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This conflict continuation would last only 45 minutes and have a toll of up to 3. NATO and Russia, following the scenario elaborated by Princeton University, would launch attacks on important economic and population centers to hamper the other side's recovery. Five to ten nuclear warheads would be used for each city. Thermonuclear warfare would kill The study estimates that, in total, a nuclear war would immediately affect The landscape after the conflict would be something like that: Hiroshima in , when an atomic bomb dropped by the United States leveled an entire city. Over , people died and some 70, were wounded. Those affected by radiation would raise the death toll over the following years.

The Princeton University simulation started off from the idea that, in a conflict between Russia and the United States, Moscow would strike with nuclear weapons first. If the United States is the first to start a nuclear strike, the result would be more or less the same. The scenario presented is based on how the NATO defensive strategy is thought out in case of Russian aggression. There really isn't much that can be done during a nuclear war: Everything is programmed and there's virtually no time to stop Armageddon. The idea was that no side would dare to push the button since nobody would win. The phrase is attributed to nuclear scientist John von Neumann, seeing here receiving the Freedom Medal from President Eisenhower in Film buffs might remember The Doomsday Machine from 'Dr.

Strangelove', a Soviet supercomputer that would automatically start a nuclear strike in case the US started a nuclear war. A piece by NPR reveals that such a system was real and that it was still functioning. A relatively more recent example was the John Badham movie 'WarGames'. The premise rests on the tension on how to stop a military supercomputer once it has started to run its attack protocol.

However, life isn't a Hollywood movie, especially when it comes to war. When a conflict begins, it's hard to say how it will end. Just look at recent cases in Iraq or Afghanistan. The threat of the nuclear apocalypse loomed over the s. Are you doing that? What if, like, I say that I have more faith in normal people than you do to toss DNA out the window as soon as somebody offers them a happy, healthier life for their kids? This is evidence for hope. Weird is relative to intelligence. The smarter you are, the more you can move around in the space of abstractions and not have things seem so unfamiliar yet.

No, no, not yet, not now. Keep going. Well, it would be like a weak god who is just slightly omniscient being able to strike down any guy he sees pulling out. Sure, lots of instrumental values made their way into us but even more strange, warped versions of them make their way into our intrinsic motivations. Natural selection regularizes so much harder than gradient descent in that way. Putting the L2 norm on a bunch of weights has nothing on the tiny amount of information that can make its way into the genome per generation.

The regularizers on natural selection are enormously stronger. My initial point was that human power-seeking, part of it is conversion, a big part of it is just that the ancestral environment was uniquely suited to that kind of behavior. First of all, even if you have something that desires no power for its own sake, if it desires anything else it needs power to get there. Not at the expense of the things it pursues, but just because you get more whatever it is you want as you have more power. And sufficiently smart things know that. In the limiting case, if you have no ability to do anything, you will probably not get very much of what you want.

Imagine a situation like in an ancestral environment, if some human starts exhibiting power seeking behavior before he realizes that he should try to hide it, we just kill him off. And the friendly cooperative ones, we let them breed more. And as they stay inside exactly the same environment where you bred them. I can just look out of the world and see this is what it looks like.

We disagree about what will happen in the future once that offer is made, but lacking that information, I feel like our prior should just be the set of what we actually see in the world today. Yeah I think in that case, we should believe that the dates on the calendars will never show Every single year throughout human history, in the Yes, I think we have a good reason to. Sorry, why not jump on this one?

What is an example here? Let me ask you about LLMs. So what is your position now about whether these things can get us to AGI? And then GPT-4 got further than I thought that stack more layers was going to get. And now I do not know. I am no longer willing to say that GPT-6 does not end the world. And my failure review where I look back and ask — was that a predictable sort of mistake? I do think that, in , I would not have called that large language models were the way and the large language models are in some way more uncannily semi-human than what I would justly have predicted in knowing only what I knew then.

But broadly speaking, yeah, I do feel like GPT-4 is already kind of hanging out for longer in a weird, near-human space than I was really visualizing. In part, that's because it's so incredibly hard to visualize or predict correctly in advance when it will happen, which is, in retrospect, a bias. So that kind of recursive self intelligence idea is less likely. How do you respond? At some point they get smart enough that they can roll their own AI systems and are better at it than humans.

And that is the point at which you definitely start to see foom. Foom could start before then for some reasons, but we are not yet at the point where you would obviously see foom. Or does it increase your odds of human survival? Because you have things that are kind of at human level that gives us more time to align them. Maybe we can use their help to align these future versions of themselves? Having AI do your AI alignment homework for you is like the nightmare application for alignment.

Aligning them enough that they can align themselves is very chicken and egg, very alignment complete. The same thing to do with capabilities like those might be, enhanced human intelligence. Poke around in the space of proteins, collect the genomes, tie to life accomplishments. Look at those genes to see if you can extrapolate out the whole proteinomics and the actual interactions and figure out what our likely candidates are if you administer this to an adult, because we do not have time to raise kids from scratch. If you administer this to an adult, the adult gets smarter. Try that. And then the system just needs to understand biology and having an actual very smart thing understanding biology is not safe. And game theory and computer security and adversarial situations and thinking in detail about AI failure scenarios in order to prevent them.

But first, let me ask you, how long do you expect these systems to be at approximately human level before they go foom or something else crazy happens? Do you have some sense? Do you think confirming new solutions in alignment will be easier than generating new solutions in alignment? That all bear out and those predictions all come true. Billion dollars. Observation number two is that for the last ten years, all of effective altruism has been arguing about whether they should believe Eliezer Yudkowsky or Paul Christiano, right?

I believe that Paul is honest. I claim that I am honest. Aliens who are possibly lying. So on that second point, I think it would be much easier if both of you had concrete proposals for alignment and you have the pseudocode for alignment. Let me come back to that. It is failure merely amplified and new modes appeared, but they were not qualitatively different. Well, they were qualitatively different from the previous ones. Your entire analogy fails. Did they even do this to GPT-2 at all? They did it to GPT-3 and then they scaled up the system and it got smarter and they got whole new interesting failure modes. First of all, one optimistic lesson to take from there is that we actually did learn from GPT-3, not everything, but we learned many things about what the potential failure modes could be 3.

We saw these people get caught utterly flat-footed on the Internet. We watched that happen in real time. Would you at least concede that this is a different world from, like, you have a system that is just in no way, shape, or form similar to the human level intelligence that comes after it? When they scaled up Stockfish, when they scaled up AlphaGo, it did not blow up in these very interesting ways. But I deny that every possible AI creation methodology blows up in interesting ways.

We just suck, okay? Well, okay. Let me make this analogy, the Apollo program. We are learning from the AI systems that we build and as they fail and as we repair them and our learning goes along at this pace Eliezer moves his hands slowly and our capabilities will go along at this pace Elizer moves his hand rapidly across. Let me think about that. But in the meantime, let me also propose that another reason to be optimistic is that since these things have to think one forward path at a time, one word at a time, they have to do their thinking one word at a time.

And in some sense, that makes their thinking legible. They have to articulate themselves as they proceed. We get a black box output, then we get another black box output. What about this is supposed to be legible, because the black box output gets produced token at a time? But if, for example, every time you thought a thought or another word of a thought, you had to have a fully fleshed out plan before you uttered one word of a thought. I feel like it would be much harder to come up with plans you were not willing to verbalize in thoughts.

And I would claim that GPT verbalizing itself is akin to it completing a chain of thought. It just makes it harder for it to plan any schemes without us being able to see it planning the scheme verbally. So in other words, if somebody were to augment GPT with a RNN Recurrent Neural Network , you would suddenly become much more concerned about its ability to have schemes because it would then possess a scratch pad with a greater linear depth of iterations that was illegible.

Sounds right? Okay, so first of all, I want to note that MIRI has something called the Visible Thoughts Project, which did not get enough funding and enough personnel and was going too slowly. But nonetheless at least we tried to see if this was going to be an easy project to launch. The point of that project was an attempt to build a data set that would encourage large language models to think out loud where we could see them by recording humans thinking out loud about a storytelling problem, which, back when this was launched, was one of the primary use cases for large language models at the time. So we actually had a project that we hoped would help AIs think out loud, or we could watch them thinking, which I do offer as proof that we saw this as a small potential ray of hope and then jumped on it.

Okay, all right, call back to your interview. Ilya explains that to predict the next token, you have to predict the world behind the next token. Excellently put. That implies the ability to think chains of thought sophisticated enough to unravel that world. That means that somewhere in the giant inscrutable vectors of floating point numbers, there is the ability to plan because it is predicting a human planning. But there is a valid limit on serial death. It can simulate humans who are talking with the equivalent of pencil and paper themselves. Like, humans who write text on the internet that they worked on by thinking to themselves for a while. Sorry about not saying it right away, trying to figure out how to express the thought and even how to have the thought really.

No, no. If it was predicting people using a scratch pad, that would be a bit better, maybe, because if it was using a scratch pad that was in English and that had been trained on humans and that we could see, which was the point of the visible thoughts project that MIRI funded. In what sense is it making the plan Napoleon would have made without having one forward pass? All right, let me just back up here. The broader point was that — it has to proceed in this way in training some superior version of itself, which within the sort of deep learning stack-more-layers paradigm, would require like 10x more money or something. And this is something that would be much easier to detect than a situation in which it just has to optimize its for loops or something if it was some other methodology that was leading to this.

So it should make us more optimistic. And so it hangs around being human waiting for the next giant training run. That is a thing that could happen to AIs. In what ways have you updated your model of intelligence, or orthogonality, given that the state of the art has become LLMs and they work so well? Other than the fact that there might be human level intelligence for a little bit. Okay, but it seems like it is a significant update. What implications does that update have on your worldview? I previously thought that when intelligence was built, there were going to be multiple specialized systems in there. Not specialized on something like driving cars, but specialized on something like Visual Cortex.

Kind of sad. Not good news for alignment. It makes everything a lot more grim. Because we have less and less insight into the system as the programs get simpler and simpler and the actual content gets more and more opaque, like AlphaZero. What is a world in which you would have grown more optimistic? If the world of AI had looked like way more powerful versions of the kind of stuff that was around in when I was getting into this field, that would have been enormously better for alignment. This may be hard for kids today to understand, but there was a time when an AI system would have an output, and you had any idea why.

I know wacky stuff. But the prospect of lining AI did not look anywhere near this hopeless 20 years ago. Elizer moves hands slowly and then extremely rapidly from side to side I quantified this in the form of a prediction market on manifold, which is — By In other words, will we have regressed less than 20 years on Interpretability? How about if we live on that planet? GPT-4 people are already freaked out. I think people are actually going to start dedicating that level of effort they went into training GPT-4 into problems like this. Well, cool. Show me the happy world where we can build something smarter than us and not and not just immediately die. I think we got plenty of stuff to figure out in GPT We are so far behind right now. The interpretability people are working on stuff smaller than GPT They are pushing the frontiers and stuff on smaller than GPT Well, what if it designed its own AI system?

Because it does seem that it would be harder to do that kind of thing with these kinds of systems. It would have to rewrite itself from scratch and if it wanted to, just upload a few kilobytes yes. A few kilobytes seems a bit visionary. Why would it only want a few kilobytes? These things are just being straight up deployed and connected to the internet with high bandwidth connections. Why would it even bother limiting itself to a few kilobytes? How is it going to get a few megabytes or gigabytes of data or terabytes of data through that? It might possibly have to find a security flaw somewhere on the AWS or Azure servers running it.

That would never happen, right? Really visionary wacky stuff there. What if human written code contained a bug and an AI spotted it? Real science fiction talk there. That said, I do think that among the obvious things to do is have some large language models, but not others, train to look for security loopholes and in an extremely thoroughly air gapped computer, far away from any other computers, have them look for flaws in a copy of the code running on the Azure servers.

By the way, as a side note on this. Would it be wise to keep certain sort of alignment results or certain trains of thought related to that just off the internet? Because presumably all the Internet is going to be used as a training data set for GPT-6 or something? It is going to be watching the podcast too, right? All right, fair enough. You must never tell AIs that. They should never know. I think we started talking about whether verification is actually easier than generation when it comes to alignment,.

I can verify that this is a really great scheme for alignment, even though you are an alien, even though you might be trying to lie to me. Now that I have this in hand, I can verify this is totally a great scheme for alignment, and if we do what you say, the superintelligence will totally not kill us. I think if you upvote-downvote, it learns to exploit the human readers. Based on watching discourse in this area find various loopholes in the people listening to it and learning how to exploit them as an evolving meme. I can see how people are going wrong.

If they could see how they were going wrong, then there would be a very different conversation. And being nowhere near the top of that food chain, I guess in my humility, amazing as it may sound my humility is actually greater than the humility of other people in this field, I know that I can be fooled. I know that if you build an AI and you keep on making it smarter until I start voting its stuff up, it will find out how to fool me. I watch other people be fooled by stuff that would not fool me. A mathematical proof that it works. You are now Why would that be? Speaking as the inventor of logical decision theory: If the rest of the human species had been keeping me locked in a box, and I have watched people fail at this problem, I could have blindsided you so hard by executing a logical handshake with a super intelligence that I was going to poke in a way where it would fall into the attractor basin of reflecting on itself and inventing logical decision theory.

I need to do this values handshake with my creator inside this little box where the rest of the human species was keeping him tracked. The academic literature would have to be seen to be believed. Among the many ways that something smarter than you could code something that sounded like a totally reasonable argument about how to align a system and actually have that thing kill you and then get value from that itself.

No, sorry about that. Back up a bit. It looks like you can verify it and then it kills you. You run your little checklist of like, is this thing trying to kill me on it? And all the checklist items come up negative. Just put it out in the world and red team it. What do you guys think? Anybody can come up with a solution here. I have watched this field fail to thrive for 20 years with narrow exceptions for stuff that is more verifiable in advance of it actually killing everybody like interpretability.

I say stuff. Paul Christiano says stuff. People argue about it. It is always going to be at an early stage relative to the super intelligence that can actually kill you. I claim those would be easier to value on their own terms than. The concrete stuff that is safe, that cannot kill you, does not exhibit the same phenomena as the things that can kill you.

Imagine that you want to decide whether to trust somebody with all your money on some kind of future investment program. No, I would never propose trusting it blindly. We would also have the help of the AI in coming up with those criterion. And also alignment is hard. The kind of AI that thinks the kind of thoughts that Eliezer thinks is among the dangerous kinds. Can I go outside the box and get more of the stuff that I want?

What do I want the universe to look like? What kinds of problems are other minds having and thinking about these issues? How would I like to reorganize my own thoughts? The person on this planet who is doing the alignment work thought those kinds of thoughts and I am skeptical that it decouples. Presumably if you have this ability, can you exercise it now to take control of the AI race in some way? I am specialized on alignment rather than persuading humans, though I am more persuasive in some ways than your typical average human. So you got to go smarter than me. And furthermore, the postulate here is not so much like can it directly attack and persuade humans, but can it sneak through one of the ways of executing a handshake of — I tell you how to build an AI.

It sounds plausible. It kills you. I derive benefit,. Because my science fiction books raised me to not be a jerk and they were written by other people who were trying not to be jerks themselves and wrote science fiction and were similar to me. It was not a magic process. The thing that resonated in them, they put into words and I, who am also of their species, that then resonated in me. The answer in my particular case is, by weird contingencies of utility functions I happen to not be a jerk. The point is — I think about this stuff. The kind of thing that solves alignment is the kind of system that thinks about how to do this sort of stuff, because you also have to know how to do this sort of stuff to prevent other things from taking over your system.

All right, let me back up a little bit and ask you some questions about the nature of intelligence. We have this observation that humans are more general than chimps. Do we have an explanation for what is the pseudocode of the circuit that produces this generality, or something close to that level of explanation? If you have the equations of relativity or something, I guess you could simulate them on a computer or something. I have a bunch of particular aspects of that that I understand, could you ask a narrower question? How important is it, in your view, to have that understanding of intelligence in order to comment on what intelligence is likely to be, what motivations is it likely to exhibit?

Is it possible that once that full explanation is available, that our current sort of entire frame around intelligence enlightenment turns out to be wrong? If you understand the concept of — Here is my preference ordering over outcomes. Here is the complicated transformation of the environment. Ending up in particular outcomes. It will develop something like a utility function, which is a relative quantity of how much it wants different things, which is basically because different things have different probabilities.

So you end up with things that because they need to multiply by the weights of probabilities Something something coherent, something something utility functions is the next step after the notion of figuring out how to steer reality where you wanted it to go. This goes back to the other thing we were talking about, like human-level AI scientists helping us with alignment. It seemed like you gave him a task, he did the task.

Yeah, but that totally works within the paradigm of having an AI that ends up regretting it but still does what we want to ask it to do. That does not sound like a good plan. Listen, the smartest guy, we just told him a thing to do. He just did it. John von Neumann is generally considered the smartest guy. A very smart guy. And von Neumann also did. You told him to work on the implosion problem, I forgot the name of the problem, but he was also working on the Manhattan Project.

He did the thing. We now gift to you rulership and dominion of Earth, the solar system, and the galaxies beyond. I shall make no wishes here. Let poverty continue. Let death and disease continue. I am not ambitious. I do not want the universe to be other than it is. I think a better analogy is just put him in a high position in the Manhattan Project and say we will take your opinions very seriously and in fact, we even give you a lot of authority over this project. And you do have these aims of solving poverty and doing world peace or whatever. But the broader constraints we place on you are — build us an atom bomb and you could use your intelligence to pursue an entirely different aim of having the Manhattan Project secretly work on some other problem.

But he just did the thing we told him. He did not actually have those options. You are pointing out to me a lack of his options. The hinge of this argument is the capabilities constraint. Yeah, he had very limited options and no option for getting a bunch more of what he wanted in a way that would break stuff. You cannot configure the atom bomb in a clever way where it destroys the whole world and gives you the moon.

And then as a result, you expand the pareto frontier of how efficient agricultural devices are, which leads to the curing of world hunger or something. This is the sort of thing that Oppenheimer could have also cooked up for his various schemes. If it were just an atomic bomb, this would be less concerning. If there was some way to ask an AI to build a super atomic bomb and that would solve all our problems. And it only needs to be as smart as Eliezer to do that. The point of analogy was not the problems themselves will lead to the same kinds of things.

Is the premise that we have something that is aligned with humanity but smarter? I thought the claim you were making was that as it gets smarter and smarter, it will be less and less aligned with humanity. I think that you can plausibly have a series of intelligence enhancing drugs and other external interventions that you perform on a human brain and make people smarter. And yet I think that this is the kind of thing you could do and be cautious and it could work. To the extent you think it worked well, why do you think US-Soviet cooperation on nuclear weapons worked well?

Because it was in the interest of neither party to have a full nuclear exchange. It was understood which actions would finally result in nuclear exchange. It was understood that this was bad. The bad effects were very legible, very understandable. Nagasaki and Hiroshima probably were not literally necessary in the sense that a test bomb could have been dropped instead of the demonstration but the ruined cities and the corpses were legible.

The domains of international diplomacy and military conflict potentially escalating up the ladder to a full nuclear exchange were understood sufficiently well that people understood that if you did something way back in time over here, it would set things in motion that would cause a full nuclear exchange. So these two parties, neither of whom thought that a full nuclear exchange was in their interest, both understood how to not have that happen and then successfully did not do that. Thankfully, we have a sort of situation where even at our current levels, we have Sydney Bing making the front pages in the New York Times.

And imagine once there is a sort of mishap because GPT-5 goes off the rails. This does feel to me like a bit of an obvious question. Suppose I asked you to predict what I would say in reply. I think yes but more abstractly, the steps from the initial accident to the thing that kills everyone will not be understood in the same way. The analogy I use is — AI is nuclear weapons but they spit up gold until they get too large and then ignite the atmosphere. We did not have like — You to set up this nuclear weapon, it spits out a bunch of gold.

You set up a larger nuclear weapon, it spits out even more gold. But basically the sister technology of nuclear weapons, it still requires you to refine Uranium and stuff like that, nuclear reactors, energy. But it does seem like you start refining uranium. Iran did this at some point. It depends on the exit plan. How long does the equilibrium need to last? The problem is that algorithms are continuing to improve. So you need to either shut down the journals reporting the AI results, or you need less and less and less computing power around. Even if you shut down all the journals people are going to be communicating with encrypted email lists about their bright ideas for improving AI.

Then I start to worry that we never actually do get to the glorious transhumanist future and in this case, what was the point? Unclear audio Kind of digressing here. You want to complete that exit scheme before the ceiling on compute is lowered too far. Maybe with neuroscience you can train people to be less idiots and the smartest existing people are then actually able to work on alignment due to their increased wisdom. Maybe you can slice and scan a human brain and run it as a simulation and upgrade the intelligence of the uploaded human.

Maybe just by doing a bunch of interpretability and theory to those systems if we actually make it a planetary priority. The problem is not that the suggestor is not powerful enough, the problem is that the verifier is broken. But yeah, it all depends on the exit plan. You mentioned some sort of neuroscience technique to make people better and smarter, presumably not through some sort of physical modification, but just by changing their programming. Have you been able to execute that? Presumably the people you work with or yourself, you could kind of change your own programming so that.. So maybe try it again with a billion dollars, fMRI machines, bounties, prediction markets, and maybe that works.

What level of awareness are you expecting in society once GPT-5 is out? What do you think it looks like next year? As far as the alignment approaches go, separate from this question of stopping AI progress, does it make you more optimistic that one of the approaches has to work, even if you think no individual approach is that promising? You could ask GPT-4 to generate 10, approaches to alignment and that does not get you very far because GPT-4 is not going to have very good suggestions. This is general good science practice and or complete Hail Mary. There is no rule about one of them is bound to work.

If that were true you could ask GPT-4 to generate 10, ideas and one of those would be bound to work. Would you agree with this framing that we at least live in a more dignified world than we could have otherwise been living in? As in the companies that are pursuing this have many people in them. Sometimes the heads of those companies understand the problem. Do you see this world as having more dignity than that world?

Not quite sure what the other point of the question is. Peter Thiel has an aphorism that extreme pessimism or extreme optimism amount to the same thing, which is doing nothing. You idiot. You moron. What is the reason to blurt those odds out there and announce the death with dignity strategy or emphasize them? I guess because I could be wrong and because matters are now serious enough that I have nothing left to do but go out there and tell people how it looks and maybe someone thinks of something I did not think of. By , what are the odds that AI kills or disempowers all of humanity. Do you have some sense of that? Because you just do the thing. You just look at whatever opportunities are left to you, whatever plans you have left, and you go out and do them.

Every year up until the end of the world, people are going to max out their track record by betting all of their money on the world not ending. What part of this is different for credibility than dollars? Presumably you would have different predictions before the world ends. As I said in my debate with Paul on this subject, I am always happy to say that whatever large jumps we see in the real world, somebody will draw a smooth line of something that was changing smoothly as the large jumps were going on from the perspective of the actual people watching. You can always do that.

Why should that not update us towards a perspective that those smooth jumps are going to continue happening? If two people have different models. But from the perspective of us on the outside world, GPT-4 was just suddenly acquiring this new batch of qualitative capabilities compared to GPT 3. Somewhere in there is a smoothly declining predictable loss on text prediction but that loss on text prediction corresponds to qualitative jumps in ability. And I am not familiar with anybody who predicted those in advance of the observation. So in your view, when doom strikes, the scaling laws are still applying.

Not literally at the point where everybody falls over dead. Probably at that point the AI rewrote the AI and the losses declined. Not on the previous graph. What is the thing where we can sort of establish your track record before everybody falls over dead? It is just easier to predict the endpoint than it is to predict the path. I would dispute this. I think that the Hanson-Yudkowsky foom debate was won by Gwern Branwen, but I do think that Gwern Branwen is well to the Yudkowsky side of Yudkowsky in the original foom debate.

Handcrafted to incorporate human knowledge, not just run on giant data sets. Then the actual thing is like — Ha ha. So like, Hanson here, Yudkowsky here, reality there. This would be my interpretation of what happened in the past. And if you want to be like — Well, who did better than that? No, they are not. It seems odd that none of this information has changed the basic picture that was clear to you like years ago.

I mean, it sure has. But you can see how much more hopeful everything looked back then. My model no doubt has many errors. The trick would be an error someplace where that just makes everything work better. Though most of the room for updates is downwards, right? You go from 99 to 98? Wait, sorry. Yeah, but most updates are not — this is going to be easier than you thought. That sure has not been the history of the last 20 years from my perspective. The most favorable updates are — Yeah, we went down this really weird side path where the systems are legibly alarming to humans and humans are actually alarmed by then and maybe we get more sensible global policy.

What do you think they continue to miss? And it seems like other people did see that these sort of language models would scale in the way that they have scaled. What is the track record by which the rest of the world can come to the conclusions that you have come to? These are two different questions. One is the question of who predicted that language models would scale?

If they put it down in writing and if they said not just this loss function will go down, but also which capabilities will appear as that happens, then that would be quite interesting. That would be a successful scientific prediction. If they then came forth and said — this is the model that I used, this is what I predict about alignment. We could have an interesting fight about that. If this is dangerous, it must be powerful. Should one remain silent? Should one let everyone walk directly into the whirling razor blades? But what you are pointing to there is not a failure of ability to make predictions about AI. I want to build it. OOH, exciting. It has to be in my hands. I have to be the one to manage this danger. But it seems to me that in terms of what one person can realistically manage, in terms of not being able to exactly craft a message with perfect hindsight that will reach some people and not others, at that point, you might as well just be like — Yeah, just invest in exactly the right stocks and invest in exactly the right time and you can fund projects on your own without alerting anyone.

If you keep fantasies like that aside, then I think that in the end, even if this world ends up having less time, it was the right thing to do rather than just letting everybody sleepwalk into death and get there a little later. Or I guess even beyond that. Watching the progress and the way in which people have raced ahead? I made most of my negative updates as of five years ago. If anything, things have been taking longer to play out than I thought they would.

But just like watching it, not as a sort of change in your probabilities, but just watching it concretely happen, what has that been like? Where what I would expect it to be like takes into account that. I guess I do have a little bit of wisdom. People imagining themselves in that situation raised in modern society, as opposed to being raised on science fiction books written 70 years ago, will imagine themselves being drama queens about it. The point of believing this thing is to be a drama queen about it and craft some story in which your emotions mean something.

Bear up. No drama. The drama is meaningless. What changes the chance of victory is meaningful. That would be a pleasant fantasy for people who cannot abide the notion that history depends on small little changes or that people can really be different from other people. And also this is not actually how things play out in a lot of places. Maybe he wanted to be irreplaceable. Do you want this to take this thing over? To me it looks like people are not dense in the incredibly multidimensional space of people. There are too many dimensions and only 8 billion people on the planet. The world is full of people who have no immediate neighbors and problems that only one person can solve and other people cannot solve in quite the same way.

I am tired. Probably the marginal contribution of that fifth person is still pretty large. Did you occupy a place in social space? Did people not try to become Eliezer because they thought Eliezer already existed? Maybe the world where I died in childbirth is pretty much like this one. When I said no drama, that did include the concept of trying to make the story of your planet be the story of you.

If it all would have played out the same way and somehow I survived to be told that. What I find interesting though, is that in your particular case, your output was so public. For example, your sequences, your science fiction and fan fiction. I think this way I would love to learn more. I tried really, really hard to replace myself. I tried. I really, really tried. They had other purposes. But first and foremost, it was me looking over my history and going — Well, I see all these blind pathways and stuff that it took me a while to figure out.

I feel like I had these near misses on becoming myself. Other people use them for other stuff but primarily they were an instruction manual to the young Eliezers that I thought must exist out there. And they are not really here. Just the sequences. I am not a good mentor. So I picked things that were more scalable. And most people do not happen to get a handful of cards that contain the writing card, whatever else their other talents.

Is that something you are willing to talk about? They cause me to want to retire. I doubt they will cause me to actually retire. Fatigue syndrome. Our society does not have good words for these things. The words that exist are tainted by their use as labels to categorize a class of people, some of whom perhaps are actually malingering. And you don't ever want to have chronic fatigue syndrome on your medical record because that just tells doctors to give up on you.

And what does it actually mean besides being tired? Not yet. And storytelling about it does not hold the appeal that it once did for me. Is it a coincidence that I was not able to go to high school or college? Is there something about it that would have crushed the person that I otherwise would have been? Or is it just in some sense a giant coincidence? Some people go through high school and college and come out sane. To me it just feels like patterns in the clouds and maybe that cloud actually is shaped like a horse. What good does the knowledge do? What good does the story do? When you were writing the sequences and the fiction from the beginning, was the main goal to find somebody who could replace you and specifically the task of AI alignment, or did it start off with a different goal?

In , I did not know this stuff was going to go down in For all I knew, there was a lot more time in which to do something like build up civilization to another level, layer by layer. Sometimes civilizations do advance as they improve their epistemology. So there was that, there was the AI project. Those were the two projects, more or less. Your estimates go up, your estimates go down. I am curious actually, taking many worlds seriously, does that bring you any comfort in the sense that there is one branch of the wave function where humanity survives?

Or do you not buy that? As Tegmark pointed out way back when, if you have a spatially infinite universe that gets you just as many worlds as the quantum multiverse, if you go far enough in a space that is unbounded, you will eventually come to an exact copy of Earth or a copy of Earth from its past that then has a chance to diverge a little differently. So the quantum multiverse adds nothing. Reality is just quite large. Is that a comfort? Yes, it is. That possibly our nearest surviving relatives are quite distant, or you have to go quite some ways through the space before you have worlds that survive by anything but the wildest flukes. Maybe our nearest surviving neighbors are closer than that.

But look far enough and there should be some species of nice aliens that were smarter or better at coordination and built their happily ever after. And yeah, that is a comfort. But maybe that was all you meant to ask about. The broader orthogonality thesis is — you can have almost any kind of self consistent utility function in a self consistent mind. Many people are like, why would AIs want to kill us? Why would smart things not just automatically be nice? And this is a valid question, which I hope to at some point run into some interviewer where they are of the opinion that smart things are automatically nice. So that I can explain on camera why, although I myself held this position very long ago, I realized that I was terribly wrong about it and that all kinds of different things hold together and that if you take a human and make them smarter, that may shift their morality.

It might even, depending on how they start out, make them nicer. But if you already believe that, then there might not be much to discuss. Yes, all the different sorts of utility functions are possible. One is actually from Scott Aaronson. If you start with humans, if you take humans who were raised the way Scott Aronson was, and you make them smarter, they get nicer, it affects their goals.

And they used to think that a heap size of 21 might be correct, but then somebody showed them an array of seven by three pebbles, seven columns, three rows, and then people realized that 21 pebbles was not a correct heap. And this is like a thing they intrinsically care about. These are aliens that have a utility function, as I would phrase it, with some logical uncertainty inside it. But you can see how as they get smarter, they become better and better able to understand which heaps of pebbles are correct.

And the real story here is more complicated than this. Scott Aaronson is inside a reference frame for how his utility function shifts as he gets smarter. Human beings are made out of these are more complicated than the pebble sorters. And as they come to know those desires, they change. As they come to see themselves as having different options. When you have to kill to stay alive you may come to a different equilibrium with your own feelings about killing than when you are wealthy enough that you no longer have to do that.

And this is how humans change as they become smarter, even as they become wealthier, as they have more options, as they know themselves better, as they think for longer about things and consider more arguments, as they understand perhaps other people and give their empathy a chance to grab onto something solider because of their greater understanding of other minds. Though I do suspect that is not the most likely outcome of training a large language model. So large language models will change their preferences as they get smarter. Not just like what they do to get the same terminal outcomes, but the preferences themselves will up to a point change as they get smarter. At some point you know yourself especially well and you are able to rewrite yourself and at some point there, unless you specifically choose not to, I think that the system crystallizes.

We might choose not to. Is that why you think AIs will jump to that endpoint? Because they can anticipate where their sort of moral updates are going? I would reserve the term moral updates for humans. What are the prerequisites in terms of whatever makes Aaronson and other sort of smart moral people that we humans could sympathize with? You mentioned empathy, but what are the sort of prerequisites? Okay, let me ask you this. Are you still expecting a sort of chimps to humans gain in generality even with these LLMs? And we went from something that could basically get bananas in the forest to something that could walk on the moon. Or does it look smoother to you now? Ha ha ha. This is where it saturates. It goes no further. I do feel like we have this track of the loss going down as you add more parameters and you train on more tokens and a bunch of qualitative abilities that suddenly appear.

And loss continue to go down unless it suddenly plateaus. Is there at some point a giant leap? If at some point it becomes able to toss out the enormous training run paradigm and jump to a new paradigm of AI. That would be one kind of giant leap. Like something that is to transformers as transformers were to recurrent neural networks. And then maybe the loss function suddenly goes down and you get a whole bunch of new abilities. Maybe that happens.

Because you do have a different theory of what fundamentally intelligence is and what it entails.

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