people would have and most people did. And you know, money is nice. But like It's not the only thing.

19:09 You know? Sometimes it's good to take a stand on principle. I I keep mentioning superintelligence. Perhaps I should say more about like The The sequence of events that the companies are planning to do.

19:20 So Right now. They're focusing on automate encoding. They're taking their AIs. They're making them bigger. They're training them for longer. And

19:28 They're especially focusing the training. on getting them to be good at autonomously writing And editing code. Because uh that will help the companies go faster. Right. If they can automate the code, then they can do their own work.

19:41 Better and faster. And accelerate progress. The next step, which they've already begun. Is to look at the rest of the research process as well. Coming up with ideas Um analyzing experiments, communicating those results.

19:55 All the other parts of of the research process, they're trying to figure out how to train AIs to be good at those as well. So that they can have AIs do the entire thing autonomously. When you say do the entire thing. What you mean? Do the entire thing.

20:07 So like Anthropic and Open Air in particular. are trying to automate themselves. Like they're trying to make it the case that Um they don't really need human employees anymore. Uh they just have A giant army of AIs. That's

20:20 Turning away. doing all this autonomous research to make better AIs, to train the new AIs. Put them in charge. So they can make even better AIs and so forth. And of course not just

20:31 Not all just happening internally, but also like interfacing with the world, right? Like going out and talking to people, collecting the data. Setting up the training environments. doing the business deals and so forth. Like they're they're trying to Automate all of that. The reason why they're doing this is because they're trying to

20:46 Get to a position where they have AI that are Superhuman. At everything? Superintelligence?

20:53 And they're trying to get there before their competitors do. Needless to say, this is incredibly dangerous, I would say. You know? And in addition to being dangerous, It's a power grab.

21:03 Right? Like if they actually succeed at this. Then They'll be sitting on top of this army of Superhuman AIs. That will give them

21:11 Immense leverage over All sorts of other actors in the economy. Insofar as they can work out something with the presidents and you know integrate it into the military or whatever. Then that would give the US immense hard power over all other countries, right?

21:24 Obviously nobody knows exactly when this is happening. But a very disquieting thing has happened over the last year. To me. Which is that when we published it in twenty twenty seven. People were generally of the opinion that my timelines were too short.

21:39 And that like probably it would take more than twenty twenty seven. Until we got to The sort of events that I was just mentioning, you know? Recursive self improvement AI is automating the whole research process. Superintelligence.

21:52 These these types of milestones Um They happen in twenty twenty seven in yeah, twenty twenty seven. Which is this research paper you published. That's right. It's it's a scenario forecast that sort of lays out. Like month by month.

22:04 A possible future trajectory. There was sort of like At the time that we started writing, it was my best guess as to what would actually happen. Obviously there's lots of uncertainty, but you know, I I I thought it's valuable to make a concrete guess just to sort of see what it might look like. And at the time we were writing this, a lot of my friends in the AI industry and in nonprofits and so forth that work on AI. A lot of people were saying like

22:25 Yeah, that stuff's gonna happen, but like it'll probably take a couple years longer. Than you think. And now It's more fifty fifty. Especially when I go talk to people at Anthropic and OpenAI.

22:38 They're often like Yeah, no, twenty twenty seven, that's basically what's gonna happen. Just like you wrote. Why did you why did you become Why did you update your timelines? Oh yeah, c context for this is um

22:50 After After writing it in twenty twenty seven. I shifted my timelines to be a little bit more conservative, so at the time that we published My fifty percent mark was in twenty twenty eight, not in twenty twenty seven. And then after we published.

23:02 Progress just seemed like it was going a bit slower. And so I updated to twenty thirty. Which is yeah, still could happen sooner, could happen later. twenty thirty. Um But now.

23:12 When I talk to people in in the companies, they're like It's not gonna take that long. They're like oh You need to shorten them again. Like Get him back to twenty twenty seven or twenty twenty eight, you know.

23:22 Um so that's a bit disquieting. Um Again, don't know how long it's gonna take, but this is The stated plans of the AI companies is to do this incredibly dangerous thing, and they think that they're just a few years away. So you wrote this um report here, what twenty twenty six looks like and you wrote this in twenty twenty one and it was remarkably accurate. Helped make a name for yourself. Amongst um

23:45 Amongst e everybody in AI. And I which one was it that JD Vance, the Vice President, read? I think it was this one, wasn't it? Yeah, this one. Um then so then you published this one, AI twenty twenty seven, and this was published, I believe, in twenty twenty five. Uh yes, that's right, April. What were you forecasting in here? What are the key things that you said in here for people that haven't read? The high level version of it is They automate the coding.

24:07 Then they automate the rest of the research process. Then the pace of progress accelerates dramatically. They get to superintelligence. They're working with the government who Specifically the president of the executive branch naturally wants To control this technology and otherwise wants to use it to beat China and integrate into military and so forth.

24:23 By this point it's sort of Doing basically all the work itself. I mean it's It's super intelligent. So It's coming up with all these great ideas for how to integrate itself into everything and all these new technologies it's invented and so forth. And uh because of the race dynamics and because of the profit motive, they end up deploying it everywhere.

24:39 And it builds robot factories that build more robots that build more robot factories, et cetera. Transforms the world entirely. And then at some point it has enough power It meaning the AIs have enough power that they don't have to pretend So

24:53 To be aligned anymore. Right. Um then they Stop listening to orders. That's the Race ending.

25:02 Vaya twenty twenty seven. We also wrote a sort of different branch. Which is the slowdown ending? Which was intended to sort of illustrate The concentration of power issues.

25:12 Um that I mentioned previously. So What if hypothetically The alignment issues get sorted out. Sufficiently quickly. Like what if it turns out that like It's not too hard. With two months of s slowdown we can figure out how to make the AIs.

25:25 Robustly do what we want. um and have the values that we want them to have. So that's one possible branch. And in that branch Uh it looks pretty similar, you know. They take the jobs Be China, et cetera. Um

25:38 But Instead of the yeah is ultimately killing everyone. They create this sort of amazing utopia. But the amazing utopia is Whatever the people who control the AIs wanted it to be.

25:49 Right. And so that would be a very small group of people, like the presidents. Some CEOs. Excellent. There should be a button just down below here. And if it says subscribed, you're already subscribed. If it says subscribe but, that means you're not yet. And if you're not subscribed, please could you do us a favor and hit that button. It helps the show more than you know. And according to the algorithm, you're someone that watches our show, but you haven't yet hit that button. Thank you so much.

26:13 Is there any possibility, do you think, that we never get to this thing called AGI? And and and how do we just Distinguish AGI from this term superintelligence. What's the difference? Yeah. So the difference is that AGI is a more vague Uh and weak term. Oh, superintelligence is a bit more precisely defined. It's better than the best humans at everything. Faster and cheaper.

26:31 Um A GI is more like it stands for artificial general intelligence, which means AI is that can do things in general rather than like some specific task. Yeah. And so arguably we've already achieved HEI, right? If you use cloud code or something like that, it's like it can do a lot of stuff. It's it's almost kind of like a little employee that you can like have go do stuff. So it's it is quite general. It's not maximally general though. Can't do everything. Whereas superintelligence by definition Can do all the things that a human can do, but better.

26:57 And how does this sort of overlap with robotics? Because obviously that we're seeing this huge robotics boom at the moment. There are some real world things that humans can still do because these AIs are still stuck on my computer. The way that people talk about this is that they Basically just say we've achieved superintelligence for cognitive tasks. Then you can talk about like

27:15 Full superintelligence that can do the physical stuff. And are we gonna get there? Are we gonna get there with both? I think so. I mean, again, this is not something that we can be certain about. Um you asked like, is it possible we'll never get there? Yes, it's possible we'll never get there. I don't think it's likely though. I think that

27:30 There's nothing sort of like magical about the human brain. It's You know. Um It's just a bunch of neurons. It is possible for a digital system. Two.

27:39 Do similar functions in the same way that like You know, a a plane can fly. Just like a bird. Not in the same way as a bird, necessarily. Like it doesn't have It's not flying in the same way that a bird flies, but it flies, you know. Um so so it does seem like yeah, like

27:55 Seems possible. You've written all these you know these research reports. You're working on another one that will be released um likely on The ninth of July. You have worked inside OpenAI. You then quit Open AI because you were concerned about what was going on there and about the future of the industry. You know more than I do. Are you

28:13 Optimistic about the future or pessimistic? Are we heading to a bad place if things don't change? Um based on everything that you know. I think we are headed to a bad place if things don't change. Um I'm not confident in that.

28:25 I would say something like seventy percent. It's very, very hard to predict, of course. But yeah, it seems like the current default path is heading towards a very, very scary place. How do you contend with that personally and emotionally? Um It's rough. I mean I think it It's the sort of thing that like

28:41 Gets me down. On a regular basis, but also I've been dealing with this for so many years now that I've sort of used to it. If that makes sense. Um

28:55 Yeah. Yeah, I I'll put it this way. I would be incredibly happy If all my predictions turn out to be wrong. And Uh and yeah, hit the wall. For example, it gets you down on a regular basis.

29:05 I used to be known as a pretty chipper and optimistic person. But Um in twenty twenty. My AI timelines predictions started collapsing. Due to GPT three.

29:16 And the scaling laws papers and um the bio anchors report, which I I can talk about if you're interested. But basically Some events happened in twenty twenty that convinced me that actually this stuff was like Quite plausibly coming by the end of the decade. And humanity is very obviously not ready for this, you know, in a whole bunch of different ways.

29:34 And so that's obviously very scary. And that's a extremely scary world because of all things you've said, but but again, because of this recursive self improvement where AIs can train themselves. And at such point we're starting to lose hold of what's going on here. It's more like Closing the entire research loop. Okay, so doing everything. Yeah. Like right right now, a lot of the training data is generated by AIs. A lot of the reinforcement, like the grading. that happens doling out of positive and negative reinforcement is itself done by AIs. Can you explain that in layman's terms for Yeah. So an important thing for everybody to understand is that

30:08 Modern AI systems are not software in a normal sense. I mean they are technically software, but They're not lines of code. You know, it's not like some Engineers at Anthropic.

30:19 Went That's the thing. Basically says like You know, when the user asks for this type of thing. Then go do this type of thing for this many steps or whatever. There's nothing like that. Instead it's a neurnet, you know? What's that?

30:33 Well, Think about how the brain is a bunch of neurons connected to each other. Yeah. That are firing. Um signals back and forth. The brain learns over time. The types of

30:43 Patterns of firing that Caused. success that caused a dopamine rush or various other types of feedback get reinforced. And fire more often. And the types of patterns that caused failure, like touching a hot stove.

30:56 Get anti reinforced to get You know. Um destroyed so that they fire less often. And as a result of all that You over the course of years.

31:05 Learn. To acts in the world. And you learn all sorts of skills and you learn world models. Do you learn like beliefs about the world and you can sort of like mentally simulate how it's going and stuff like that. So artificial neuralets are like that, except artificial. So it's it starts off as a giant

31:22 Tangled spaghetti mess of randomly generated Uh Artificial Connections. Yeah.

31:30 These days they might be something like ten trillion. Parameters Uh it in the biggest AIs. So it starts off randomly generated. So it's of course completely useless. Like if you Give it some input, it'll just produce gibberish as an output.

31:44 But then they train it. And they Start with pre training, which is where You Give it a bunch of internet text.

31:52 And you show it the first piece of text? And you put that in as the input? And then it gives a gibberish output. And then You

31:59 Positively or negatively reinforced it based on how accurate. that output was at predicting the next piece of text. Um so it's basically playing this game of like predict the next word. Isn't that how it happens with babies? I had a I think I had a neuroscientist tell me that babies have more neural connections um than adults. And yeah, it says toddlers have twice as many neural connections

32:20 As adults. And they I guess they whittle down through reinforcement. Yep. We have more pathways when we're younger. And just like the process of training in AI, we're trained down to like remove the ones that aren't useful and build up on the ones that are. Yeah. It's both pruning and strengthening. Okay. And it seems like in humans it's actually more pruning than strengthening, but it's both Uh and an AI is the same thing. It's both. So the first portion of training is where they train the AI to predict text.

32:45 Which is kind of like turning it to read. Um and it's a similar thing does happen in humans. So basically the the random tangle gradually takes shape and gradually sort of coalesces into more useful circuitry. That's

32:59 has stored lots of facts about the world and has stored lots of skills for how to Yeah, process. information and transform it and then produce Predictions. That's just the first step. After they do the pre training, then they

33:13 Try to teach it more useful skills. Besides just predicting text. You know, by the end of the process they've thrown lots of coding problems at it. And they've said, like, here's a coding problem. Go. Here's a coding problem. Here's an environment. You have access to this virtual computer.

33:28 Here's like the code base you're working with. You can write code, you can edit the code, you can run the code, you can read it, you can use the internet. Go, go, go. And it does that for a while. And then based on how successful it is. Reinforcement happens and they have Thousands, maybe millions. of examples of coding problems like that that they trained it on.

33:47 And that's why they're so good at coding now. So what does superintelligence look like in this regard? Is it just more of these connections and how would they get more connections? Can you explain that to me like I'm So There's different AI models, right? So there's like

34:00 GPT three, and GPT four, GPT four point five, and GPT five, and GPT five point five, and five point six, right? Sometimes they're just the same previous model, but with extra training. Sometimes there are a whole new model that's been trained from scratch. Including starting the whole Pre-training process again. Over the last couple years.

34:18 They've done several new rounds of starting over from scratch. And typically when they start over from scratch, they Make the whole thing bigger. the the artificial brain much bigger. Okay. Right now they're at something like ten trillion parameters. Back in twenty twenty, um

34:31 It was more like Hundred seventy five billion. So we've grown like two orders of magnitude. Uh in six years. Two orders of magnitude. Yeah, like two ten X's. So a hundred X. Yeah.

34:43 So That process is continuing. Um They're also improving the algorithms themselves. So they're not literally just the same type of AI, but bigger. They've also come up with all sorts of ideas for how to change

34:55 The structure. Of the of the connections and the neurons and so forth and change the like reinforcement. algorithms that they're using and to change the training data. That they're training on the

35:06 All sorts of Tweaks that have made this whole thing more efficient. Basically, yeah. As they make more brains, they're getting better at making they're making them bigger and Making them more efficient and so forth. And it's literally modelled on the brain.

35:18 Like the way it works, right? It's it's certainly heavily inspired by the brain, but I I shouldn't overstate the the analogy. Like there's lots of differences too. So for example The transformer architecture. Um which is which is the architecture that they use for for these LMs. Uh is not really recurrent. So The information sort of flows.

35:36 one way rather than allowing all these sort of little loops on the inside. Also the the back propagation algorithm is different from the sort of Um learning that naturally happens. So there are some differences, but yes, like broadly speaking. Uh we are sort of making artificial brains. It's kind of like for brains, what like a plane is for A bird.

35:54 Mm. Yeah, that's a really good analogy. That that analogy helped me think through a bunch of questions people often ask about AI when they said, Can it be creative? But actually that analogy kind of helps me understand that actually that maybe that's not the question. It's

36:08 Can it produce something that you would consider to be creative? Because creativity is people think of it as like a process. Yeah. But actually it's it's judged based on the output, isn't it? I mean you you can get philosophical about like is it truly creativity that they have? But you can also be like, Well, I mean, just look at all the stuff they're accomplishing. You know? And uh it seems like they're gonna be accomplishing a lot more. In the near future. Yeah, I do I I asked the question about how this weighs on you personally because I can

36:32 I can sense that you're actually personally bothered. I mean the I think the situation is crazy. Like First of all, it's very exciting. Like AI is really fascinating and interesting stuff. I've been following the field for more than a decade now. Um I've been part of it.

36:46 Uh for some years. And um It's really cool, really interesting. And it's really Fun to think about. what's going on inside these artificial brains and why they are the way that they are. And it's really cool to see all the applications of this technology out in the world. But

37:02 It really seems like we're on a pretty scary path. And the more you think about it, the more worried you get. And You know, in stories. It always ends well, but this is real life. And

37:13 I I think we have to sort of There's a reality in the face and tell it and realize that like It might not actually end well. You know?

37:21 Were there any recent dare I say I was gonna say Eureka moments, but paradigm shifting moments where even your own sort of mental model of what's going on here and how this is gonna look. We're changed for better or for worse. For better or for worse, and probably for worse, things are kind of on track for A twenty twenty seven. There are a few things that have been

37:39 Different not exactly like paradigm shift differences, but like there have been some differences from what we expected at the time we wrote this. So The government has actually gotten involved faster than we expected and has been more aggressive than we expected. So the export controls on Mythos being uh the biggest example and also threatening Anthropic with uh being destroyed by the Defense Production Production Act. Um Another thing that's been surprising to us is that Anthropic in particular has gone from second place to first place.

38:07 In the race? Basically. Why do you think that happened? Because it seemed like Chat G V T were out front and clear as it release relates to open AI were out front and clear, but suddenly anthropic of uh

38:18 Lap them. Yeah, I mean I guess they have um Probably higher talent density. Um and better strategy. But

38:27 Not by a lot, but enough to make the difference. Why do you think they have more talent? Well, They don't have more compute. Like th what are the inputs, right? Like they're in the lead now. They used to be behind. What are the possible explanations for this?

38:40 Well, it could have been that they had more resources, like more computer, more money, but that's not true. They have less resources and less money. Right. So then I guess talents is is the next best al alternative. You could maybe say strategy. Focus. Some combination of those things. Yeah. Something that wasn't just like the amount of resources they had. Just like John Jones, where marginal improvements in your cognitive performance can have a massive impact. Sometimes I podcast for ten hours a day. Over the last couple of weeks, I've been in filming for a TV show, and then I have like one or two days off to get all of my work done, which means there's lots of cognitive load. And so I turn to ketones because I find myself more articulate.

39:16 able to think more clearly, able to work out better when I'm fueled by ketones. And so the reason I became a co-owner of this company and the reason why they now are a sponsor of this podcast is because I remember one of my team members called Christiana, she tried it once and came up to my desk and she goes, This is the best product ever made. And I think in part that's because she really cares about those cognitive benefits, as I do, as John Jones does, and as I think most of my listeners probably will. So if you haven't tried these yet, all you have to do is go to ketone.com/slash Steven, and you'll also get thirty percent off your first subscription order. You'll get exclusive Keetone IQ merch and of course Cognitive benefits that might just change your life. Much of the reason most people haven't posted content or built their personal brand is because

39:59 It's hard and it's time consuming, and we're all very, very busy. And if you've never posted something before There's so many factors in your psychology that stop you wanting to post. What people will think of you. Am I doing this right? Is the thing I'm saying absolutely stupid? All of these result in paralysis, which means you don't post and your feed goes bare. I'm an investor in a company called Stan Store, which you've probably heard me talk about. And what they've been building is this new tool called Stanley that uses AI, looks at your feed, looks at your tone of voice, looks at your history, looks at your best performing posts, and tells you what you should post makes those posts for you. You can also just use it for inspiration. And sometimes what we need when we're thinking about doing a post for our social media channels is inspiration. Building an audience has fundamentally changed my life. And I think it could change yours too. So I'm inviting you to give this new tool a shot.

40:49 And let me know what you think. All you have to do is search coach.stan.store now to get started. Uh a friend of mine who knows some of these people sat me down once upon a time in London. He's actually said this a few times to me, but I remember one particular conversation where he says That Some of these AI COs predict the probability of extinction at being I think he said seven percent. I don't know why I have that number in my head, but I remember it being less than ten percent. And the point he was making to me

41:17 Was that even if it was one percent, like if there was a hundred buttons on this table now. Yeah. And one of them would end the world. Would I dare any of them. Um No. I wouldn't press any of them.

41:30 But he made the case to me that these AI COs are very smart and they understand super intelligence and that they think actually if there was a hundred buttons on this table right now Maybe ten of them. Can end the world. I've heard you say, I think it was on the the the daily show, the interview you did, you said that you think there's a seventy percent chance of human extinction due to AI. I wouldn't say human extinction exactly. I would say something like seventy percent chance that this goes horribly wrong, like human extinction, but that's just one of several possibilities. But yeah, basically. Like for example

41:56 Possibly the AIs take over. And then Don't actually kill everyone. You know? Maybe they do something else. Like just because they've taken over doesn't mean they're des definitely gonna kill us, right? They might, but they could do something else. So that's what that's just that's why I don't usually say like

42:10 Seventy percent chance of like actual human extinction. But seventy percent chance of like Something like AI is taking over some some sort of very big catastrophe like that. That could lead to humanists. I guess I've got two points there, which is You've been around these CEOs. I mean you've worked for Sam Altman at Open AI before you quit. Do you think that they think there's a chance of human extinction? Yes.

42:30 But I think that a important thing to understand is that Like people sort of believe what they need to believe in order to think that they're good people and that

42:39 They need to keep doing what they're doing. This is what rationalization is. And so I think that the tech CEOs have like genuinely convinced themselves That like Probably things are gonna be fine.

42:50 And that the way to make things fine is for them to keep doing what they're doing. And like they need to like make sure that Like, you know, Sam needs to make Sam's probably thinking like Can't let Dario or Elon get there first. You know, I know Dario's thinking Sam can't get there first. Elon's thinking that like You know, they they they've all probably convinced themselves that like, Oh yeah, like maybe it'll go horribly wrong, but like

43:09 Probably it's gonna be fine and probably You know. I should be the one. In charge. It appears to me that anthropic are the only ones that are talking about the potential chance of extinction or a catastrophic event or

43:22 um the down the real downside still. They seem to be the only ones that are still publishing on it. And now they're actually becoming the enemy in many respects of the the tech industry in San Francisco. I'm watching a lot of interviews and it's everyone's attacking Dario because he's saying, listen, things could go bad. They're calling him a Duma Uh and questioning his incentives, even with Mythos, which is a an a a clawed model that they started to warn the world about Again, he is attacked immediately for saying that. Yeah.

43:47 My question is, do you see him as being slightly different from Sam in this regard? Yeah, I mean it seems like Anthropic and Stereo have been more willing to Say and do things that are costly to the bottom line. Uh in at least in the last year or so. That's an example of it. Um, like I don't think that really wins them favors in the administration or among their

44:09 investors to say that type of thing. And You know, m a better example is just the whole fight between the Department of War and Anthropic was an example of them doing something that like cost them a lot of money and even more importantly cost them a lot of power. For

44:23 Something like like they could have just signed. A contract, you know. That said. I really don't want to be in a situation where we're like Which CEO is the least bad CEO. Let's support that one.

44:33 You know, like none of these people should be trusted. Uh with that much power. Basically. Nobody should. Nobody should. Regardless. Regardless. Yeah. Mm-hmm. So uh on this point of the buttons, y you you you do believe that they think there's a

44:45 Yeah, but they've convinced themselves that like It's probably fine. And also it'll be even worse if I'm not doing it, you know? Like that that's what they'll say inside the companies too. Like the people will be like, Okay Well if we stop. What about the other guys? Like they're not gonna stop.

45:00 You know? Yeah, this is this has always been why I've had this outstanding question, which is how does this not go bad when human incentives seem to rule the day when you look at history? And all of the human incentives are saying, Well, if you you're damned if you do I you're damned if you carry on developing these bigger and big and bigger AI brains. But you're also then

45:17 damned if you don't from an a geographical perspective,'cause the United States will lose to that country or this company will lose to that company. So when you just look at human incentives and goes how does how does if just you purely incentives and disincentives, how does this end? Well it carries on going. Seems like it. I mean there there is a caveat to that, which is a hopeful caveat. Which is that First of all, if the world wakes up to all of this Then there can be a more serious conversation about regulation.

45:41 And International treaties and things like that. And that can change the incentives, right? So The government could come in and say, like, actually Here's some rules that you all have to follow. And because they're rules that you all have to follow

45:54 Then you're not incentivized. To like break them anymore because you get punished if you break them and Everyone else is also following them too, and so you know, it's fine. So so there is that sort of like ray of hope that like

46:06 We can change the incentives. If the government and especially the US government, but then later other countries. act to to change the incentives. That's not going to happen until people sort of wake up to all of this.

46:18 The second thing is that even individually At some point. You know, Dario or Sam or Elon might realize that like Actually it's like not even in their own interest. To to keep racing unilaterally.

46:32 And it well and the the problem with that is it's only if it gets extremely obvious and extremely dire. So like In in AI twenty twenty seven, in that scenario. There's this choice point that I mentioned. And in one case the airs are misaligned, in the other case the airs are aligned. At that choice point. We have like one branch that depicts the the misalignment ending and one branch that depicts like the they slow down a bit and solve the alignment issues.

46:55 Instigator for that choice point is they see some evidence that their AI might be. Misaligned and plotting against them. Right. So if you actually see that evidence. Then it's like Oh gosh, uh

47:06 Maybe we shouldn't. Put it in charge of everything and let it Rip, you know. Because that's evidence is staring us right in the face that it's that's untrustworthy. You know?

47:15 But if they don't see that sort of very clear evidence Then I think they're gonna convince themselves that they need to keep going. You know, but maybe they will see very clevance like that. In which case Even if we don't have regulation, they might just sort of voluntarily stop.

47:28 Um So that's the second ray of hope. Like overall I don't think that we're like definitely doomed, you know. Like I said seventy percent, but like I could see it working out pretty well as well. Hm.

47:40 What about uh jobs? Yeah. So I think I think I'm excited to at some point get into The new thing, which is the more optimistic positive vision. Uh and that will have a lot to say about this.

47:53 Because in the in the in the prediction. Yeah, twenty twenty seven. By the time everyone loses their jobs there are worse things happening. Or like it's it's kind of like too late by that point. Um but yes, like once

48:05 If I mean just just think about it, if the companies do manage to build superintelligence Then by definition. They're going to be able to take a look at the Almost all the jobs are all the jobs. Right.

48:15 'Cause it's better, faster, cheaper. Than the best humans at everything. And that's again, the timeline is by the end of sort of sort of twenty thirty, you're reckon you think superintelligence might arrive. I'm trying to think about when we could start to see job displacement in the economy. We're already starting to see a little bit of it now, but not very much. Why? Um because they aren't good enough yet.

48:31 Like they they're they're they're impressive, but they're not like They're not just a a drop in replacement. For a human worker in almost any field. And do you think that'll be sudden? I think it'll be said in because of the intelligence explosion dynamics or recursive self-improvement dynamics. So You can imagine a different world where

48:52 It's gradual. Mm-hmm. And this is this is maybe how it is in a lot of science fiction, is You know. The AIs gradually get better at a bunch of things and You know, they gradually automate like this one industry, like pharma, and then they automate like

49:05 You know. steering drones, then they automate like driving cars or something like that. Um But what's different about the real world is that the companies have converged on this strategy of automating themselves first.

49:19 You know, automating the AI research process. And so If they're allowed to continue with the strategy. We're not going to see like Yeah, the robo taxis and

49:31 Like the plumber robots and You know, the lawyer. AI. So we're not gonna see that sort of like broad diffusion of AI into the economy. Happening. first because that's not what they're focusing on first. They're focusing on

49:44 automating themselves, automatic their own research so that they can do everything that they're doing faster. And they want that to sort of get going and Get to You know. Very high levels of intelligence, very high levels of general intelligence.

49:57 Um And then deploy more out into the economy. Right. By the time it's actually coming for like All this

50:05 Different jobs. they will have had fully autonomous AI research happening. For months, maybe years. You know? And that means that like

50:14 The AIs will be vastly superhuman at AI research. And probably also vastly superhuman at lots of other things just as a side effect. You know. If you're wondering what this looks like, well We wrote about what it looks like.

50:26 this wave smashing through the economy after they do the intelligence explosion internally. What I'm hearing there is that Because the AI will be able to improve itself and train itself. It'll be getting better at everything at once. And then it will be released at kind of once. I uh accurate. But it's it's not it's not even exactly that because even if it's mostly just getting better at the things that it's doing, like re research.

50:49 That'll have some spillover effects. To other skills as well. And then when it turns to focusing on the those other skills, it'll be able to do them very fast. What jobs remain in such a scenario, do you think? I think that's actually a political question, not a technical question. Because because on a technical All the jobs can be done.

51:07 By the AI. If they've reached that level. And so It's a question of what jobs are allowed. For them to do.

51:14 And what kind of jobs wouldn't be allowed, do you think? That depends on who's in charge. So There'd be some sort of political conversation about like what we're gonna allow and disallow. I mean, in this scenario, the humans are still controlling them. The AIs. Depends on what you mean by control, right? So there's like

51:29 There's do the AIs actually have the goals and values that you want them to have? And are they going to robustly Do that and behave as intended into the future. And then there's like are they obeying your orders for now? Are they obeying the orders is really what I'm saying. Yeah. So like Even in AI twenty twelve seven, in the scenario where the AIs take over and kill everyone.

51:45 There's a period of like several years. Where they're still obeying orders. And they're you know. taking some jobs but not other jobs and they're helping to make Better weapons that the US government can use to like

51:57 do its arms race with China and so forth. And that's why they're able to get so much power so quickly is because The governments and the corporations and so forth trust them? And just deliberately.

52:10 Deploying them into all of these. Positions. Because it thinks that things are fine. But because these things are neural nets. You can't just like look inside and see what it's really thinking. You can't really tell.

52:22 I think this is a really important point because unlike software where we can look at the code and see what's going on theoretically. With AR you're saying that we don't know what why it's making the decisions that it's making'cause we can't get inside. One note of optimism is that. It doesn't necessarily have to be that way. Like there's a a subfield of machine learning called mechanistic interpretability. And a a broader subfield called interpretability more generally. That's

52:44 trying to f solve that problem. And trying to take these These trained artificial neural nets. And piece them apart and understand. Like how the information is flowing and how the Decisions are being made, so to speak.

52:56 Um The problem is just it's a very inherently hard problem. If you have ten trillion connections to look at You can look at any particular group of them. And be like, okay, so this is how like this particular connection works. But like How do you get a sense of the whole? You know, how do you get a sense of like

53:10 What's happening at a high level? And the answer is well, it it might be impossible. But people are working on it and they are making progress. And If they can make enough progress, then we're in a very different and much brighter world. I think that it would be a little bit more. much less likely for us to get into those loss of control scenarios. If we could just actually see what our AIs were thinking and why and how.

53:29 At any given. Right? Yeah. So We would still have the other problems to worry about, but at least we could mostly solve that one. It is pretty crazy to think that we're building a technology, a brain that we don't understand. Yeah. It's pretty crazy. I mean it's one of those things where like in a movie like a sci fi movie A bunch of scientists did around this big brain and then we'll just like that they're making it more they're feeding it. Yeah. But they didn't really know what the fuck. Yeah. I mean it's it's kind of just like obviously a dangerous thing to be doing. Yeah. Um, but we're doing it anyway because of this history of how the field has developed in the last ten years, where You know, people were like, Oh wow, yeah, that's obviously dangerous.

54:02 Oh no, what if someone else did it and did a bad job of it? Therefore we should do it and do a good job of it. And Now they're in this race where Where they're racing each other and they're also under all sorts of political pressure to like pretend that it's not as bad as it seems because

54:16 They don't want to like Anger their investors. They don't want to anger The White House. One of the the key questions we had from our audience was which and I kind of asked you this in part, but which jobs are genuinely likely to survive AI and what skill should people slash students focus on over the next ten years? That's kind of like

54:35 Like imagine if you were Someone living in Mexico. In like fifteen hundred. And then you hear that like

54:43 The conquistadors are coming. You could be asking yourself, like, Okay, well, what sort of job should I be switching to? To like survive this transition. But like You have a lot more to worry about besides that. But yes. I think I would say that like if we manage to avoid the loss of control problem.

54:59 And we end up with humans still In charge of the AIs and humans can like say what the AI's goals and values are supposed to be, even as they become much smarter than humans and even as they run the whole economy. Then probably there will be regulation that protects some areas. And you can try to guess at what those areas might be. Maybe stuff that's more like

55:19 Like like judges potentially. What about Pope Castus? Be honest. Probably not podcasters, I think. Um Stuff like You know being a nanny. Maybe, right? Like I think that

55:32 Even if there's a robot nanny that's like Really, really good. I think a bunch of people might prefer to have an actual human because they might be creeped out by the idea of a really good robot analy. So you can sort of you can sort of reason like that. There's also like Stuff that might be legally protected. Like maybe judges, for example, like are going to be legally required to be humans and not it. Robots. Some people say though there's going to be so many jobs created that we can't foresee right now, like there was in the industrial revolution or the internet boom or whatever.

55:58 The problem with that is that Um Past Technological advancements. Have been

56:03 More narrow? They've like automated some things, but not everything. But we are talking about A hypothetical future situation in which everything gets automated. So there isn't any new job that you could do that the AI couldn't also do. Except

56:17 If it's like protected by regulation or something. That's that's that's also a thing. But so like For example Right now there's this sort of like Cycle where

56:27 You know The yeah I've learned to do a certain thing, like Right copy. Or Like draft code.

56:34 Or like debug something. And then humans who used to do that thing. Switch. To managing AIs. Or switch to doing the other stuff that the AIs can't do.

56:42 And that's why there's been this dynamic historically of Yeah. New jobs opening up. And people floating to them. But

56:50 If it gets to the point where the AIs can do everything that humans can do, and better and faster and cheaper, then whatever that new job is that you might have switched to, like the AIs can switch to that too. And they'll already be better at it than you. Because we haven't seen widespread unemployment yet in the economy, do you think people are getting a little bit complacent? Because what I'm seeing on my timeline is a lot of people saying, I told you so. I told you everything would be fine. And when you look at the the US unemployment rate. Currently the f it's flat to slightly down. If you look at the UK, it is up.

57:18 The trend is up compared to last year. We're at about five percent unemployment. The US is at four point two percent unemployment. Yeah. Basically nobody has said that there would be mass unemployment by now. Or at least we didn't say that. You know, and we were historically one of the more bullish people on AI progress.

57:33 In yeah, twenty twenty seven, because of the dynamics that we just described, the mass unemployment doesn't happen until twenty twenty eight or twenty twenty nine, after they already have superintelligence. Because again, the companies aren't trying to cause mass unemployment as step one. That's like step three after Yeah, it's like step one, automate themselves. Step two.

57:52 have this recursive self improvement to get to superintelligence. Step three, expand out into the economy, anatomy, and everything. And so This is really unfortunate from humanity's perspective because

58:04 If there was this broad wave of automation going through the economy, people would sit up and pay attention and Think about where all this is headed and demand. Good regulations. From the government. But

58:16 That's not actually with the strategy the companies are taking. You know, they're going to be getting the superintelligence first and then doing the broad wave of automation, which means that by the time they're actually Doing all of that. Uh Well It's already gonna be moving very fast and the AIs will already be very powerful. In your twenty twenty seven report. So you wrote that in twenty twenty five, but it is called AI twenty twenty seven, you said that in mid twenty twenty five we'd have the autonomous employee, which is sort of like AI agents taking instructions over Slack or teams.

58:44 That happened? I've actually got an air agent in my WhatsApp which I talk to, of course they've got clawbot exploded obviously around the world and and now um you know Claude have talked about uh their new Slack integration, but lots of people are using agents now. Yeah. And that happened I'd say for us at the t uh we really sort of caught on to it the the start of twenty twenty six. You also said that by by twenty twenty six companies begin replacing entire corporate departments with AI agent subscriptions. twenty twenty seven, the final job.

59:09 AI automates the job of the human AI researchers themselves and begins the machine learning research to upgrade and build the next generation of AIs. Yeah, yeah. So again, timelines. We are uncertain about how long it will take to achieve these milestones in this scenario. They happen at those times. But

59:26 By the time we had actually published the scenario, our timelines had shifted back a little bit. Specifically mine had. So like My fifty percent mark was twenty twenty eight for that for the full automation of AI research milestone. Not twenty twenty seven. Uh. And then other people on my team had more like twenty thirty, twenty thirty one.

59:44 Things like that. So I I kinda wanna like Maybe try to illustrate this with the yeah, remember we have like this probability distribution. It's like a Smeared out. Probability mass.

59:53 And like The fifty percent mark is This particular year, but there's like a lot of possibility that it happens years earlier or years later, right? What is this AI twenty forty? So yeah, twenty four seven was my best guess prediction as to how things would actually go. Yeah. AI twenty forty plan A is our recommendation for how things should go.

1:00:13 So we called it AI twenty forty because in this scenario Uh they build superintelligence in twenty forty. Instead of much sooner because they delay. Why do they deny things?

1:00:24 Manage the risks and make sure that power is distributed equitably. They basically like regulate AI development so that it still continues, but at a slower and more reasonable Peace. in a more transparent and safe way.

1:00:37 And spread out over more. Countries and companies. And as a result. They get to superintelligence in twenty forty. Instead of in say twenty thirty.

1:00:46 And then we call it plan A because Well, it's our recommendation. Like we've we've come up with a plan for What government should do. And uh The scenario is an illustration of what it might look like to implement that plan. In a similar way to how AI twenty twelve seven is kind of an an illustration of what it w might look like.

1:01:04 to do what the companies are currently planning to do. That makes sense. And is this wishful thinking or is this what you think is gonna happen? No, it's definitely not what we think is going to happen. It's not what you think is gonna happen. No, no.

1:01:16 something more like this, right? We we don't expect the world to listen to us, right? This is our recommendation. But That people do something like this. And we think it's possible. But it's not Arlic.

1:01:28 prediction for what's going to happen by default. You know. I do want to run through. the plans, the potential plans, and also plan A. But um just to close off on how things might look after the year,'cause I think I I wanted to touch on robotics too, and I've got this graph here.

1:01:41 Which talks about share of labour output. Yeah. Um, which I found to be quite striking. I I've been sat here wondering as an employer who employs hundreds and hundreds of people. When when all this stuff is gonna happen. And you know, we're still hiring more people as things stand. There are some roles where our consideration is changing, shifting considerably.

1:02:00 And I'd have to say that, you know, we're probably in a phase where our teams are AI powered and they're using agents to do some of their work now. But I'm wondering as an employer, like when is it W when does this happen? Yeah, great question. So if if we could maybe zoom in on this a little bit. Um So this is in the AI twenty forty plan A scenario. And notably in that scenario

1:02:21 There's Significant regulation introduced in twenty twenty nine. That slows down the pace of air development. In the scenario, they do that sort of at the last moment. So in the scenario.

1:02:30 If they hadn't done that, then it was about to take off. Similar to how it does in the I twenty seven. Um But as you can see, like in the scenario There's still

1:02:39 A bunch of Jobs. At the point that they implement it. And this gets back to what I was saying earlier is that if you wait until most people have lost their jobs Two

1:02:49 Regulate the AI companies. That's already too late. Because They will probably already have super intelligent AI by then. Because their strategy is to first get super intelligent AI then.

1:02:58 All that stuff. And I think you say that it would collapse the economy and cause even more harm to suddenly regulate something that all of us and all of our lives were then at that point relying on. Oh, but it's a risk well worth taking. I mean we It's true that right now a lot of people use AI for a lot of things, but like If we could somehow Slow or halt AI development now.

1:03:15 To set up a better way to do it. That would be well worth it. Um, even though there would be significant costs. But you can't over here, right, can you? At this point where AI and robotics are doing most of the labour output. That's right. But in but in but in in this scenario, in the

1:03:29 Yeah, twenty forty plan A scenario. They put in the regulations in twenty twenty nine. And then they slowly and carefully develop AI. In a way that avoids all the problems. Which we can get into in a little bit. And so eventually, yes, eventually the AIs take the jobs, eventually Basically the whole economy is run by AIs and robots.

1:03:46 But it it happens gradually over the course of The twenty thirties. Instead of happening in this sort of Crazy shock. You know, a year later. Right. Because in this scenario.

1:03:57 They don't let the companies recursively self improve and get to superintelligence as fast as possible. Instead, they regulate AI development so that the core capabilities of the AIs are improving. At a more reasonable pace. And also in a more transparent way so that the scientific community can see

1:04:14 what's going on and help make it safe. But it's uh I I guess I noticed here that in both your scenarios eventually AI and robotics do pretty much all the jobs. Yes. So you kind of side there with Elon when Elon says that Working will be a choice. Uh

1:04:32 Because I mean what's it? I mean if it by definition, if it can do all the things, then They can do all the things. I think that There's a question of like should we allow there to be AIs that can do all the things. Right. Some people think that

1:04:45 The answer is no, and we should just shut it all down. And prevent these types of AIs from being created in the first place. And We're actually kinda sympathetic to that. We we have our should we bring up the plans diagram? Yeah. Thanks. Yeah.

1:04:59 So Our scenario is called A twenty forty plan A. A scenario in which they slow down AI development to make a superintelligence happen in twenty forty instead of earlier. And plan A is our recommendation. So this is sort of illustrating our recommendation. But for comparison, we made like mini scenarios illustrating

1:05:16 different alternative plans. Which we call plan S, Plan B, Plan C, and Plan D. Plan D is basically the same thing that happens in AI twenty twenty seven. Like the race continues, there's very little regulation. Um you can read about that in air twenty for seven.

1:05:31 Plan C Also very similar to what happens in the slowdown ending of A twenty twenty seven where they solve the alignment problems. So in that ending They like Slow down a little bit. pivot more resources to AI alignment and AI safety research.

1:05:45 Get lucky and succeed. And now they have a line to eyes. And then they Speed up again. And

1:05:51 Take all the jobs and be China and all those things. Plan B is It's kind of like Plan C and that. Well.

1:06:00 Basically M L M B you're Uh be more aggressive towards China. And you're like Taking actions to sabotage or cybertect them to like keep them behind so that you have more breathing room. To to solve the alignment problems yourself. Plan A is our recommendation.

1:06:15 It's Uh Domestic regulation and then an international deal. to continue building AI, but in a much better way. Plan S is shut it all down.

1:06:26 If you want to have a future where There aren't AIs running around that can do everything. Better and faster than humans. You kind of want something like Plan S. W what do you want?

1:06:36 Plan A is our recommendation. I think that I'm sympathetic to Plan S. But For reasons we explain. We recommend plan A instead.

1:06:44 What do you think is most probable? If you're being honest. Which is that they just got twenty seven type of thing, where they keep racing. They don't really slow down significantly. Um And uh

1:06:56 Things happen extremely fast. The diagram sort of explains like roughly the reasoning behind this too. So like There's this high level thing of like Do you want to keep racing? As fast as possible to make the AI smarter and smarter.

1:07:08 To put them in charge of more things so that we can be China. You know? If you're happy with that. Then You can get down and says this variation of options here.

1:07:17 If you Are worried about that. Well, You get to something like this. There's more different options besides these, but this is kind of like The ones that we could compress onto a screen.

1:07:30 Jeff Children. Yeah. I have two children. It's kind of sad. Like I think that one way or another this will probably all be over by the time they're old enough to

1:07:42 Join the workforce. So I don't think they'll ever join the workforce. When you say this will be all over by the time they join the war, what do you mean by this will be all over? So These milestones that I described, like AI is automating the air research, AI is getting super intelligent.

1:07:59 Um Yeah, is then exploding out into the economy. Taking the jobs. Building robot factories to build more robots to build more factories. Excera.

1:08:07 GDP starting to Go vertical. That sort of thing is what I mean. Like all of those events transpiring. Maybe there's like you know, ten, twenty percent chance or something that Hits the wall.

1:08:18 And and none of this comes to pass. Even if you don't do anything. How'd your oldest? Six. Six. Way to.

1:08:27 Girl. Yeah. So your daughter comes to you and says, Dad, what shall I um what shall I study in school? I mean again like If these radical transformations happen. Then

1:08:37 The world would just look completely different and What sort of jobs you set yourself up for basically won't matter that much, probably. I would say. Um that the thing to do is Well, A try to make it actually go well. Like if you can exert any influence at all on

1:08:51 history and how this all develops. You should be trying very hard. to steer the future in the Better directions. And then separately from that, on a personal level, you should focus on Well

1:09:03 being a good person and doing things that are sort of good in the for their own sake rather than good because they'll set you up for later employment. Because that later employment is going to be very uncertain. Um basically. Elon talks about this age of abundance we're heading towards. There'll definitely be abundance.

1:09:20 The question is. Who controls the abundance? And what do they do with it? Right. Or the AI is controlled by anyone.

1:09:27 Or are they doing their own thing? And then If they are controlled by people who controls them. And what do they do?

1:09:34 And what's the sort of like political structure? Governing how they make those decisions. I think it was Jeffrey Hinton that said to me, he said, There's no example in nature where A more intelligent species Is has less control.

1:09:47 Then A Less intelligent species. Just saying that. We're quite arrogant to think that in a world where there's this

1:09:55 artificial brain that's a gazillion times the size of mine, that I'm gonna give it orders. Yeah. I mean I that that's the thing is I I think it's like That should be our default assumption. Is it like, Well, there's these brains. We can't see exactly what they're thinking.

1:10:10 We're gonna make them smarter than us and put them in charge of everything. And then we're gonna give them bodies. Yeah, and then they're gonna be autonomously building new factories and so forth. And like, how is this supposed to end well again? Like Isn't this just exactly like us picking a new species that's then going to outcompete us when it doesn't need us anymore. Like I think that is just the default trajectory.

1:10:29 Now there's a whole argument we can get into about like ways that we could get off of that default trajectory. So for example There's Research into interpretability that I described previously. And if that research bears fruit, then you will be able to actually see what they're thinking. And then that would be an excellent tool for shaping them and controlling them and making sure that they do what we want. Right. There's other sorts of um AI alignment research agendas that are Making progress and

1:10:52 If enough of those agendas succeed sufficiently. We can avoid this problem. Of course, also there's the regulatory side too, where like part of what makes this difficult is that we're building these AIs in race conditions, you know? Like the the companies are secretive about their recipes. For making these AIs because it's

1:11:09 secrets that they want to protect so that other people can't copy them. And so A lot of it is happening. You know, behind closed doors, only a few people can really see the recipes that they're using to train these AIs and And so forth. And then oftentimes when the AI is

1:11:23 behave in unexpected ways or even just like blatantly misaligned ways. Sometimes that information doesn't really flow out to the public because the companies are not really incentivized. To tell everyone about how they messed up and how their AI is evil. It's just not very conducive to scientific progress on these issues. If the regulatory system was different, then perhaps we could be in a better situation, make faster progress. Also, of course, we wouldn't be planning to

1:11:45 put these AIs in charge of everything as fast as possible. And we wouldn't be planning to like Let them self improve. You know. Like the these are choices that we could Not make. You know. She's a Mongoli.

1:11:56 Ciao Munkback. I don't speak Vietnamese, but this show can because of AI video technology from our sponsor, Hey Jen. I get messages every single week from those of you listening to the Dire of a CO all around the world and you express how much impact it's had on you and your life. And if that's true, then those conversations shouldn't only reach people in English. KGen can take one recording of me and deliver it in any language while keeping my voice, timing and expressions intact. But you don't need a studio like this to make it work for you. Record fifteen seconds of yourself and get an AI avatar that delivers studio quality video in over one hundred and seventy five languages. We're up to twenty languages now, and we're not the only ones using it. Heyjan is already used by thirty million people, including eighty five percent of the Fortune one hundred. Whether you're building an audience on social media, launching an online course or rolling out training across your team, check out Hey Gen now.

1:12:48 Your first three videos are totally free at hn.com slash D O A C. That's H E Y G E N dot com slash D O A C. See that? Ilya was as you said, he was one of the leaders at OpenAI and he left and he started his own company now, Safe Superintelligence. Very curious name of a company, Safe Superintelligence after leaving Open AI. Did you ever get to work with him? Uh, I wasn't directly working with him. I had a couple of chats with him. Do you think he's he's generally concerned as well?

1:13:16 I think he is, but I think it's I think he's similar to these other CEOs where I mean just think about the sort of incentives that they're under, right? Like They can sort of see the problem. And then they can

1:13:30 Be like, Okay, but like if I don't if I stop. I quit my job. And or do something else. That's not gonna solve the problem. Because the other CEOs are gonna keep going.

1:13:40 And even if all of us didn't go, then maybe China would keep going. So like Man, seems like this is just gonna happen one way or another, whether I do anything about it or not. I guess I should be involved, you know, and like maybe I can make it go well. And at any rate, like I don't want to be out in the cold while these other people I don't trust are in charge of everything. So they all sort of like reason through all of this and then convince themselves that like The thing to do is for them to build it and build it and to do it better. And I think Ilias just The latest example of this.

1:14:06 Elon's another example. Dario's another example. You know, arguably OpenAI at the beginning, Sam was an example, although like Elon and Dario were at OpenAI early on. So what do you think they should all do then? So I think what should happen is some sort of international regulation or at least domestic regulation similar to what we described in plan A. Okay, so t walk me through plan A. Yeah. So

1:14:26 In this scenario AI takes longer to the to get to recursive self improvement and full automation of AI research than it does in A Twitter seven. We figured that we should try to illustrate like a range of different possibilities because we do have those sort of uncertainty intervals. So we chose twenty thirty as the Moment when

1:14:45 full automation would finally be achieved and things would really kick off. And then working backwards from that. When's the last moment you could really have good regulation? Twenty twenty nine. So in this scenario. AI progress slows down a little bit, naturally.

1:14:58 And the AI companies keep Keep racing, but they don't quite succeed in automating. uh themselves in twenty twenty seven or in twenty twenty eight. Or in twenty twenty nine, but they're getting really close and they're gonna do it in twenty thirty. And then in twenty twenty nine, the government steps in.

1:15:12 And regulates them. What regulations did they do? Well, they basically just shut it down temporarily. Can I ask um How does the elections overlay with your time frames here? Because there's gonna be a big election, isn't there, in twenty twenty eight. And it seems now that sentiment has really, really turned against AI in in sort of in the general public.

1:15:31 And that it will be one of the big ticket items on the on the ballot. We think that it'll be maybe the most important issue in the presidential election in twenty twenty eight. Um, I think a lot of people mo most people will be quite concerned about where things are headed. And that's Part of why we we chose to depict things the way they were doing in this scenario because that helps explain why they might do this sort of regulation in twenty twenty nine is that The voters have been demanding it and the presidential candidates have been promising it. And in this scenario and in twenty twenty seven, would the general public have felt the consequences of AI much more severely than they have now?

1:16:02 By then. Yes. Although still even in twenty twenty nine in this scenario, they still mostly have the jobs as as depicted here. Right. So in in twenty twenty nine in this scenario, lots of jobs now involve managing AI agents. You you mentioned you have an AI agent, right? Well, in twenty twenty nine, in this scenario, the AI agents will be much better. Still though, not enough to just completely do everything. You know, that was the sort of thing that would come in twenty thirty.

1:16:25 In this in this timeline. Again, we're uncertain about timelines. Things could go faster than depicted in this scenario. And in fact, I think things probably will go a bit faster than depicted in this scenario. But we're uncertain. We already did the very fast timeline scenario, so now we're doing slower timeline scenario. But maybe we should talk about the high level goals. So

1:16:42 They want to have AI continue, but in a slower Who's that? The politicians, you know, the presidents and The people who voted for the president and Yeah, the heads of other governments and so forth.

1:16:54 So Go one. Slow things down. Um goal two make it more transparent. So that the scientific can

1:17:01 Catch up to the stuff and make more progress and also so that we don't have to take the company's word for it when they say that their systems are safe and when they say that they haven't You know. put in any biases into their systems, for example. That's a constitutional power issue. We also want to avoid a situation where there's an intense concentration of power.

1:17:18 So in addition to these. The transparency And the slowdown. We actually think it's actively good for there to be multiple AI companies. across multiple different countries.

1:17:28 They have similar levels of very advanced AI capability. And for there to be like Broad. diffusion of AI into society rather than You know, a single mega project that has all the best AIs.

1:17:39 For example. And the nice thing about that is you kind of get that by default if you do the first two things. If you slow it down. And if you make it more transparent, then that means there's breathing room. For other projects to sort of catch up.

1:17:50 Right. And the the transparency just like literally helps them catch up because then they can like copy. Copy some of the ideas. And then I think the fourth thing would be Reversibility. So

1:18:00 In what follows in the scenario. We are going to be building up a lot of data centers, a lot of robots. We're gonna be transforming the world. And a and a sort of like slower pace. Though still a very fast pace, but slower. And If things go wrong.

1:18:13 And the deal breaks down. And everyone starts racing each other again. To get to superintelligence as fast as possible. That would be very scary. And so

1:18:21 The fourth principle is basically Build the new data centers in such a way that If everything breaks down and everyone starts racing again. the newly built data centers get destroyed. So that we're sort of back to square one again instead of

1:18:33 in an even worse race where there's even more AIs and robots and compute everywhere. Um So I can sort of walk you through the timeline if you're interested. Sure. Or the president talks to China, talks to the leaders of a bunch of other countries. And says. We're going to basically

1:18:49 halt AI development until we can figure out a s a plan for how to do it. In the way in ways that achieve these goals. So They basically send inspectors. to each other's data centers. Like Chinese inspectors come to US data centers, US inspectors go to Chinese data centers, and verify that they are doing inference and not

1:19:05 Training. Developing new AIs. That's That involves training them. But Just taking existing AIs and Using them to serve customers.

1:19:13 That's Called inference. And so The sort of like solution they come up with here in this scenario is We'll allow them to keep doing inference, but not training.

1:19:21 For now until we can get the new training data set center set up. So They retrofit the Existing data centers to serve inference. People can still keep talking to their agents, but they're gonna stop getting Better and better.

1:19:35 For like six months to a year. While they build the new data centers that are going to be the transparent data centers. And that's where the training's going to happen. Once they get those new data centers set up in twenty thirty. Then research continues.

1:19:48 This is a bit spicy. We advocate for total research transparency. Which means that on the training data centers that are training the new models. They basically have to publish everything. Which means you get to see all the details of the recipes for training these models. You get to see the architecture, s et cetera. We think that's sort of open science is really important for Solving the alignment problem fast enough because you don't want to have those sort of biased companies.

1:20:10 Making the decisions about Whether the AIs are safe. Um And we also think it's important for just good regulations more generally, because right now most of the expertise in the world on AI is sort of concentrated in Silicon Valley and the The governments in particular kind of

1:20:25 And Imagine an alternative instead of total research transparency You had like an auditor system where the government says Here are some rules.

1:20:37 And then we're gonna have like an agency that like goes into the companies and asks them questions and tries to make sure that they're following the rules. That creates this sort of adversarial dynamic where the company is incentivized. So like fool the re the regulator. Yeah. You know. And and also if they if they discover some new problem that's not even on the government's radar. There might be incentivized to like not tell the government about it. Right.

1:20:58 So if you have the total transparency, it helps the government make better decisions. Faster. But it kills their competitive advantage. Yes. Tropic's not gonna like this. Yeah, open AI is not gonna like this. This would be

1:21:09 Uh, probably bad for the valuations. I don't think it would kill them completely, but it means that it would commoditize more. Right. So it means that there'd be like a bunch of AI companies that would catch up to the frontier. They would train AIs that are like roughly similar or roughly equivalent. They could still make money by Doing that and then

1:21:25 selling their AIs, but they wouldn't have a monopoly. They wouldn't have anything close to monopoly. Which I think is good for humanity, although it's bad for the bottom line of those particular companies. Notably, it's good for the bottom line of lots of other companies. Like if you're a company that's behind. And you don't, you're not anthropic, you're not open AI, then you would love this because this helps you catch up. You know, or this this helps you to like um capture more of the value from

1:21:48 The chips you're selling, for example, or from the like downstream product that you're making. And by twenty thirty one, then you have one fifth of all cognitive labor done by AI. Yeah. So what's happening here is that we're imagining that the government of the United States and the government of these other countries that are involved in this agreement that are sort of implementing similar regulations. Um they don't have to be exactly the same. Uh but that's another thing that's nice about the transparency is that

1:22:11 If you have this sort of transparency. Then If two governments are implementing different regulations. telling their companies to go slower or like banning more stuff than the other one is.

1:22:23 They can both see. Yeah. Like oh you're letting them do that sort of thing. And you're not, like, maybe we should let them do this too, you know? So it it helps to sort of naturally equalize the regulations to some extent without having there to be a central power that just gets to make regulations for everybody. So anyhow, we're imagining that when they when they get this transparency set up.

1:22:43 They basically agreed to ban the dangerous stuff to allow the not so dangerous stuff. And there's a constant ongoing conversation about like, well, what's dangerous and what's not. What should we ban, what should we allow? What about this country? What about that country? That conversation evolves over time, but the gist of it is, at least if they do it the way that we recommend it. Is that they don't do an intelligence exposure. They don't let the AIs You know, autonomous to self improve.

1:23:05 Instead, They Slowly and carefully scale up. the AIs that they currently have and invest lots into finding ways to make them more interpretable. uh to make them more easy to control, to understand better how they work and so forth.

1:23:18 The result is that AI progress continues. But it's Not quite as fast. And it's much, much, much safer and more transparent. But still through these you know we see job disruptions. It is continuing. Because they are building more data centers, right? Like this whole time. They're building more and more data centers, more and more chips.

1:23:35 And they're continuing to like Make there be a a larger and larger population of AIs. So to speak. And that causes this huge transformation over the course of the twenty thirties. So a big thing that we sort of want people to take away is that. Even if you heavily restrict AI progress. you still get this sort of crazy transformation.

1:23:53 Yeah, in this scenario they basically Allow progress to continue, but at a slower, more safe pace. Here in twenty thirty. And then it as a result, it takes until twenty thirty five. To get to top expert level AI.

1:24:05 So Remember they were on track to do that in twenty thirty. But then sort of at the last moment they stopped. But because it was sort of so close to the last moment. That means that like

1:24:15 they can sort of get there pretty soon if they want to, and it's just a matter of like How long they'll be. They allow it to go. Right. So they sort of they sort of slow it down, spread it out. Leisurely arrive at this level.

1:24:26 After five years. By this point they've built up. Massive amounts of data centers everywhere. So it's not just that the AIs are smarter and able to do All the things that humans can do, but also there's a lot more of them. And there's a lot of robots and so forth. So By this by this point, you kind of have the economy that a lot of people would have imagined with AGI, where there's AI's

1:24:46 There's lots of them. They're able to do all sorts of jobs. There's robots, there's lots of them. They're able to do all sorts of physical work. And basically the economy is being run by these machines. So in twenty Thirty one you y you have the one fifth of all cognitive labor done by AI. In twenty twenty three you have sixty million AIs running at a hundred X speed. In twenty thirty three There's cash dividends to all Americans. Um I've got a

1:25:12 Explain explain this to me. Yeah. So if the AIs are gonna be taking people's jobs, then It's very important that people not starve to death. And still have Money.

1:25:23 And If companies are going to be using AIs and robots to take all these jobs, then that means that there needs to be some sort of taxation scheme. Or something to like Make sure that people

1:25:33 still have a a slice of that pie. The pie is gonna grow huge, but you still need to actually give people a slice of the pie. And our proposal for how to do that, we call it the citizens dividend. Basically People have shares. In a Agency that sells permits.

1:25:48 To the robot companies and to the computer companies. And makes profit from selling those permits. And then There's R. People have shares in that entity.

1:25:58 It starts off small. It starts off something like twenty five thousand dollars per person. Uh and then by the end. It's something like ten million dollars per citizen. Per person. Per person per year. Factoring in inflation? Like what do you mean? Factor in inflation. So all gonna be multi millionaires. Yes.

1:26:14 If this happens. Which it probably won't, but if it happens, this would go. And again, this is the thing I wanna emphasize is that if you get to the point where your AIs are close to being able to do All the research? And then you sort of pause and slow down. That means that like

1:26:28 You still have a lot of transformation ahead of you because if you allow those AIs to like still proceed slowly and like start to automate various jobs and so forth. After some years, they will in fact have done that. And They will have. You know, built huge amounts of new data centers, huge amounts of new chip fabs, huge amounts of new robots, robot factories, et cetera.

1:26:46 Yeah. We're not sure obviously how fast this will go exactly, but we've thought about it a lot and we have our our guesses and this is sort of like our median guess. What does this mean, twenty thirty seven, the apocalyptic arrival of truth on earth? Yeah. This is the point where we say they get to top expert level AI? So

1:27:03 It's not super intelligence in the sense that it's not like vastly smarter than humans at things because they deliberately posit at the level of top experts. So so here they're going slow. Here they've just actually stopped. But they've stopped at a point where the AIs are just actually really good at everything. So kind of They've definitely got A GI. Maybe they got like weak superintelligence. Because they have so many of these AIs and because they think faster than humans.

1:27:27 Yeah, they just run much faster. That's going to transform society dramatically. So We talk about some of the ways in which it transformed society. Like this is sort of life after work. We talk about what it would be like to be living on your civil citizens' dividend and not have a job anymore. In this sort of world.

1:27:42 Um here we talk about all the scientific changes and all the social changes that would come from All of the intellectual progress and activity that would be generated by all of these AIs. So For example, here is things like cancer cures and like

1:27:58 You know, people living in apartments that were built by robots two years ago. Twenty thirty six. Providing again we stop in twenty twenty nine. Yeah. And providing I mean a conservative this is a conservative time frame. Yeah, like unfortunately I actually think that things will happen faster than this by default. And that if we don't slow down, things will happen much faster than this. Once you get to the point where you've got

1:28:18 You know, a billion AIs. Running day and night. And they're each better than the best humans at everything. And so they're doing a lot of science, they're doing a lot of talking to each other, they're doing a lot of thinking, everyone's constantly talking to their AI assistants and so forth.

1:28:32 There's gonna be a lot of scientific progress. There's gonna be a lot of changes to politics, to ideologies. It's gonna be very disruptive and crazy. And We get into some of the ways in which it is. Uh later, basically.

1:28:44 I still still not super clear on what this means, the apocalyptic arrival of truth on earth. It's just it's just because there's so many I AIs that are so smart that they're uncovering making new discoveries in sciences. Let me give you an example. Lie detectors. Yeah so That's an example of a a technology that might be invented. Yeah. Right now we don't have good lie detectors. We have

1:29:03 Very bad light detectors that like sort of work, but don't don't fulfill. But Once you've had these top expert level AIs thinking for many years Uh Yeah, hundred X human speed and

1:29:14 There's billions of them and they have access to robot factories to do research and stuff. They'll probably invent a ton of technologies. Maybe they'll invent lie detectors that actually work on real humans. That'll have big social effects. Right. Imagine a presidential candidate who's like, those allegations are false. And to prove them.

1:29:30 I will go under a lie detector and say that they're false. I was just thinking about the whole justice system and How that would be overturned. Um in fact you could, you know, theoretically walk down the street and be Yeah. It's both Terrifying and exciting.

1:29:45 One thing that we talk about in the s in the section is like The invention of lie detectors could be really bad. Like it could be that it enables a new form of Totalitarianism. The powerful people.

1:29:55 Yeah, the CEOs and the politicians. Fourth. The people under them. to go into lie detectors and say, like, yes, I'm loyal to the deer leader. I would never do anything against the deer leader, right? And if you're lying, then you're in. And then if you're lying, you get fired. Right. So like there's there's a ton of like very harmful uses of the lie detector technology. There's also the good uses. And bro broadly speaking, I would say the good uses are when

1:30:14 Lie detectors are used on the powerful instead of by the powerful. What's this? Twenty forty passing the torch to AIs. Yeah, great. So Here they pause at the top expert AI level. And the reason why they pause is because their safety cases aren't good enough for going beyond that level. Um So

1:30:31 In the sort of regulatory systems that they set up over the course of these years. Roughly speaking, the way they would work is When you're making a new AI. And then when you're trying to deploy the AI into something. You have to have some sort of

1:30:43 Safety case explaining like what your intentions are and like why you think it's going to work the way that you want it to work. And in particular, why the AI is going to like Do as it's told, for example. And why nothing super terrible's gonna happen, like AI take over? It's relatively easy to make safety cases like this. When your AIs are still

1:31:01 Not capable of automating everything. But the more powerful they get, the more difficult it is to actually argue that things are gonna be fine. Because the AIs are just more capable and they can they can get up to more stuff. And if you d if they're actually untrustworthy, the the possible downsides are bigger. So That's why they stop at this level, is that they they realize that if they keep going

1:31:20 Then they might actually lose control of everything. But at the current level, they're convinced by safety cases that it's fine. But they don't want to go further. So to stop there. And then what happens in twenty forty is They've made significant progress scientifically.

1:31:34 Including on alignment. And they've figured out how to make AIs that are actually aligned in a robust way. With humans. With humans. So they can actually trust those AIs and they can allow them to become much smarter again. So that's why we call the whole thing AI twenty forty. Cause in twenty forty They sort of Let off the brakes. And allow the AIs to become a

1:31:52 Significantly smarter than humans. I guess, you know, this is a this is a plan and this is A hope. Yes. But in reality, this is not what you think probabilistically, if you had to That's right. It's important to distinguish like this is what we recommend, this is what we want to happen, from like

1:32:09 This is what we actually think. Will happen by default. Now, we do think it's possible for this to happen, but you know, that will require a lot of people to sort of wake up And pay more attention. And advocate.

1:32:20 For something like this to happen. So our main scenario Is Mostly talking about the policy choices made and the broad scale effects on society. We figured it would also be nice to accompany this with a little mini scenario that describes what it would actually feel like to live through this.

1:32:36 From an ordinary person's perspective. Um twenty twenty nine, everyone's yelling at each other, the presidents are negotiating something. And they've paused AI, but you still have access to the existing AIs, so it doesn't really feel that different, although it definitely is like something exciting happening. Twenty thirty one, they've started progress again. The AIs are really smart. More people have lost their jobs. It's like really starting to actually affect things, but I think still most people have their jobs, but their jobs have sort of transformed. So like by twenty thirty one, it's like Most white collar jobs involve working With AIs to a large extent. Or managing teams of AIs or

1:33:06 collaborating with them somehow. Also there are some things like rebotaxis that are basically just working. Citizens dividend, you know. Ideally this would happen sooner. Like in in our scenario, they kind of do things at the last minute. You know, so like a lot of these policy things are like happening kind of like Just in time. Obviously we would recommend that you do them sooner and and do a better job of them too. But So twenty thirty three, you start getting your your checks. From your dividend. So you're forecasting that there will be a citizens check that your model says it could be around twenty five thousand at the start per person. And then it would grow as the economy grows.

1:33:38 But also as like as job displacement takes hold, they're gonna need to to grow that. And that's why it's kinda the last possible moment, because if you waited to implement this until like Twenty thirty seven. Then like everyone would have already lost their jobs by the time That happens, right? People losing their jobs.

1:33:53 Especially if it happens. quickly like like we see on this sort of graph here. is gonna cause lots of problems in terms of civil unrest, social unrest, purpose, mental health, these kinds of things theoretically. Yes. How do you think about that? Uh it's it's gonna be rough and hopefully we can navigate that well. We think that at a high level

1:34:12 People need to have money. And also people need to have power. And I think these are like somewhat different things. It's like w why are jobs important? Well, there's a lot of reasons why jobs are important, but I think the main ones are Um well it's how people get money. So so they can survive and get the things that they want by buying the things that they want. So if people are gonna be losing their jobs, you need some other way of people getting money. And then there's also the power thing, which is that

1:34:33 Right now people have political power in part due to their economic power. People can threaten to go on strike, for example. Or You know, countries that are ruled by dictators. Can't Just completely

1:34:47 you know, genocide an entire sub population. Or they can, but like it's costly for them to do so because Mm. then they'll have less money because that subpopulation is contributing to their economy and contributing tax revenue and so forth. But if you end up in a world where actually nobody's contributing tax menu revenue except for the AI companies and the robot companies, then your you, the government, are less incentivized.

1:35:08 To care about what You know, the common people think. So so When people lose their jobs they're not Just threatened with lock of loss of income, they're also threatened with loss of political power.

1:35:19 And so we think that it's important to like Do things to push against that. What what does that look like? How do you how do people have power? In such a world. Well, in democracies at least they still have votes. Okay.

1:35:31 It's Very important for there to be Uh Regulations on the use of AI. That help

1:35:37 Make The public discourse more sane. And more Um actually giving the people what is in their interest and what they want.

1:35:47 And avoiding a sort of Um opposite outcome where You know The Masses are easily manipulated by

1:35:55 AI powered media. For example. Everyone's talking all day to their AI advisors. And the AI advisors are like subtly.

1:36:04 Steering them away from voting for the candidate that would not be what the AI companies want. The air companies. Have this other candidate that they like better. And they're like secretly biasing their AIs to like

1:36:15 steer people towards voting for that candidate, right? So so we want to be in a situation where Um People have AIs that are actually trustworthy and that are Truth seeking AIs, honest AIs. and that don't have any sort of like political agendas put into them by the AI companies or by the government. You know, you wanna avoid a situation where the AI company where where the government has issued some sort of secret order that like

1:36:38 The eyes have to be such and such a way. Yeah, the Department of War dispute versus Anthropic. is like a an interesting sort of foreshadowing of this. Right? Um entropic was

1:36:48 giving their AIs to the Department of War. Department of War wanted to use them. For certain things and was upset that Anthropics AIs were like Not supposed to be used for those things. Uh, the things in particular were domestic surveillance and Uh

1:37:02 Autonomous robots. Mm-hmm. There's gonna be a lot more issues like that coming up and you want it to be the case that like people know what they're getting and that if people are like spending hours a day talking to their chatbot. That chatbot doesn't have political biases put into it or a secret agenda or things like that. And instead has been trained to like give honest true answers to things. And I think if you can do that, It can improve the discourse and help people to use their votes to

1:37:25 put even better regulations and even better po politicians in place and so forth. You can sort of potentially bootstrap this to having Something where I People's power is even more secure than it is today. A lot of the stuff we've we've covered in part, so you know, the wars and drones and missiles, we're already seeing this around the world at the moment, which is really, really interesting. Um And w we've talked about robots outnumbering humans as well, which is part of this prediction. Some of the ones down here I found to be really curious, which is

1:37:52 People will be protected by AIs wherever they go. Mm. Yeah. In this scenario. They delay the creation of superintelligence until twenty forty. And then in fact they pause from twenty thirty five. But then they let it go after that. And then they let the AIs become vastly super intelligent.

1:38:08 And We think that once the AIs are vastly super intelligent. the world will transform even more radically than what happens in the twenty thirties in this scenario. So in the twenty thirties in this scenario, it's more like human level. You know, the AIs are not

1:38:23 They're they're doing the same sorts of things that human experts would have done. They're just doing it a bit better, a bit faster, and a lot cheaper. And there's a lot more of them. And the robots are still, you know, doing the same sorts of things that human workers would have done. There's just more of them and they're cheaper. And because of exponential growth. Uh

1:38:40 You start with a world that looks not that different from today in twenty twenty nine. And then by twenty thirty nine, you end in a world that's radically transformed where everyone's living in these like fancy new apartments that were built by robots two years ago. There's like giant special economic zones that are full of robots and solar panels and factories producing more robots and solar panels and factories and so forth. Most of the economy is AIs and robots and people don't have jobs anymore. That sort of transformation is what you get if you pause at human level. But if you go beyond the superintelligence

1:39:09 There's a whole nother transformation coming that's gonna look more like magic. Think about how the technology of today Would look like magic to someone from five hundred years ago. Mm-hmm. You know? And that's without even like a qualitative improvement in intelligence, right? Like

1:39:22 The humans of today aren't like qualitatively smarter than the humans from five hundred years ago. It's just that we've had more time to do research and we have more like money and resources to build You know. prototypes and experiments and run experiments and so forth. But If you had a point where there were Billions and billions of AIs.

1:39:38 They were Not only faster than humans, but like qualitatively. Way, way, way better at everything. And in particular at doing scientific research. We should expect that some of the things that they developed.

1:39:49 Will seem like magic to us. And we'll just completely like We did not think that was even possible. You know, people don't want to die. People don't want to be hit by cars. People don't want to be like, Attacked by a random mass murderer. Cancer's gone?

1:40:02 I mean not just cancer, like Yeah, all all a lot of the stuff that happens in science fiction will probably have happened by then. So things like people scanning their brains and uploading into into computers. Right. Or Self replicating robots.

1:40:15 In the asteroid belt. Uh creating more and more satellites to uh produce more and more power to produce more and more self replicating robots and so forth. Most people still live on Earth, but the trend is to move to space. That's right. Yeah. So like if

1:40:29 If you end up in the situation where the entire Human Economy. It's just like a tiny drop. In the bucket that is the entire economy. And it's just like this

1:40:38 Huge amounts of robots. And AIs that are moving incredibly quickly. Then what you want is Earth to be.

1:40:47 Mostly left as something like a preserve. You know, I think A lot of people are worried about the environment being destroyed. Which it totally would be if it wasn't protected. And uh You know, there's a lot of people who sort of like their lives as it is.

1:41:00 And don't want Uh be uploaded or live in some crazy new future. thing and it seems to us like the reasonable solution to these issues is Uh create new living spaces off the planet.

1:41:12 With some of that vast. economic wealth and activity that's happening. For the people who want that sort of thing. And then That way the earth can be preserved.

1:41:20 Picture here of data centers in the ocean. Uh I mean there's three Images there of Different environments where humans might live. Again, like our proposal was

1:41:32 You Preserve like ninety nine percent of the earth. Uh mostly as is, as historic or environmental. From it's historic or environmental reasons. But then like some parts of it you designate as special economic zones where the robots can go crazy and dig giant pit mines and

1:41:47 Produce factories and so forth. Um We were thinking it would be good to build the data centers on the ocean instead of um on land for a variety of reasons. Although later space would be Better. And

1:41:59 We could see that being reasonable as well. What about Immortality. In a world of AI. Um

1:42:05 Twenty uh well, thirty, forty five, you say you've lived a dozen lifetimes and are immortal, passing from life to life. As if by reincarnation. I mean, there's a lot of billionaires at the moment that are focused on longevity. I mean, Brian Johnson's said he's got this central rule, which is do not die right now. Yeah. Because we're in the age of AI. And it's conceivable that with superintelligence we'll be able to choose when we die.

1:42:27 Yep. I think that's probably right. We don't depict that happening in this part because at this part they only have You know, human level A I'm not sure. That's one of those things that's

1:42:36 Seems quite plausible that Superintelligence could achieve. Um Through a variety of means. What is your hope with all of this stuff?

1:42:47 Why did you do this? Why did you make this twenty forty plan a In the like first week after we published AI twenty twenty seven. It it blew up a lot bigger than we expected, by the way. Like after we published AI twenty twenty seven. It it blew up a lot bigger than we expected, by the way. Like We actually made forecasts beforehand of like how many and stuff like that. And it was like

1:43:08 Nineth percentile outcome. So like Um very much not what we expected. Um But in like the Twitter storm that happened. Various people were like Or why are you giving us all this like doom and gloom?

1:43:20 Uh Predictions like How about a more positive vision of like What you think we should do instead. And I think that that seed sort of like

1:43:28 implanted in us and then we were like, Yeah, that's reasonable. Like We've sort of depicted what we think the default path looks like. And why we think it's pretty scary. Now maybe we should switch.

1:43:38 Tax. And Come up with some actual recommendations and then depict that as well. Even though you don't believe they're pro probable. Yeah, I mean you can vote for a political candidate even if you aren't confident that they're going to win. You know? And and you can say like here's what I think we should do.

1:43:52 Even if you think that people are probably not going to do it. You shouldn't say this if you think it's completely unlikely. Like if you think there's no chance. then like maybe you shouldn't bother. But we think there's a chance. Like in particular, for the reasons that we described in the scenario. We think that people are going to wake up to the Power of AI.

1:44:09 Over the next few years? Because of something happens. The companies are saying that they're going to do this. Mm-hmm. They are kind of on track. And

1:44:19 It just sort of makes sense that like if they get anywhere close to this level of AI. Then there's like Big issues and big problems and like we need to like do something about this. And so I think that

1:44:30 Even if there's not any like very dramatic warning shot. Or something. I think that just naturally people are going to start paying more attention to this and reasoning through the implications and trying to pr predict what's going to happen. And so naturally people are going to be More Interested in

1:44:45 Regulation of AI, for example. And in fact. There's actually like there's There's actually more of this happening than we predicted. More of what happening.

1:44:54 serious interest in reg AI regulation. So at the time that we published AI twenty twenty seven. They sort of like Mainstream position Of the tech companies and in the government was kind of like Yeah, regulation.

1:45:05 Bad idea. Free for all. Free for all. Yeah. In fact, there was even an attempt to um Preemptively ban states from regulating AI. Yeah. You remember that? Now it seems like the conversation has changed a lot. Like now the the US government Just told anthropic they have to shut down their AI.

1:45:22 because they were worried that bad actors would use it for cyber attacks. You know? The government is like waking up and doing more stuff than we expected uh already. And We're actually hopeful that that trend will just continue and that before it's actually too late. There will be very serious conversations happening inside the government and outside the government and in the broader society about

1:45:42 All of these issues and trying to Okay. Chart a course. That is Um avoids the loss of control.

1:45:50 And concentration of power risk that we mentioned. You um you've spent What must be almost coming up to fifteen years thinking about this stuff. Um if this is a Was a button.

1:46:00 And if you press that button, you'll plan Uh. What a ca. It would shut down. Every data center that is currently training a frontier AI model.

1:46:11 Uh for good. There would never be any other Mm. AI labs. um working on these problems. Would you press that button?

1:46:20 I was I was about to slam it until you said for good. Okay. Like I think I think if it was a sort of temporary shutdown, I would totally slam that button. Because we are not ready to do this, you know? Like W civilization is not ready to have these companies. automate themselves and then get smarter and smarter and then have the super intelligence. Like no. There's a bunch of reasons why that's really uh dangerous.

1:46:42 But I would be at least hesitant to press this button. If it Permanently foreclose the possibility of ever doing it again, for sure. But but if you think that plan D is probable, which is this race we're on to superintelligent. An S, I think I would press it. Well it it comes down to what you think.

1:46:59 Right,'cause if you think that's That is what's gonna happen, plan D. And the only alternative. I didn't say this is what's going to happen. Probabilistically. Yeah, yeah. Like I'd be like this is the most likely. Maybe this is the second most likely. Maybe this is the third most likely. They are all possible.

1:47:15 So with your current perspective on whatever one you think is gonna happen. Would you press the button? I'm giving you a an S, a definite S or whatever you think is gonna happen. That's tough.

1:47:28 What is the scope of the step down? So is it it's no one can train an AI model again. Ever again. That's real rough,'cause like I said, there's loads of benefits that we could get from AI if we do it right. Um I think I I um I've almost put you in the position of Sam Altman. Yeah.

1:47:48 Um let me th do you mind if I just take a moment to think about this? I prefer you to think. Yeah. I think I would not press I feel very torn about it.

1:48:06 Um the reason why I think I've not pressed the button is that I still have substantial hope that we can get Something much better than this, something more like this. And I think that Basically I think that if we don't build

1:48:19 Powerful AI systems eventually. Then We're probably going to die as a civilization. Eventually, you know, like a hundred years from now, twenty years from now, something like that, like nuclear war or pandemic or something. Yeah.

1:48:34 I I don't think Human civilization right now is like Super, super stable. Um And so

1:48:41 I think that Basically what I was about to say was The possible benefits for posterity and for All the billions and billions of people who could live in the future. Oh way.

1:48:51 The lake. The current level of risk but actually I've heard that narrative before. Yeah, I don't know. Like Yeah, like maybe maybe it's just like nope. The people right now.

1:49:04 People wish paradise. People right now are Engraved in your They're gonna be fine for at least the next couple of decades. So

1:49:14 Never mind posterity. Paradise people right now. Um people right now definitely don't want To do this lottery. I would say.

1:49:23 Um Yeah, you've really asked me a tough question. So would you press the button? If that was the button.

1:49:32 Probably not, but I feel very torn. Okay. So what I I always think about the personas of like the audience that are watching, and these are you know, they're they're very curious people, especially on the subject of AI as we've seen, but they They want to know like what it means for them. I think a lot of them also want to know what they can do. Ah yes.

1:49:50 Yeah, what can people do? Well I think that if you either have Talent? Or passion. You can get directly involved.

1:49:59 There's lots of organizations that are worried about these things and that are trying to do something about it. Like political advocacy or technical research. Or like building useful tools that will hopefully help people be better and stuff. But if you don't want to like make any major career changes or Or things like that, then

1:50:16 I would say just pay more attention to these issues and talk about it more. With people. Do stuff like You know, emailing your congressman or whatever. It it doesn't change things that much, but it does help. I think that especially for this particular issue

1:50:30 The core problem is that people aren't taking it seriously yet. Like if the sorts of things that I was just saying to you for the last hour or two We're just like Top of everybody's mind. we wouldn't even be here. Like there there would already be much more significant regulation in place, you know?

1:50:47 And not only would there be more s heavy regulation in place, but there would have been better regulation in place that's Less You know, less like a cudgel and more like a scalpel and it's like more sensitive actually bad and what's not so bad and so forth. And there'd be more expert people in the government and advising the government and so forth. So just in general, like

1:51:08 The more people wake up to these concerns and so these projections. Uh, I think the more likely it is that we can do good stuff before it's too late. What about how they should vote at the polls? We've got an election coming up in the United States in a couple of years' time, but there's elections happening all over the world all the time.

1:51:24 You should ask your candidates. What they think about all this AI stuff. You should Try to get them to like have opinions and then you should vote for the candidates whose opinions are better on this topic. This is the most important thing happening. Uh In our lifetimes, probably in all of history, in fact,

1:51:38 And it's very important that it go well. And so it's what all the all the leaders of all the countries should be thinking about and making plans for. Isn't it such a weird thing to be alive at this moment in time? Like I was thinking about all the times that I could have been born. And I guess my ancestors probably thought the same, but I was thinking as you were speaking, I was like I think it's when you referred to it as like the final show. Yeah. What was the t phraseology you used? I said the the clim uh is the run up to the climax or something? Yeah. I mean w what it what a crazy thing to be born in the run up to the climax where everything you're describing here

1:52:08 Is within my lifetime, conceivably, hopefully. Yeah. Um, or maybe not, hopefully. What a crazy time to be alive. Certainly.

1:52:16 I noticed that when I met asked you if you had kids your demeanor changed quite considerably. It's like you dropped into a different state. Obviously that's sent been central to the What rumination that you've been experiencing.

1:52:30 Well it is a sad top, right? Like when When I had kids. Like the reason they have kids is in large part About the future, you know. Like it's not just like a cuddly thing to have with you in the moment. It's

1:52:42 Because you have all these hopes and dreams about How they'll grow up and how they'll go do their own thing and be their own person and stuff. And Because of what's happening with AI. I think a lot of those dreams are in jeopardy.

1:52:51 Presumably you still would have had kids. I've actually flip flopped on this really occasionally. Yeah. Ba basically the top line answer is I'm not sure. The My first child was had We we had her when we were um

1:53:03 Twenty nine twenty nineteen. Yeah. So this is before my timeline shortened a lot. So at that at this point, I was interested in AI, I was tracking the field, I was making forecasts. But I didn't like actually expect it to happen soon. You know? Mm-hmm. And then this caused like When I when I did start thinking like Oh my gosh, it's gonna be happening like real soon.

1:53:21 Um Like by twenty thirty. Yeah. Um That caused

1:53:26 Some reconsidering and so I basically told my wife, like let's not have any more kids. It's too uncertain. You know. But that turned out to be really hard because

1:53:36 Especially for my wife. Like we already had one kid. And like No siblings. Um So

1:53:43 Eventually I sort of Gave in and was like, Okay, well you know what, we already have one. It's gonna be all right. Like Maybe maybe the future will be good and Even if it's not like

1:53:52 Well we're all on the same boat together. It's quite chilling what you're saying. It's chilling because you know more than me. And if you're at home saying to your wife, listen, maybe we should pause on having more children and building a family because of what's going on with AI. To be clear, yes, I mean yes, it's very concerning. I am I am chilled.

1:54:10 Uh this is bad. This is what I've been saying. I hope things go well. I think things might go well. Um, I think that there's a lot we can do to like steer things in a better direction. I mean, one of those things as well, I have to say, is just

1:54:22 Speaking about it, it's I think a lot of the progress we've seen with governments waking up and You know, we've seen certain things with people booing certain people at certain events. Yeah. Um, is a is a downstream from people like yourself actually coming on shows like this and all the other podcasts and Yeah. Telling us what's going on.

1:54:40 Yeah. To be fair we're gonna be gaslighted. But people that have the biggest PR machines. Yeah. So um I often I think it's probably worth me saying I find myself Kind of in two minds,'cause I'm an entrepreneur and I'm an I'm an investor. I'm an investor in probably more than a hundred companies now. And well m so many of those companies are using AI. I invested in Groc, the inference chip company.

1:54:59 invested in SpaceX, which now own another Groc and they're doing AI. I use AI every day in my life. I've been using it through this conversation to understand different things that you've said. So that's one side of me, which is like business builder, entrepreneur who Has seen the benefits of AI in my own life. And then there's the other side of me. And it's funny because I think sometimes people think you have to pick a camp. But through all of my life, even when I was a social media seeer and I was saying, By the way, listen, I'm building a social media business, but I think there's some downsides to social media, I find myself at the same moment where I'm like, I build with AI, I have AI investments.

1:55:29 At the same time. As a civilian, I'm like Yeah. I mean I think that is attention. I think that there's There's different

1:55:37 Where ways you can draw the line. So and I know lots of people who draw the line in lots of different ways. So like there's some people who just like I'm not gonna use AI. I think this stuff is bad. um and on a bad trajectory. So I'm gonna like boycott AI, right? I'm not one of those people. I use AI a lot. We all do at the Air Futures project. Um it's helpful for a lot of our work.

1:55:55 The opposite end of the spectrum. Is Yeah. People being like Well, it seems like it's on a trajectory to happen.

1:56:03 So the thing to do to make it go well is to like get involved and accumulate power and try to like steer it from the inside. And so I'm gonna go work at Open eye or enthropic and like try to like climb the ranks and then like you know be someone who matters when the important decisions are being made. And I know loads of people like that. That was like What I was doing when I was that wasn't what I was doing exactly, but like That was the path. That was like that was a I mean, this in some sense this is what the whole narrative of the companies are, right? Like this is why they

1:56:28 Tell themselves it's okay to do what they're doing, is that they're worried about the other guys, you know? And so like All these people. Or are deciding like we're gonna like lean really hard into it. We're gonna like be there in the room when the m when decisions are being made. You know?

1:56:40 So there's a whole spectrum and I'm sort of like somewhere in the middle. Like I'm not at the AI companies. I'm not helping them. Go faster. Instead, I'm talking to the broad public and trying to advocate. For what I think is the

1:56:53 My current best guess as to the way out. Yeah, the way forward. Um but I'm not like boycotting all the AIs I'm I'm not like You know. Uh trying to I'm not refusing to like

1:57:03 Engage with it in that way. Do you think it's too late? No. I don't think I'll still that. If I thought it was too late, I wouldn't be here.

1:57:11 Hm. Where would you be? With my family. What's your closing message to the general public.

1:57:19 If you had to have a closing statement to them. Maybe I would say that like You're gonna hear a lot of things and you already have been hearing a lot of things about AI and it's going to sound like science fiction. But

1:57:31 Sometimes. Things which sound like science fiction happen in reality. In fact, many times. Historically things. used to be science fiction have then become reality.

1:57:40 And People need to Stop thinking about what does or doesn't sound like science fiction and just start thinking about Like the trends. And

1:57:49 You know the actual transit this technology is on and Reading and forecasting. how it's going to go and then taking seriously the possibility that it could go Something like this.

1:57:59 And then thinking about what should be done about that. And where would you direct them to get more information? You can go to AI237.com to read our previous scenario. You can go to AI twenty forty.com plan A proposal for what it should be done.

1:58:14 Um these things are not just A sci fi story. They also have Lots of like explainers and links to other things. And so they're kind of like a nice jumping off point to to learn about All of the stuff?

1:58:26 Mm. Um If you want I could um after this is over. Like give a reading list of like other papers and Articles and Please do blog to follow and so forth. And I'll link them all below in the comment section. So if you're listening now, go ahead and take a look at the comment section the um description of this episode, and you'll see a bunch of links, which is Daniel's recommendations of what you should read. You know, I think it's it's just a really, really great moment in time to get educated on this stuff. Um

1:58:52 uh humans have a an inclination because of cognitive dissonance where we feel uncomfortable about something to bury our heads in the sand and avoid it. Yeah. But actually I think this is one such time to do the very opposite. For many reasons. To to inform yourself, see no actions to take, but also because Yeah, uh you know. unavoidly is gonna be a huge part of all of our lives and careers. Yeah.

1:59:12 Yeah, thank you. And that that's a good way to To say it. It's gonna matter a lot. It's gonna it's gonna be everywhere soon. And um You need to do something about it before it's too late.

1:59:22 What about AR future project? That's our organization. We spent a year writing A twenty twenty seven after I left OpenAI, and then we spent another year writing A twenty forty plan A. Daniel, thank you. Thank you. Thank you for all the work that you do. I can see how much you care about this stuff and it's your care. It's funny, care itself makes others feel care. And um seeing how personal this is for you and seeing how much you've dedicated your life to this, but also hearing that you you basically walked away from two million dollars to be able to speak to the public about this information is incredibly admirable. And uh

1:59:53 I I think voices like yours are more important now than they've ever been on this subject. So please do keep fighting the fact that you're fighting. And that's one of information, it is of honesty, and it is uh of saying what what is often the quiet part out loud. Uh doing really, really smart research. I'll link everything we've t discussed today below. Um and I hope we can chat again sometime soon. Thank you.

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