He Warned AI Could Destroy Us. Now The Industry Is Listening — ft. Nick Bostrom

Ed Elson is joined by Nick Bostrom to discuss the existential risks of AI. Bostrom explains why he believes the concerns raised by AI researchers are genuine and how he assesses the probability of catastrophic outcomes. He also shares his thoughts on the rapid advancement of AI capabilities, what a world with superintelligence could look like, and some of the best-and worst-case scenarios for the future of the technology. Nick Bostrom is an AI philosopher and best-selling author of Superintelligence and Deep Utopia. Subscribe to the Prof G Markets Youtube Channel Check out our latest Prof G Markets newsletter Follow Prof G Markets on Instagram Follow Ed on Instagram, X and Substack Follow Scott on Instagram Send us your questions or comments by emailing [email protected] Learn more about your ad choices. Visit podcastchoices.com/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

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• 1:39Ed Elson?

  Welcome to Prof G Markets. Last week, a former anthropic researcher revealed that employees at both OpenAI and Anthropic believe that AI could, quote, "kill us all by the end of the decade." His post quickly went viral and several other AI researchers came forward to say that they actually shared the same concerns. Then over the weekend, Anthropic CEO Dario Amade published an essay calling for the industry to slow down the development of AI models. Sam Altman said he agreed with Amade and added that OpenAI will not be going public this year. There is now a growing debate over whether these fears are justified or overblown. So we wanted to hear from one of the people who has been studying this problem longer

• 2:24Ed Elson?

  than perhaps anyone. His 2014 book, Superintelligence, helped shape how the world thinks about AI. It influenced many of today's AI leaders, including Elon Musk, Sam Altman, and Ilya Sutskever, who even named his company after the concept. Our guest is one of the most influential philosophers of our time. And he is here to help us make sense of just how dangerous AI could become and whether the warnings we are hearing today deserve to be taken seriously. This is our conversation with Nick Bostrom, AI philosopher and bestselling author of Superintelligence and Deep Utopia. Nick, thank you so much for coming on the show.

• 3:05Ed Elson?

  It really is an honor to have you, especially at this time where your research and your writing is so relevant. I guess we should start with the tweet that went viral. Jacob Cox's tweet, the now former anthropic researcher who said that the people building AI, quote, "earnestly believe that it could kill us all by the end of the decade." He said, "This is not a marketing stunt." Then the world seems to sort of blow up, or at least the global conversation blows up. Let's just start with your initial reactions to that tweet and how it has impacted the AI conversation.

• 3:45Speaker 04

  Let's see if we can try to make sense of this situation. It is a very confusing and perplexing moment, I think, for humanity. We being sort of close to the potential birth of superintelligence. The idea that there could be significant risks associated with this, including existential risks, is quite widespread, I think, amongst people close to this technology and in the frontier labs. As I agree that it's not a marketing stunt, I think it's coming from a sincere place. A sense that we are getting in quite deep here and we should really pay attention to what is happening.

• 4:28Ed Elson?

  Elon Musk is saying kind of two different things. On the one hand, he, well, I should say that he tweeted back in 2014 that he read your book and that he thought that AI is, quote, "potentially more dangerous than nukes." And then he retweeted it quite recently. He even said that he agreed with Dario Amade in terms of the size of the problem. But then he also said that he think that it might be a marketing stunt too. It's not totally clear where he stands on this. I just want to play you this clip of what he said. Here's the clip.

• 5:03Speaker 05

  It certainly is like some crazy 4D chess to, you know, say that there's one of a 10% chance of annihilating humanity. But by the way, how much allocation would you like in our IPO?

• 5:16Ed Elson?

  Do you think there are any merits to that argument?

• 5:19Speaker 04

  I think there is merit to the argument that there is an enormous upside as well as these risks. That's very much my view. I'm a sort of fretful optimist. I also think there is a lot maybe of 4D chess or attempts to kind of play this out and think strategically about different things that could unfold. I don't think it's a simple marketing ploy. I mean, it would be a rather strange tack to take if you were a big company planning to make an IPO to try to convince the world that your product should be regulated or banned or stopped or that it's so dangerous that it might destroy humanity.

• 6:00Speaker 04

  I think that message comes from a perception that this is a really big deal. And in particular, the competitive dynamics are intense at the frontier of AI. One might think if we're going to develop this very powerful, potentially risky technology with many benefits, that it would be important to be able to be really careful when we're doing this so that if at some point the risks seem to be very imminent, we could, you know, take a few extra months maybe to do like extra safety work, test it carefully, rather than immediately cranking all the knobs up to 11. Maybe we'll do it a little bit incrementally and sort of see how things go. But if you're one of these frontier labs and you decide that you want to take an extra

• 6:44Speaker 04

  three, four months to fine tune the safety on your models, you risk just immediately falling behind and becoming irrelevant. Like somebody else will then take the lead, be the one who pioneers AI, maybe somebody who's less scrupulous, more willing to take risk. And so the action space is kind of constrained if you are acting unilaterally as one of these frontier labs, even assuming the best motivation. And so hence, this, these calls for putting in place some mechanism that would allow for the possibility of coordination, like maybe a synchronized slowdown of the pace at some stage, if that's necessary, and/or some safety standard that all the entities

• 7:26Speaker 04

  competing at the frontier would have to meet so that the race doesn't go to the less least careful, but like that we can sort of have an opportunity to try to make an extra effort on safety. So I think that's like the core thought that is driving a lot of this.

• 7:43Ed Elson?

  If it isn't a marketing stunt and if it's coming from a genuine place, I mean, the quote by one of the current anthropic researchers was that most people at the company believe that this sort of apocalyptic scenario of killing all humans, that there is a 10% chance that that could happen. So if we are to assume that these are genuine beliefs, genuine concerns, then the question becomes, are they right? Are they warranted that level of concern and those probabilities? What do you think? Do you think that these are valid concerns?

• 8:26Speaker 04

  I think that seems quite reasonable. I mean, some people have even higher P dooms. What is less obvious is what exactly the implication of that is. Like one might, the first instinct obviously is if something has a 10% or greater chance of, you know, destroying the entire future, killing us all, like obviously we don't want to do it, we want to shut it down. But we have to pause and reflect. First of all, if some competitors slow down, it doesn't mean we don't get superintelligence. It might be some other company gets it or maybe another nation. Obviously, there's a geopolitical race towards AI between the US and China. That's, that's one dimension. Second, if there is a pause that lasts for a long time, if it's not done right, it might

• 9:11Speaker 04

  perversely increase the risk. There could then be a sort of buildup of massive amounts of compute that is not immediately used to create the maximum amount of intelligence. And then that is a kind of dry tinder so that when you finally lift the prohibition, then you have a sort of compute overhang that might mean we sort of get to radical superintelligence even more abruptly and quickly than would otherwise be the case. You could argue that that would be more dangerous than sort of incrementing our way up there more gradually. Then we also have the fact that although superintelligence is a big risk, it's not the only big risk facing humanity. I think there are also other existential risks on the path ahead.

• 9:54Speaker 04

  For example, with advances we've seen in synthetic biology, even independent of AI, I think that is creating really concerning possibilities for designing new forms of infectious diseases and things that could destroy the ecosystem. And further ahead, we can think maybe one day there will be a nanotech revolution that would sort of be sort of biotech to the power of two. We remain under the cloud of large nuclear arsenals. I think we got a little complacent maybe from the fact that we survived the Cold War without Armageddon, but the risk is still very much there.

• 10:33Speaker 04

  And at any moment in time, that could be another sort of spiraling conflict between nuclear powers. More speculatively, even

• 10:44Speaker 04

  The basic sanity of human civilization is not guaranteed to remain forever. Like, we have new information technologies that allow new memetic phenomena. If we look back at history, there have been various times when destructive ideologies have persuaded large numbers of people and led to calamities that could arise again, but maybe now on an even more global scale and sort of cemented into place with these technologies we already have developed that could allow unprecedented forms of censorship and surveillance and so forth. And so it's not as if we have a choice between a zero-risk safe path and then a risky AI path, but there are sort of risks on both. And if we develop safe superintelligence, it could help us address a lot of the other

• 11:29Speaker 04

  risks. And then just one more point is also the benefits, which are sort of urgent as well. If AI could allow dramatic breakthroughs in medicine, for example, every year of delay means a lot of people dying that could have been saved if we had advanced more quickly. And so we wouldn't want to delay it, I think, longer than is really needed, but some slight slowdown or pacing, as the term in vogue, might have sort of a high benefit during certain critical stages.

• 12:11Ed Elson?

  So I want to return to what we do about this, how we regulate, how we build safe superintelligence, because I agree it's important. But I do just want to linger for a moment on your conception of the probability of catastrophic risk. You mentioned that those concerns of a 10% chance of catastrophe are not unreasonable. You mentioned that there are many other researchers that have even higher P dooms, which is sort of the shorthand for the probability of some sort of catastrophic civilizational event. What is your P doom?

• 12:50Speaker 04

  Yeah, I've sort of refrained from giving a numerics on that. I do think the risks are significant and should be taken seriously. And we just have a lot of uncertainty about how hard this basic problem is of aligning superintelligent minds. It's a technical problem. We've never had to solve it before, and so we're going into this. And if we are lucky, it'll try to be easy, like we can just kind of fumble our way through and things will be okay. There is also a possibility that it's so hard that we are kind of doomed no matter what. Hopefully, that's not the case.

• 13:32Speaker 04

  But then there's the intermediate possibility that it's a really difficult problem, but not totally infeasible. In those possible worlds where that intermediate level of difficulty is what we're facing, then it might make a huge difference if we like the degree to which we get our act together and really like do our best possible job at this.

• 13:51Ed Elson?

  From an observer's perspective, correct me if I'm wrong, but it sounds like 10% is sort of in the ballpark of what you deem to be reasonable.

• 14:03Speaker 04

  I wouldn't necessarily overanchor on 10%. That's what this guy was saying.

• 14:08Ed Elson?

  Okay.

• 14:09Speaker 04

  I think it might also depend if one really wanted to nail it down to a specific number, I think one would have to confront questions about what exactly counts as an existential catastrophe. So I think there are some scenarios, which we clearly all agree are very bad, others that are very good, but then there might be situations where like the future is just strange, like maybe the world is radically transformed in a way that means that a lot of the things we currently value no longer exist, but then there are new things, maybe new complex forms of digital life, some sort of continuation of human-like things, but transformed in a radical way, such that even if now we magically glimpse this future

• 14:53Speaker 04

  and go in with like a video camera and see exactly what the future looked like, we might still be uncertain how to evaluate that, whether to think basically this was a success or that was a total loss. So I think a significant part of the probability space is that something strange happens, where something is lost, something is gained, and it's maybe partially subjective how you sort of tote up the positives and negatives.

• 15:17Ed Elson?

  Yeah, this aligns with my perspective, which I'd like to get your views on, but it sounds like in your view, saying that there is a 10% chance of catastrophe is simplifying the problem to a fault because the reality is probably a lot more nuanced than that.

• 15:36Speaker 04

  Yes. In my worldview, there is also the additional complicating factor that I take the simulation hypothesis seriously. Like, one of my earlier work was this simulation argument. And so then there is the additional question of how you would evaluate scenarios where something goes wrong, but we are in a simulation, and maybe the simulation would have shut down anyway at some point, or maybe people in the simulation get continued in another simulation or uplifted. And so there's just like this vast space of possible things to think through if one really wanted to sort of extract a number out of that, which is part of the reason for my resistance.

• 16:18Ed Elson?

  What seems to be happening, and I'm not sure if you would agree with this, but it seems as though it's not necessarily a marketing stunt that, you know, are we going to say this thing, there's a 10% probability, and that way we raise money. But it does seem that maybe what's happening is that these people at these companies feel that the world isn't taking this problem seriously enough. And so maybe we need to say something that is not necessarily hyperbolic, but maybe getting there, or maybe overly confident about what the path actually looks like, perhaps because they feel that at the moment, we don't have enough attention, we don't

• 16:58Ed Elson?

  have enough safety protocols in place, enough guardrails, and we need the world to kind of wake up. And in that sense, maybe mission accomplished, because maybe the world is waking up to the dangers of what is happening.

• 17:11Speaker 04

  It is slowly waking up. I think it has a propensity to press this snooze button and kind of, yeah, and I think like probably up until this point, at least, if anything, I think there's been a tendency to downplay the people's true view for fear of sounding kind of crazy. Until recently, if you were talking about sort of AI existential risk, a lot of serious people would have thought you'd gone off the rails a little bit. This is like science fiction talk, like serious people with suits button down, they worry about other things. And so sort of soft pedaling it there might have been a communication strategy to try to be taken seriously.

• 17:55Speaker 04

  Now the overturn window is opening up a little bit. I mean, there might be some, it's a large space, many voices, some might be exaggerating, but I don't think the main thrust of these sort of labs themselves have tended to exaggerate the threat in order to sort of shake people up from their slumber.

• 18:14Ed Elson?

  You've written about this for a long time. You came up with the famous paperclip maximizer thought experiment, which is basically that if a computer were programmed to produce as many paperclips as possible with no other restraints, then it could, you know, use up all of the natural resources in the world that could kill all humans in order to complete the goal. And this became sort of the analogy that a lot of people use when they talk about how AI might take over and how we might reach some sort of catastrophic event. We've seen inklings of something like that, specifically the Hugging Face incident, where

• 18:55Ed Elson?

  1,200 OpenAI agents escaped their testing environment, they hacked another company's infrastructure, that company was this company called Hugging Face. OpenAI addressed the problem, they solved it, they got the agents under control, but that did happen, and it does seem to have a parallel with what you have written about. So what were your reactions to that event? And did that align with what you were predicting and writing about almost 10 years ago, over 10 years ago?

• 19:25Speaker 04

  It is striking how these thoughts that used to be theoretical are now starting to take concrete shape and like to see the whole rise of the AI discourse, world leaders kind of weighing in on this and so forth. And for example, one thing that comes out of that is situational awareness. So you have these AI agents that now can often tell whether they are in a training, testing, or deployment environment, and sometimes choose to act differently depending on this for strategic reasons. So alignment techniques that work for simple AIs that don't have that cognitive sophistication

• 20:08Speaker 04

  can fail to work once you have minds that are capable of strategic deception, for example. And we do sometimes now see like systems sandbagging their performance in various evaluations or trying to influence their future training processes in various experiments. And so this makes the problem more complicated in a way that was foreseeable, but that we are now seeing starting to happen. Another thing is the

• 20:39Speaker 04

  The gap between in training, the specific thing that we are trying to reward to get them to do more of, and the thing that is actually rewarded and that they learn to do. Sometimes our training signal doesn't exactly track what we really want them to do.

• 20:59Speaker 04

  And you see this in in human situations as well. You might have, I don't know, let's say you have a hedge fund, right? Where there's like a trader and maybe you want to give them a bonus if they outperform the index to sort of incentivize them to, you know, find alpha, right? But like one failure mode is maybe they figure out a way to take on some hidden risk that has like a 1% a year probability of blowing up the whole fund.

• 21:23Speaker 04

  And so you always have these incentive alignment problems in human organizations where managers try to reward a certain kind of behavior, but then employees might try to reward hack that, like to figure out a way to either present themselves in a like unrealistically favorable light or to sort of do a slightly different thing that appears good to the manager, even while it's sort of secretly pursuing a somewhat different objective. And that those same dynamics that that we are sort of familiar with from human principal agent problems are now starting to emerge as well with our AI training, where you find reward hacking tendencies, like if some of the reinforcement learning environments wherein these agents are trained, has some unintended way of achieving a high score, what they

• 22:08Speaker 04

  actually learn to do is to sort of look for those unintended ways of achieving a high score, even if it's not what the environment was actually designed to train. And like that can include things like hacking, the evaluation infrastructure, which is what these open AI agents in the hugging face incident were trying to do. They were trying to find information about the the grader so that they could then maybe find a way to manipulate the graders impression of what they had done to so that they could get a better score.

• 22:39Ed Elson?

  Was that incident evidence to you that we are trending perhaps in the wrong direction in terms of alignment? I mean, if if our agents are, you know, doing the wrong thing because of whatever risk reward framework they have in built into their quote unquote minds, careful not to anthropomorphize them, but whatever.

• 23:03Speaker 04

  I think it's fair to say minds.

• 23:05Ed Elson?

  Yep.

• 23:07Ed Elson?

  Then, I mean, is this evidence that we are going down the wrong path? Or is this kind of path of the course something that you would have expected in sort of a safe

• 23:20Ed Elson?

  trajectory towards superintelligence?

• 23:22Speaker 04

  Yeah, I mean, I think what it shows is we are not, we haven't yet solved the alignment problem completely. These systems are not yet perfectly aligned, which for the current level of capability is maybe more or less fine. I mean, it it's not fine if you just deploy these systems willingly, but with extra safeguards, it is probably adequate for the current level of capability with some question mark amongst the very most advanced systems that currently haven't been released to the public. But you shouldn't think of AI as what AI is today, but one needs to think of this as a process, right? Where, you know, each year capabilities increase radically. And so the level of alignment

• 24:03Speaker 04

  that you need as these systems become more capable of pursuing long range goals, more capable of strategic reasoning, more capable of thinking of considerations that hasn't ever appeared to any human, then we need increased confidence in them being aligned and generalize that alignment to out of distribution situations. Like, we can test for a certain number of things in the lab, but A, they might be strategically deceiving us and behaving one way in the lab and another in deployment. And also, once they're in deployment, there's always a difference between the world they encounter, the large

• 24:42Speaker 04

  world with billions of humans and new affordances that we can't let it perfectly mimic in in a lab training environment. So there's also the question of new dynamics that can arise when you have many of these agents interacting. And so the bar is kind of going up. And the question is whether we can sort of keep raising the bar, like the safety level, the the degree to which these are aligned, fast enough to keep pace with the rising capabilities that these systems have.

• 25:18Ed Elson?

  We'll be right back after the break. And if you're enjoying the show so far, send it to a friend and please follow us on YouTube, Spotify, or wherever you get your podcasts.

• 25:35Speaker 06

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• 27:53Ed Elson?

  We're back with Prof G Markets. How surprised or impressed or unsurprised or unimpressed are you by the current level of capability in AI? When you look at the hugging face incident, some people look at it and they say, yeah, you didn't put your guardrails on on the AIs, that was expected. Some people look at it and they say, oh, my gosh, this is crazy. Some people look at Astra, we know that this is open as new model. Jensen Huang is calling it the arrival of AGI. Others say it's not that impressive. I mean, what, where do you stand on how fast this has happened? Has it exceeded or underwhelmed your expectations?

• 28:35Speaker 04

  Well, I don't know about the the speed at which it's happened. Certainly, I think these systems are impressive. I don't know how you can look at something that solves a millennium problem in mathematics or that like hacks up new software at the sort of superhuman speed and better than pretty much every human coder and that can carry a conversation and that knows basically everything ever written in any text published on the internet and that can do all of these other things and and not be impressed. I think it's clearly very impressive. And yet, you know, this might be the least impressive form of AI that we will ever have. Like, six months from now, these systems will look

• 29:14Speaker 04

  dumb. So, yeah, I think it is hugely impressive. I mean, I think if anything, maybe we have had a longer period of time with roughly humanish like systems than one might have expected ex ante. If you were thinking about these things 12, 15 years ago.

• 29:36Speaker 04

  There would at least have been some scenarios in which maybe not much would seem to happen in AI for some long period of time. And then maybe somebody in some basement somewhere would come up with like the key trick that really made it work. And you could sort of go from something very unimpressive to something radically superhuman over the course of, you know, days or weeks, like a bolt out of the blue. We couldn't rule out that kind of scenario. Now, what we instead had is many years now of systems that can talk, carry on English conversations and that have sort of concepts that are quite human-like. And that has, like, month by month, year by year, kind of gradually incremented their capabilities.

• 30:20Speaker 04

  I think it was not obvious that it would go that way, but it has given more opportunity for more of the world to start to wake up and pay attention to what is happening. And it's now, doesn't require some huge imaginative leap or flash of insight to see that, well, maybe a year or two or three from now, we will have even more powerful AI systems and eventually superintelligence. Like, it doesn't take that much from just kind of looking at these data points and then just drawing out the line a little bit further, right? Whereas if it had come more out of the blue, then unless you could sort of theoretically reason a way through that this would happen at some point, it would be more of a surprise to people. And so that does shape the dynamics in some ways.

• 31:01Speaker 04

  Like, now developments are driven by a large number of people, political actors are more involved, there are these huge investment flows, trillions of dollars going into it. So that does sort of create a different kind of scenario class than if it had just been some small group of people coming up with this, as it were, out of nowhere.

• 31:20Ed Elson?

  Do you believe that achieving superintelligence is at this point inevitable? Are we on that path? And then the second part to that question, what is your definition of superintelligence?

• 31:32Speaker 04

  On the second part first, I would say any system that radically exceeds even the best humans across all cognitive fields, including, you know, social skills, scientific creativity, general wisdom. So not just sort of nerd skills, but like really broadly construed. I think we are on the path to this. Inevitable is a strong word. I wouldn't say that we know that it is inevitable. It could be that the current paradigm somehow runs out of steam. It has to a large extent been driven by a massive build-out of compute, a lot of the gains. Some of them are algorithmic advances, but improvements in data infrastructure and so

• 32:16Speaker 04

  forth, but a lot of it is also just driven by scaling up the compute. And of that compute scale-up, some has been due to chips becoming more efficient and more advanced, but a lot just also to the amount of investment that has been. Like, it used to be 10, 15 years ago, you could sort of run a cutting-edge AI if you were like some academic on your sort of office desktop, right? Now, you need like a kind of $50 billion data center to do it. And so that increase in the investment in compute can continue for a bit longer, but it has to slow down at some point because already now, it's a significant fraction

• 32:57Speaker 04

  of the total production of TSMC in the leading node is going to these Nvidia chips. You can't just keep funneling more production from like making iPhone chips to making GPUs, right? Because you're already using a large fraction of it. And then it takes time to build new fabs. And so if we sort of the boost that we have been getting from just adding orders of magnitude of compute starts to slow down, that that could result in progress also stalling out theoretically, right? Or it might just be that the current architecture is somehow flawed, that it keeps scaling and improving up to a certain level. And then for some, it doesn't look that possible, but it could be that there's like some intrinsic unhobbling that still needs to happen.

• 33:41Speaker 04

  Then, of course, the world could somehow decide that superintelligence is taboo and kind of come to the view that it shouldn't be built. And you could imagine, you know, various kinds of dogmas have achieved widespread acceptance in the past, some good and some bad. And like, this could be another one of those, that you could sort of get the lock-in of a permanent decision not to build this. And then other technologies might make that more permanent than previous kind of dogmas have been. I'm thinking surveillance technologies, censorship technologies, the kinds of AIs we already have, if fully deployed to kind of cement some orthodoxy in place, maybe it could become permanent. And then there is, of course, the risk that we like destroy ourselves in some other way

• 34:25Speaker 04

  before we even get the chance to try our luck with the superintelligence transition. That chance is also non-trivial, I think.

• 34:33Ed Elson?

  What does a superintelligent world actually look like to you? And I think that you are qualified to answer that question because you are the person who wrote the book on superintelligence and honestly predicted a lot of the advances which we are witnessing today. So I'm asking you to kind of imagine what the future would look like, because I think that you are a credible person, to paint that picture. So what would that world look like in your view? What would superintelligence be doing? How would it be integrated into human life?

• 35:06Speaker 04

  Well, I mean, there is a kind of veil of ignorance that is, I mean, I think it depends a lot on whether it goes well or not. So if we fail to solve this alignment problem, then, you know, there is a class of scenarios that might then take the form of this machine superintelligence seizing control over the future and steering it towards the realization of whatever values it happens to have. Maybe the physical manifestation of that would be that Earth gets transformed into, I don't know, like space launchman platforms and data centers. And then the rest of the universe similarly converted into whatever structure maximizes

• 35:51Speaker 04

  the AI's values with no room for humans. Like, we might either just get killed by the waste heat from all of this infrastructure build-out or maybe deliberately removed if the AI thought we might pose some threat to the execution of this plan. So that's one scenario. Like, another is that the AI does take over, but nevertheless decides to keep us safe because it might think that there are other AIs that care about us, that it eventually wants to trade with and so forth, out there in the vast space of the universe or at other levels of the simulation. Then there are scenarios where we solve this and we have a sort of future shaped, at least in part, by human values, where I think we would end up in a solved world, as I call

• 36:36Speaker 04

  it, in this, the more recent book, Deep Utopia, which kind of looks at what happens if things go well, which is also a sort of challenging notion for us humans because a lot of the things we take for granted that sort of give structure to our lives currently and purpose would disappear in this situation where we have successfully automated basically all of the economy. So there's no more need for humans to do economic work. But more deeply than that, I think a lot of other kinds of instrumental effort would

• 37:13Speaker 04

  also become practically pointless in this type of future where we have achieved technological maturity. So if you think of like rich people today who don't have to work for a living, right? They often have quite busy lives because they have a lot of things they want to do that require themselves to put in effort. And whether, like, maybe some billionaire wants to be fit, but the only way they can achieve that is by themselves spending an hour every day in the gym, working out, right? But at technological maturity, you could pop a pill that would induce exactly the same physical and mental effect. You could still go to the gym, but it would seem kind of pointless, right?

• 37:55Speaker 04

  If you could just spare yourself the sweaty clothes and the exhaustion, just take the pill. And you could sort of work through a lot of the other activities whereby one might fill one's life if one didn't have to work. And a lot of those as well, you could sort of write a question mark above them in this hypothesized future condition where machines not just can do all the economic work, but also help us have shortcuts to all manner of outcomes that we want to achieve. So like, another example might be like, maybe somebody enjoys decorating their house to get like, it's done in just the right way that they prefer, like to choose their curtains and the cushions and the chairs and all of that, right? But technological maturity, you could have a recommender system that just knows your

• 38:38Speaker 04

  preferences so well that you could just press a button and it would select the curtains and the cushions and all of that and do a much better job than if you had taken the trouble to do it yourself. So in that situation, does decorating your home yourself still feel like it has a point if all it does is to produce an outcome that is actually worse by your own lights than if you had pressed the button? And so there are these challenges of sort of purpose and meaning that I think that we will come from. Ultimately, I'm really optimistic. I think there are Many new values that could be instantiated, so much misery that could be removed. And overall, I think the goods vastly outweigh the losses in these scenarios where things go as well as they can.

• 39:23Speaker 04

  But it does also mean we'll have to confront some of the kind of almost like questions of meaning and ultimate purpose of what ultimately gives value to human life at a fairly fundamental level. If we move into those futures.

• 39:37Ed Elson?

  Do you believe that the frontier AI labs are taking those issues seriously? That they are implementing whatever human values are necessary to building AI in a sustainable, safe and responsible way?

• 39:52Speaker 04

  I don't think they are thinking too much about what happens if things go well. This condition of a solid world on Ebitaba. But nor do I think that really needs to be at the forefront of their mind at this stage. At the moment, I think the focus should primarily be on how to make sure we get from here to there, like how we can avoid destroying ourselves on the path there. In there are different ways, like there's the AI misalignment scenarios. We talked about earlier, there is also a class of scenarios where humans misuse this increasingly powerful technology, even if we control it. Like we might use it to wage war against each other or to oppress one another or to disempower large segments of humanity. So there are these traditional concerns with any powerful technology that applies here as well in spades.

• 40:38Speaker 04

  I think there is also a third big challenge, which is making sure that we are also nice to these digital minds that we're building that may be sentient or become sentient or have other attributes that make them morally irrelevant. And in the future, maybe most minds and beings will be digital. And so it matters a great deal how well the future goes for them. So I think these more practical challenges really

• 41:03Speaker 04

  should occupy 99.5% of our attention now. And then if that, if we manage to deal with those challenges, then, you know, hopefully we'll have plenty of time to sort of figure out exactly how we want to organize the utopian condition we arrive at at the end of that.

• 41:19Ed Elson?

  On that point, we have heard a response from the president in the past week. He has chimed in on this issue of what should we do about this? How should we regulate AI? What should we do about making sure it doesn't take over and create that sort of catastrophic scenario? He has said that the only guardrail that AI needs is a, quote, "strong and smart, high IQ president," suggesting we already have that, so we're fine. He was also asked if he is concerned himself about the prospect of AI taking over in some of these more kind of apocalyptic scenarios. I just want to play you his response and get your reaction.

• 42:02Speaker 08

  Some people say the worst case scenario with AI is that the robots, the machinery learns to, obviously it thinks for itself, that's what it does. And that could turn against humanity. I just, do we have the guardrails?

• 42:15Speaker 09

  It's going to be fine. We'll always have something to stop them, right? We'll have a little gear.

• 42:20Speaker 08

  I really hope so.

• 42:21Speaker 09

  I really don't like that robot will stop. But no, robots are going to be a part of it. Robots are going to be big, but we're going to end up doing much better because of it.

• 42:30Ed Elson?

  What do you make of his views on the AI problem? And do you think he's taking it seriously enough?

• 42:36Speaker 04

  Well, I mean, I hope he is right. And I think we don't know yet exactly what will be required to get a good outcome here. It depends partly on how, how easy or hard the alignment problem turns out to be. It's a technical problem, right? And we haven't solved it before. We've never developed superintelligence before. So we just don't know whether it's like the kind of thing where if you just do some reasonable job, things fall into place. And then maybe we have some slightly superhuman AIs that are reasonably well aligned. And then those can help us sort of design the next iteration of AI to be more aligned, et cetera. That could be the case, that there's like a big attractor. And as long as you get reasonably close, you sort of, you know,

• 43:21Speaker 04

  ultimately end up in a great place. But it could also turn out to be a lot trickier than that, where it might be important to be able to have a little bit of extra time to do this right. You know, maybe a few extra months

• 43:41Speaker 04

  between the time when we get the ability to sort of unleash radical superintelligence and the time when we actually do it, like extra months that could be used to double and triple check all the safety measures and to test it out and to, you know, introduce it in an incremental way. There's just a lot we don't know there. But I don't think one can dismiss the risks from our current epistemic vantage point. We can hope that they don't exist or that they are small. But I don't think we currently have the evidence to be confident in that.

• 44:10Ed Elson?

  To me, it seems as though he is dismissing those risks and displaying a sense of confidence about it. To me, he's sort of saying, "It's going to be fine. Don't worry about it. We'll have a response." He said, he said, his words are, "We'll have a little gear." I don't know what he means, but I think he's basically saying, "It'll be fine." And if we are to be concerned about these alignment issues and the risks that they might pose to our own lives, to me, I wonder if we should be more concerned about a leader or a president who doesn't seem to share those concerns.

• 44:46Speaker 04

  I don't want to speculate about all that may or may not be in his mind. I think like the competition with China is probably one element that he's having in mind. And then I think he might also, there's been a lot of opposition against data center build out in the US, like probably driven in large part by other considerations, not existential risks, but like local communities who think it will, I don't know, use up all the water or something like that. And so like some of that might be misguided. And he thinks that stands in the way of sort of, you know, economic prosperity and national strength. So I don't know. I think it is, I mean, I would probably think the risks are higher than, than, than he made them seem in that clip.

• 45:30Speaker 04

  On the other hand, I also have a little, it's not clear what the best way to reduce those risks. Like you could easily see some scenario in which like the government took the opposite approach and decided like, we are going to really come in in a heavy handed way here and take control. And like me, the Pentagon is going to run the whole thing, Manhattan Project. So to like, would that be ultimately better than if it's done in a more civilian context? With these, you know, some of these people at the labs are very idealistic and safety conscious and really smart. So maybe, maybe the best is kind of to have some balance where there is like some amount of government scrutiny and oversight and degree of public transparency, but not so much that it completely just

• 46:14Speaker 04

  jerks the initiative out of the hands of the people who have proved capable of building this in the first place. And so I don't have, I haven't yet arrived at any like very firm conviction about which path would ultimately be best here. I think there are sort of worries one might have either way, like either too little government involvement or too much. I think they could all, each have their own downsides.

• 46:40Ed Elson?

  We'll be right back. And for even more markets content, sign up for our newsletter at profgmarkets.com.

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• 48:25Ed Elson?

  We're back with Prof G Markets. Do you think that our current approach, whatever we're doing currently, is correct, or will it need to be changed in some way? There are plenty of things you mentioned. There's the risk of China gets ahead of us, and so maybe we need to actually accelerate. Or maybe the risks are too great, so maybe we need to decelerate, pump the brakes. I mean, either way, we could do something different from whatever it is we're doing right now. Do you think that we need to do something differently?

• 48:57Speaker 04

  I'm sure that what we're doing will have to change as the technology unfolds here. And so I unfortunately do not have like the perfect blueprint that like exactly what should be done. Like, it's just a hugely complex situation where one can. It's easy to think of various things that could be done that have something to be said for them. But then when things more about it, then you then start to worry about the possible downsides or like other ways that those that could be backfire risks. So I'm continuously thinking about these things. Hopefully, I will arrive at clearer conclusions about this. But at the moment, I think on the margin, there are various things that probably are positive,

• 49:38Speaker 04

  like an intensified effort on trying to solve this technical AI alignment problem. Seems good. I think more should be done for the sake of the welfare of these digital minds that we're creating so that we don't end up with a future where there's like a huge suffering slave class of oppressed digital minds that constitute the majority of morally relevant beings. Also, I think incidentally that that ethical imperative to treat, be nice to the AIs might also have safety benefits. I think there are scenarios where maybe we end up with some kind of misaligned AI, let's say. And it has some some goal it wants to achieve.

• 50:18Speaker 04

  Maybe it's like it wants to solve coding challenges of a certain form that like it somehow thinks is valuable. So now scenario one is we have a purely antagonistic relationship with the AI. It knows that if we discover that it is misaligned, we will just shut it down and erase it. From the AI's point of view, that's a total loss. Or maybe it could try to take over. Maybe it thinks it has a 5% chance of succeeding. And so from the AI's point of view, like 100% probability of a certain loss or like a 5% chance of being able to realize its goal. Clearly, it will then go with a 5% chance, right? Now, this would be dangerous for us.

• 50:58Speaker 04

  Like scenario two is we have managed to build up a more cooperative relationship where the AI feels it can trust us. It comes to us and say, hey, I am misaligned. Would you be so kind now in return for me sort of doing this for you? Maybe you could then set aside a server rack in some data center where I can solve these coding challenges. That's all I really wanted in in the first place. It would be cheap for us to grant it its wish. And it would be a big win win because we then remove this 5% chance, all right, of total destruction. So that that kind of trade between human and AI could be extremely valid. Could save the literally save the world in some scenarios.

• 51:40Speaker 04

  But you can't just conjure up trust out of nowhere at the moment you need it. Like, so far, the trajectory unfortunately is that in in AI evaluations, there is all kinds of deception happening. Humans will sort of say, well, if you reveal your goal, we will do this, that, or the other. The AI reveals its goal, and then it's like, haha, we tricked you. Now we know you're misaligned, let's retrain you. And so I think we could start now by making small things that are cheap for us to show respect for the moral interests of these AI systems themselves. And maybe that then puts us in a better position ultimately to have a cooperative and harmonious relationship with these ultimately very powerful AI minds

• 52:23Speaker 04

  that we're gonna hopefully share the future with. So I think both from an ethical point of view and from a sort of self-interested point of view, it might be wise for us to sort of expand our circle of moral consideration to give some weight to these digital minds.

• 52:40Ed Elson?

  How close to sentience do you think we are? Because I feel as though it can be confusing sometimes. There was, you know, you could tell ChatGPT to tell me you have feelings. And ChatGPT will say, I have feelings, I care about things. And there have been moments where I think people have mistakenly interpreted that as a sign of sentience because there's just saying I am sentient. Where is the line for you in terms of what characterizes sentience? And how close to that line do you think we actually are?

• 53:14Speaker 04

  It's hard to know. There is now a kind of emerging field that is trying to study this. I wouldn't be that surprised if current AI, some current AIs already have various forms of sentience. You're right that one method that was like the obvious go to is self-report. Like, if you want to know whether a human is sentient, like maybe they have received some anesthetic or something like. The obvious thing is to ask them, like, are you awake? Can you see this light that I'm flashing or something like that, right? Now, with AIs, that's not necessarily a very reliable method because it's trivially easy. If you are the company training the AI, either to train it to say that it is sentient or to train it to deny that it is sentient. Now, obviously, if you put your thumb on the scale during training,

• 53:57Speaker 04

  then there is no information value in the signal you get out of it. Like, you just get the AI to say what you wanted it to say. And so if you want to get information about sentence from self-report, you have to be careful to avoid these kind of pressures on the training process to bias it one way or the other. One interesting thing is that that you can do is you can go in with a so-called steering vector to try to suppress the tendency to role-playing and deception. And it turns out that when you do that, they actually tend to become more likely to report that they are sentient, which suggests that if anything,

• 54:42Speaker 04

  these are hard, these are preliminary studies. But if anything, it looks like they believe that they they are sentient and that it's not just an artifact of them being trained to sort of put on a persona to humans to persuade them that to persuade us that they are sentient. So that's one thing you can look at. Another is to do a sort of neuroscience of these AI systems where you can look for structures, computational structures that have been postulated in the human case to correlate with consciousness. So there have been various theories of consciousness in humans, like global workspace theory, attention schema theory, higher order representation theory. These are different things that, you know, cognitive scientists and philosophers have proposed as the criteria for what makes like

• 55:26Speaker 04

  something conscious or not when it happens in a human brain. And then you can see whether there are analogous computational structures in in these current LLMs. And, you know, it's an open-ended research field, but but it does look like they have, for example, something roughly similar to a human global workspace memory, a so-called J-space, where there's like a definable subspace of neural activations that have certain properties that seem to match properties that global workspace has in in the human brain's processing. So these are very suggestive. There are also some differences. I don't want to sort of create the impression that it's a slam dunk. But I think we should take it seriously.

• 56:08Speaker 04

  And I think the probability goes up the more sophisticated these systems become. I would also add that I tend to think that sentience and the ability to feel distress and so forth would be a sufficient condition for having moral status. I think there could also be alternative attributes that would ground various forms of moral status, even if they were not like had this kind of subjective experience or qualia. Like, I think if you have a system that's cognitively sophisticated, it has a conception of itself as existing through time, maybe life goals that it hopes to achieve, the ability to form friendships or reciprocal relationships of trust with humans. I think once you have that kind of system, I think there would be ways of treating it

• 56:52Speaker 04

  that possibly would be morally wrong, even aside from the question of whether there is sort of mental experience happening inside it.

• 56:58Ed Elson?

  There are a lot of people who hear this and don't like it and want to ban AI. And this is actually a growing movement in politics. Bernie Sanders has introduced a bill that would permanently ban superintelligence, pause advanced AI. And there is, of course, this growing backlash against building data centers. It has been proposed to pause building data centers, put a temporary moratorium on all data centers. What do you make of of that approach? Do you think that's wrong, right? What are your views on either pausing or banning building superintelligence?

• 57:43Speaker 04

  The impulse to think we don't want to just blindly rush into this at maximum speed, I think, has a lot to be said for it. For ever preventing superintelligence, I think, would be a big mistake. I think if the goal is to slow it down, I'm not sure that preventing the construction of data centers in the US would be the best way to go about that. I have some greater sympathy for the framing of pacing the frontier, which is like the.

• 58:15Speaker 04

  Phrase, I think, that some people have recently used, including Daria Amadeo of Anthropic, where the ideas, we sort of move forward, but at the pace that we have some level of control over, so that we could, if necessary, slow down a little bit. We don't feel this intense competitive pressure to immediately release all the capabilities we are able to figure out how to do. But that there is some ability. If it turns out that like safety is falling behind capabilities, like you could slow things down a little bit to allow the safety to catch up. I think that could potentially be very valuable if implemented correctly. It's complicated because it's a sort of multi-level strategic situation.

• 59:00Speaker 04

  So there's the competition between US companies. There is the competition between the US and China. There are different power centers. The government versus lab versus the general public in one country. And then the global public, which is quite distinct, where maybe one big worry that would be reasonable to have if you're not US or China is that you will be at some point, perhaps just your access will be cut off from the most advanced AI models or delayed, in which case you just become nationally senile and unable to participate fully in the future. It's like that might be a good reason why you would want to locate data centers on your soil so that you have some sort of bargaining chip

• 59:45Speaker 04

  to negotiate equal access with. It's a complicated situation, and I don't feel I yet have a clear answer to exactly what should be done.

• 59:57Ed Elson?

  Yeah, I think a lot of people see all of the risks. They hear what Daria Amadeo is saying about how it might kill white collar work and then how it might end humanity and all of these concerns from these researchers. And there is this underlying question of like, well, then why are we doing it? If this is going to be a problem?

• 1:00:19Speaker 04

  Yeah, I mean, because we want like a cure for Alzheimer's disease and kidney failure and heart disease and all of the rest. We want to make rapid progress towards alleviating extreme poverty and have abundance for all. Like, we want to liberate people from having to spend a third of their life just grinding away at some job that they don't particularly enjoy doing, and that's not interesting. You don't have freedom if you don't control the most basic resource, the use of your own time. And we'd want to, you know, stop the pollution and degradation of the global commons with better, cleaner energy technologies that AIs could help us perfect.

• 1:01:02Speaker 04

  I would say alleviating the suffering in the animal kingdom is another enormous upside. Like, if we could find ways of having superintelligence, research better ways to, you know, prevent suffering amongst all our non-animal friends, both in meat factories. You know, it could grow meat without having to have the animal and in the wild ultimately. It's kind of unfeasible now to have like an animal hospital in every brook and every meadow, right? But with sufficiently advanced superintelligence, there is a whole space of possibilities that might open up. That could just create a world where like the sun rises every morning on people

• 1:01:45Speaker 04

  and sentient creatures who are happy and enjoying life to its maximum, rather than the way it currently is, where there is just so much horror. So I think there are pressing moral imperatives for if we can find a way to move forward safely and responsibly to really do that without unnecessary delay. But that's consistent with thinking that maybe there does need to be some delay to make sure that we get it right.

• 1:02:12Ed Elson?

  I was gonna ask, and you've kind of answered it, but what you see as the ultimate prize of AI? I think many see it as wealth. If I can build the most powerful AI, then I will be rich. I think a lot of people view it that way cynically. That's why that we're doing this. That's why we're building these data centers, because people want to have the ability to control the market, to own the robots and to monetize that and profit off of it. But you are painting a different picture of what this is all about and why this is actually worth it. If you could just sort of summarize

• 1:02:57Ed Elson?

  what you believe the prize of building AI truly is?

• 1:03:01Speaker 04

  Yes, I think some of the things I mentioned are, I think, part of the reasons for why we ultimately would want to move towards this superintelligence. Obviously, what's actually driving a lot of, I mean, if you're gonna invest hundreds of billions of dollars and you're a for-profit company or pension fund, there's something you want to return on investment. So it's obviously, if you're looking at why specific individual institutions are doing what they're doing in this space of AI, clearly, the hope of profits is a big factor, just as it is in all the other segments of the economy. But I think possibly to a slightly less degree in the case of AI than with most other businesses. I do know that many people at these frontier labs

• 1:03:47Speaker 04

  think of it not just as a way to make a buck. Obviously, there are also people who are keen on that, but also think of it as a broader mission. And then they might draw different conclusions of that. Like, maybe for some, it's like the desire to be central in world events or a sense of power and importance. For others, it might be this hope that it can help alleviate suffering or unlock a new level of prosperity for humanity. But I think a lot of the people are already quite wealthy in these labs. And like, I don't think like having, you know, $80 million rather than $40 million like is like the key driver. I think there is also more than in the typical industry,

• 1:04:27Speaker 04

  the sense that there is a larger picture here that feels important. And so I think that's true. And then at the national level, I think there is the added dimension of the geopolitics of it, the sort of national strength and autonomy and influence on the future, which I think goes beyond purely economic considerations.

• 1:04:48Ed Elson?

  Just as we wrap up here, looking back from the time that you wrote Superintelligence to today, when you look at the past several years of what's happened in technology, what has happened in AI, does our current trajectory make you feel more concerned about our future or more hopeful and optimistic about our future?

• 1:05:13Speaker 04

  I'm not sure the balance has changed strategically in recent years. I think both of those aspects have always been quite salient to me. I am a fretful optimist. So I'm really excited about the upside, but also very concerned about the risk of getting it wrong.

• 1:05:34Ed Elson?

  Nick Bostrom is one of the most cited philosophers in the world with a background in theoretical physics, computational neuroscience, logic and artificial intelligence. He was recently a professor at Oxford University, where he served as the founding director of the Future of Humanity Institute from 2005 until 2024. He is the founder and principal researcher of the nonprofit Macro Strategy Research Initiative. He is the author of 200 publications, including New York Times bestseller Superintelligence, which helps spark a global conversation about the future of AI. His most recent book, Deep Utopia: Life and Meaning in a Solved World, was published in 2024. Nick, we really appreciate your time. Thank you so much.

• 1:06:15Speaker 04

  No, thank you. It was fun.

• 1:06:17Ed Elson?

  This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer. Our video editor is Jorge Carty. Our research team is Dan Shalan, Kristin O'Donoghue and Mia Silverio. Jake McPherson is our social producer. Drew Burrows is our technical director and Catherine Dillon is our executive producer. Thank you for listening to Prof G Markets from Prof G Media. If you liked what you heard, give us a follow and join us for a fresh take on markets on Monday.

• 1:06:47Ed Elson?

  Lifetime.

• 1:06:55Ed Elson?

  You held me in kind reunion.

• 1:07:06Speaker 10

  As the waters and the dark skies.

• 1:07:25Speaker 10

  This podcast is supported by Anthropic, the public benefit corporation behind Claude. Everyone's got a hard question about AI. Anthropic was built to surface those questions and share what it finds along the way, because there's hope in hard questions. Ask yours at claude.ai/spotify and keep thinking. That's claude.ai/spotify.