🤖🧠 My chat (+transcript) with Google DeepMind's Séb Krier on AGI and public policy

In a world of Artificial General Intelligence, machines would be able to match, and even exceed, human cognitive abilities. AGI might still be science fiction, but Séb Krier sees this technology as not only possible, but inevitable. Today on Faster, Please! — The Podcast, I chat with Krier about how our public policy should facilitate AGI’s arrival and flourishing.

Krier is an AI policy expert, adviser, and attorney. He currently works in policy development and strategy at Google DeepMind. He previously served as Head of Regulation for the UK Government’s Office for Artificial Intelligence and was a Senior Tech Policy Researcher at Stanford’s Cyber Policy Center.

In This Episode

* The AGI vision (1:24)

* The risk conversation (5:15)

* Policy strategy (11:25)

* AGI: “if” or “when”? (15:44)

* AI and national security (18:21)

* Chatbot advice (20:15)

Below is a lightly edited transcript of our conversation

Pethokoukis: Séb, welcome to the podcast.

Krier: Thank you. Great to be here.

The AGI vision (1:24)

Let's start with a bit of context that may influence the rest of the conversation. What is the vision or image of the future regarding AI — you can define it as machine learning or generative AI — that excites you, that gets you going in the day, that you feel like you're part of something important? What is that vision?

I think that's a great question. In my mind, I think AI has been going on for quite a long time, but I think the aim has always been artificial general intelligence. And in a sense, I think of this as a huge deal, and the vision I have for the future is being able to have a very, very large supply of cognitive resources that you can allocate to quite a wide range of different problems, whether that's energy, healthcare, governance, there's many, many ways in which this technology can be applied as a general purpose technology. And so I guess my vision is seeing that being used to solve quite a wide range of problems that humans have had for decades, centuries, millennia. And I think you could go into so many different directions with that, whether it's curing diseases, or optimizing energy grids, and more. But I think, broadly, that’s the way I think about it. So the objective, in a sense, is safe AGI [Artificial General Intelligence], and from that I think it can go even further. And I think in many ways, this can be hugely beneficial to science, R&D, and humanity as a whole. But of course, that also comes with ways in which this could be misused, or accidents, and so on. And so huge emphasis on the safe development of AGI.

So you're viewing it as a tool, as a way to apply intelligence across a variety of fields, a variety of problems, to solve those problems, and of course, the word in there doing a lot of lifting is “safely.” Given the discussion over the past 18 months about that word, “safely,” is, one, I think someone who maybe only pays passing attention to this issue might think that it's almost impossible to do it safely without jeopardizing all those upside benefits, but you're confident that those two things can ultimately be in harmony?

Yeah, absolutely, otherwise I wouldn't be necessarily working on an AGI policy. So I think I'm very confident this can be done well. I think it also depends what we mean by “safety” and what kind of safety we have in mind. Any technology, we will have costs and trade-offs, but of course the upside here is enormous, and, in my mind, very much outweighs potential downsides.

However, I think for certain risks, things like potentially catastrophic risks and so on, there is an argument in treading some careful path and making sure this is done scientifically with a scientific method in mind, and doing that well. But I don't think there's fundamentally a necessary tension, and I think, in fact, what many people sometimes underestimate is how AI itself, as a technology, will be helpful in mitigating a lot of the risks we're foreseeing and thinking about. There's obviously ways in which AI can be used for cyber offense, but many ways in which you can also use that for defense, for example. I'm cautiously optimistic about how this can be developed and used in the long run

The risk conversation (5:15)

Since these large language models and chatbots were rolled out to public awareness in late 2022, has the safety regulatory debate changed in any way? It seems to me that there was a lot of talk early on about these existential risks. Now I seem to hearing less about that and more about issues about, maybe it's disinformation or bias. From your perspective, has that debate changed and has it changed for the better, or worse?

I think it has evolved quite a lot over the past — I've been working in AI policy since 2017 and there's been different phases, and at first a lot of skepticism around AI even being useful, or hype, and so on, and then seeing more and more of what these general models could do, and I think, initially, a lot of the concerns were around things like bias, and discrimination,