It's a very intense time in the field. We obviously want all of the brilliant things these AI systems can do, come up with new cures for diseases, new energy sources, incredible things for humanity. That's the promise of AI. But also, there are worries if the first AI systems are built with the wrong value systems or they're built unsafely, that could be also very bad.
Wired sat down with Demis Hassabis, who's the CEO of Google DeepMind, which is the engine of the company's artificial intelligence. He's a Nobel Prize winner and also a knight. We discussed AGI, the future of work, and how Google plans to compete in the age of AI. This is 'The Big Interview.'
Well, welcome to 'The Big Interview,' Demis.
Thank you, thanks for having me.
So let's start talking about AGI a little here. Now, you founded DeepMind with the idea that you would solve intelligence and then use intelligence to solve everything else. And I think it was like a 20-year mission. We're like 15 years into it, and you're on track?
I feel like, yeah, we're pretty much dead on track, actually, is what would be our estimate.
That means five years away from what I guess people will call AGI.
Yeah, I think in the next five to 10 years, that would be maybe 50% chance that we'll have what we are defined as AGI, yes.
Well, some of your peers are saying, 'Two years, three years,' and others say a little more, but that's really close, that's really soon. How do we know that we're that close?
There's a bit of a debate going on in the moment in the field about definitions of AGI, and then obviously, of course, dependent on that. There's different predictions for when it will happen. We've been pretty consistent from the very beginning. And actually, Shane Legg, one of my co-founders and our chief scientist, he helped define the term AGI back in, I think, early 2001 type of timeframe. And we've always thought about it as a system that has the ability to exhibit all the cognitive capabilities we have as humans. And the reason that's important, the reference to the human mind, is the human mind is the only existence proof we have. Maybe in the universe, the general intelligence is possible. So if you want to claim general intelligence, AGI, then you need to show that it generalizes to all these domains.
Is when everything's filled in, all the check marks are filled in, then we have it?
Yes, so I think there are missing capabilities right now. All of us who have used the latest LLMs and chatbots will know very well, like on reasoning, on planning, on memory. I don't think today's systems can do true invention, true creativity, hypothesize new scientific theories. They're extremely useful, they're impressive, but they have holes. And actually, one of the main reasons I don't think we are at AGI yet is because of the consistency of responses. In some domains, we have systems that can do International Math Olympiad math problems to gold medal standard, but on the other hand, these systems sometimes still trip up on high school maths or even counting the number of letters in a word. That to me is not what you would expect. That level of difference in performance across the board is not consistent enough, and therefore shows that these systems are not fully generalizing yet.
But when we get it, is it then like a phase shift that all of a sudden things are different, all the check marks are checked, and we have a thing that can do everything? Are we then in a new world?
I think that again, that is debated, and it's not clear to me whether it's going to be more of a kind of incremental transition versus a step function. My guess is, it looks like it's going to be more of an incremental shift. Even if you had a system like that, the physical world still operates with the physical laws, factories, robots, these other things. So it'll take a while for the effects of this digital intelligence to really impact a lot of the real world things. Maybe another decade plus, but there's other theories on that too, where it could come faster.
Eric Schmidt, who I think used to work at Google, has said that, 'It's almost like a binary thing.' He says, 'If China, for instance, gets AGI, then we're cooked.' Because if someone gets it like 10 minutes before the next guy, then you can never catch up. It'll maintain bigger leads there. You don't buy that, I guess.
I think it's an unknown. It's one of the many unknowns, which is that sometimes called the hard takeoff scenario, where the idea is that these AGI systems are able to self-improve, maybe code themselves future versions, that maybe they're extremely fast at doing that. So what would be a slight lead, let's say a few days, could suddenly become a chasm if that was true. But there are many other ways it could go too, where it's more incremental. Some of these self-improvement things are not able to accelerate in that way, then being around the same time would not make much difference. But it's important, these issues are the geopolitical issues. I think the systems that are being built will have some imprint of the values and the norms of the designers and the culture that they were embedded in. So I think it is important, these kinds of international questions.
So when you build AI at Google, you have that in mind. Do you feel competitive imperative to, in case that's true, 'Oh my God, we better be first?'
It's a very intense time at the moment in the field as everyone knows. There's so many resources going into it, lots of pressures, lots of things that need to be researched. And there's lots of different types of pressures going on. We obviously want all of the brilliant things that these AI systems can do. I think eventually, we'll be able to advance medicine and science with it, like we've done with AlphaFold, come up with new cures for diseases, new energy sources, incredible things for humanity, that's the promise of AI. But also there are worries both in terms of if the first AI systems are built with the wrong value systems or they're built unsafely, that could be also very bad. And there are at least two risks that I worry a lot about. One is bad actors, whether it's individuals or rogue nations, repurposing general purpose AI technology for harmful ends. And then the second one is the technical risk of AI itself. As it gets more and more powerful, more and more agentic, can we make sure the guardrails are safe around it? They can't be circumvented. And that interacts with this idea of what are the first systems that are built by humanity going to be like? There's commercial imperative, there's national imperative, and there's a safety aspect to worry about who's in the lead and where those projects are.
A few years ago, the companies were saying, 'Please, regulate us. We need regulation.' And now, in the US at least, the current administration seems less interested in putting regulations on AI than accelerating it so we can beat the Chinese. Are you still asking for regulation? Do you think that that's a miss on our part?
I think, and I've been consistent in this, I think there are these other geopolitical overlays that have to be taken into account, and the world's a very different place to how it was five years ago in many dimensions. But there's also the idea of smart regulation that makes sense around these increasingly powerful systems, I think is going to be important. I continue to believe that. I think though, and I've been certain on this as well, it needs to be international, which looks hard at the moment in the way the world is working, because these systems are going to affect everyone, and they're digital systems. So if you restrict it in one area, that doesn't really help in terms of the overall safety of these systems getting built for the world and as a society. So that's the bigger problem, I think, is some kind of international cooperation or collaboration is what's required. And then smart regulation, nimble regulation that moves as the knowledge about the research becomes better and better.
Would it ever reach a point for you where you would feel, 'Man, we're not putting the guardrails in. We're competing, that we really have to stop, or you can't get involved in that?'
I think a lot of the leaders of the main labs, at least the western labs, there's a small number of them and we do all know each other and talk to each other regularly. And a lot of the lead researchers do. The problem is that it's not clear we have the right definitions to agree when that point is. Today's systems, although they're impressive as we discussed earlier, they're also very flawed. And I don't think today's systems are posing any sort of existential risk. So it's still theoretical, but the problem is that a lot of unknowns, we don't know how fast those will come, and we don't know how risky they will be. But in my view, when there are so many unknowns, then I'm optimistic we'll overcome them. At least technically, I think the geopolitical questions could end up being trickier. Given enough time and enough care and thoughtfulness, using the scientific method as we approach this AGI point.
