All of Pongo's Comments + Replies

OK, thanks! The negative definition makes sense to me. I remain unconvinced that there is a positive definition that hits the same bundle of work, but I can see why we would want a handle for the non-technical work of AI risk mitigation (even before we know what the correct categories are within that).

There's a decent overlap in expertise needed to address these questions.

This doesn't yet seem obvious to me. Take the nuclear weapons example. Obviously in the Manhattan project case, that's the analogy that's being gestured at. But a structural risk of inequality doesn't seem to be that well-informed by a study of nuclear weapons. If we have a CAIS world with structural risks, it seems to me that the broad development of AI and its interactions across many companies is pretty different from the discrete technology of nuclear bombs... (read more)

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It definitely seems true that if I want to specifically figure out what to do with scenario a), studying how AI might affect structural inequality shouldn't be my first port of call. But it's not clear to me that this means we shouldn't have the two problems under the same umbrella term. In my mind, it mainly means we ought to start defining sub-fields with time.

Thanks for the response!

I don't think we currently know what problems within AI governance are most pressing. Once we do, it seems prudent to specialise more.

It makes sense not to specialize early, but I'm still confused about what the category is. For example, the closest thing to a definition in this post (btw, not a criticism if a definition is missing in this post. Perhaps it's aimed at people with more context than me) seems to be:

AI governance concerns how humanity can best navigate the transition to a world with advanced AI systems

To ... (read more)

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A great first guess! It's basically my favourite definition, though negative definitions probably aren't all that satisfactory either. We can make it more precise by saying (I'm not sure what the origin of this one is, it might be Jade Leung or Allan Dafoe): AI governance has a descriptive part, focusing on the context and institutions that shape the incentives and behaviours of developers and users of AI, and a normative part, asking how should we navigate a transition to a world of advanced artificial intelligence? It's not quite the definition we want, but it's a bit closer.

I would be interested in a monthly version

If I understand correctly, you view AI Governance as addressing how to deal with many different kinds of AI problems (misuse, accident or structural risks) that can occur via many different scenarios (superintelligence, ecology or GPT perspectives). I also think (though I'm less confident) that you think it involves using many different levers (policy, perhaps alternative institutions, perhaps education and outreach).

I was wondering if you could say a few words on why (or if!) this is a helpful portion of problem-assumption-lever space to carve into a... (read more)

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I'll drop in my 2c. AI governance is a fairly nascent field. As the field grows and we build up our understanding of it, people will likely specialise in sub-parts of the problem. But for now, I think there's benefit to having this broad category, for a few reasons: * There's a decent overlap in expertise needed to address these questions. By thinking about the first, I'll probably build up knowledge and intuitions that will be applicable to the second. For example, I might want to think about how previous powerful technologies such as nuclear weapons came to be developed and deployed. * I don't think we currently know what problems within AI governance are most pressing. Once we do, it seems prudent to specialise more. This doesn't mean you shouldn't think of problems of type a and b separately. You probably should.

To state a point in the neighborhood of what Stefan, Ben P, and Ben W have said, I think it's important for LTTF to evaluate the counterfactual where they don't fund something, rather than the counterfactual where the project has more reasonable characteristics.

That is, we might prefer a project be more productive, more legible or more organized, but unless that makes it worse than the marginal funding opportunity, it should be funded (where one way a project could be bad is by displacing more reasonable projects that would otherwise fill a gap)... (read more)