Roman Yampolskiy: AI Can't Be Controlled. We Need to Pause Now!

He said that humans are universal explainers, that there's no knowledge growth that can be bounded for a human being. So that means to me, there's no insoluble problems, including control of artificial superintelligence. So where is he wrong? He's arguing that in science, there are no impossible things to do. We literally published a survey of like 50 plus, including from physics, political science, economics, mathematics and computer science. Holting problem is a computer science result. Right. But there are similar results. Arrow's theorem and voting like I can go on. You know, physics has many limits. You know, there are impossibility results in quantum physics and normal physics. Well, I'm not saying that there aren't things that aren't impossible. By the way, the name of the podcast is Into the Impossible from Arthur C. Clark, who created how we'll talk about in a little bit, perhaps. And that was the only way to know the limits of the possible is to go beyond them into the impossible. You know, he's not saying that everything that's impossible is possible. He's saying that there's that that human knowledge. Humans are universal explainers. This is a concept that he that he coined, you know, 40 years ago. And because and computers could be universal constructors as well. And in the beginning of infinity, we're always closer to zero than we are to infinity. Right. Just mathematically speaking. So therefore, what what is we can't bound the limits of knowledge and part of controlling super AI? Again, I'm I'm being devil's advocate here. I'm not I'm not saying this is my position. I'm just saying this is what I think. David Paskas, David George was like, is that because you're to control something, you need to have knowledge of its future prediction of its future behavior. Although you can't have perfect knowledge of anything. Right. I mean, it's just that's impossible for sure. But the question is, can you have the same level of controllability via the knowledge that a human who's a universal explainer can glean? And I guess he's saying you're saying it's impossible for a human to ever control AI. But he's saying humans are universal explainers. Therefore, nothing explainable, even with errors and stochastic notions of what explanation means, is not fundamentally restricted. So it does seem like you guys don't agree, and that's fine. But but but I guess that's not a formal proof, by the way. I'm just saying he's saying humans can explain things. AI is something that could be explained. Therefore, it's not impossible to explain them. But I think you would say it is impossible to control them because you cannot explain them. Correct. So there is theory and practice in theory, given infinite time. Average human with pencil and paper can probably figure out everything. We don't have infinite time. And we have limited size brain with limited size memory cells. Our ability to survey information is limited. So if you had a mathematical proof and it was a billion pages long, no human can verify that proof. In theory, they could. But in practice, it's not going to happen. And I'm going to say in theory, communism works. But in practice, if we have a real world situation where you have a system, let's just say it's just like humans, but it's a billion times faster. We're not competitive in that environment. We simply don't have time to react, to do anything whatsoever, to counteract what the system is going to do. But we are not equal. We're going to have systems ten, hundred, thousand, million times smarter than us. What does that mean? They see patterns we don't see. I always bring up examples from animal kingdom, right? You can have squirrels, monkeys, whatever you want. They're very intelligent beings. Eventually, they have some language, culture. They're starting to use tools, but they're not competitive with us. We're just on a different level. And it's exactly what we're going to see here. Him being a very good professor at a very good university, he understands that when he selects students, he doesn't select them at random because all humans are universal explainers. He looks for the one with highest intelligence. Why? Because they're going to finish things in time. They're going to understood and publish on time. And it's exactly the same. Instead of looking for a student with IQ of 130, now you're comparing machines with IQ of a thousand to humans and saying, well, technically, they're all in the same class of automata. They're all Turing complete. True, but that means nothing for safety. So first to separate consciousness, what he's trying to explain with macrotubules is not intelligence or optimization power we care about. You can have a very capable optimizer with zero internal feelings, experiences that's not relevant. So as explanation for consciousness, maybe quantum effects are relevant. I think Tegmark published a very good paper saying at room temperature human brain will not have those quantum effects. So he dismissed his microtubules theory. But I'm open to having that as back door for explaining consciousness in humans. But at the same time, I think large language models are showing exactly the same internal state. So I don't think we need that explanation. Let's say all of it is right. OK, so we'll switch to quantum computers. They seem to be progressing well. Does that reduce all the disagreement? We're now saying we just need quantum computers to outperform humans. I'm willing to go that way if that helps to convince people about dangers. What is it like to be a bot? So again, I want to repeat my previous answer. Those are not related concepts. I don't need superintelligence to be conscious. That's not the point. I don't care how Terminator chasing me feels on the inside. They are capable optimizers, pattern recognizers. They can solve problems. Human intelligence is seemingly unable to solve better, faster. And they're getting better at solving real world problems. Consciousness is interesting. It may be fundamental, fundamental to physics even. But it's not a big safety concern at this point. If you talk about robot rights, if you talk about suffering in large language models, that is a fundamental question. I love the topic. We can talk about it. We have some new experimental data on it. But when it comes to safety, that's not what we're even talking about. We can know nothing about consciousness and still create dangerous superintelligence.