Dario Amodei: commitment

Transcript context

…All right. So it does have to interact with the physical world to verify. But you just look at even the simplest problems. I think I talk about The Three-Body Problem or simple chaotic prediction, or predicting the economy. It’s really hard to predict the economy two years out. Maybe the case is humans can predict what’s going to happen in the economy next quarter, or they can’t really do that. Maybe a AI that’s a zillion times smarter can only predict it out a year or something, instead of … You have these exponential increase in computer intelligence for linear increase in ability to predict. Same with again, like biological molecules interacting. You don’t know what’s going to happen when you perturb a complex system. You can find simple parts in it, if you’re smarter, you’re better at finding these simple parts. And then I think human institutions, human institutions are really difficult. It’s been a hard to get people. I won’t give specific examples, but it’s been hard to get people to adopt even the technologies that we’ve developed, even ones where the case for their efficacy is very, very strong. People have concerns. They think things are conspiracy theories. It’s just been very difficult. It’s also been very difficult to get very simple things through the regulatory system. And I don’t want to disparage anyone who works in regulatory systems of any technology. There are hard they have to deal with. They have to save lives. But the system as a whole, I think makes some obvious trade-offs that are very far from maximizing human welfare. And so, if we bring AI systems into these human systems, often the level of intelligence may just not be the limiting factor. It just may be that it takes a long time to do something. Now, if the AI system circumvented all governments, if it just said, “I’m dictator of the world and I’m going to do whatever,” some of these things it could do. Again, the things have to do with complexity. I still think a lot of things would take a while. I don’t think it helps that the AI systems can produce a lot of energy or go to the moon. Like some people in comments responded to the essay saying the AI system can produce a lot of energy and smarter AI systems. That’s missing the point. That kind of cycle doesn’t solve the key problems that I’m talking about here. So I think a bunch of people missed the point there. But even if it were completely unaligned and could get around all these human obstacles it would have trouble. roblems that I’m talking about here. So I think a bunch of people missed the point there. But even if it were completely unaligned and could get around all these human obstacles it would have trouble. But again, if you want this to be an AI system that doesn’t take over the world, that doesn’t destroy humanity, then basically it’s going to need to follow basic human laws. If we want to have an actually good world, we’re going to have to have an AI system that interacts with humans, not one that creates its own legal system, or disregards all the laws or all of that. So as inefficient as these processes are, we’re going to have to deal with them, because there needs to be some popular and democratic legitimacy in how these systems are rolled out. We can’t have a small group of people who are developing these systems say, “This is what’s best for everyone.” I think it’s wrong, and I think in practice it’s not going to work anyway. So you put all those things together and we’re not going change the world and upload everyone in five minutes. A, I don’t think it’s going to happen and B, to the extent that it could happen.,It’s not the way to lead to a good world. So that’s on one side. On the other side, there’s another set of perspectives, which I have actually in some ways more sympathy for, which is, look, we’ve seen big productivity increases before. Economists are familiar with studying the productivity increases that came from the computer revolution and internet revolution. And generally those productivity increases were underwhelming. They were less than you might imagine. There was a quote from Robert Solow, “You see the computer revolution everywhere except the productivity statistics.” So why is this the case? People point to the structure of firms, the structure of enterprises, how slow it’s been to roll out our existing technology to very poor parts of the world, which I talk about in the essay. How do we get these technologies to the poorest parts of the world that are behind on cell phone technology, computers, medicine, let alone newfangled AI that hasn’t been invented yet. So you could have a perspective that’s like, “Well, this is amazing technically, but it’s all or nothing burger. I think Tyler Cowen who wrote something in response to my essay has that perspective. I think he thinks the radical change will happen eventually, but he thinks it’ll take 50 or 100 years. And you could have even more static perspectives on the whole thing. I think there’s some truth to it. I think the time scale is just too long and I can see it. I can actually see both sides with today’s AI. So a lot of our customers are large enterprises who are used to doing things a certain way. I’ve also seen it in talking to governments, right? Those are prototypical institutions, entities that are slow to change. But, the dynamic I see over and over again is yes, it takes a long time to move the ship. Yes. There’s a lot of resistance and lack of understanding.…

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