> If the value on the other hand comes from people being extremely good at math, rather than from them solving novel open problems, then we should pay them to do that, which is independent of whether the open problems are solved or not. There's just no version of this where "not solving the problems" is morally justifiable.

I think the value comes from having people who have built very good intuition in a way that allows them to give explanations that make their ideas (new and old) accessible. Of course the most cutting edge math has become completely inaccessible for even many mathematicians, but at the same time, we've made massive progress in this regard. A hundred years ago college students might barely see calculus, and only serious researchers would see something like group theory. Today, many college students that aren't even math majors learn group theory and (we hope that) this gives them cognitive tools that they can apply in other situations (ability to axiomatize a concept, abstract reasoning etc).

The concern with how these tools are being used is that the current push by AI companies to solve math problems by chucking LLMs at them and producing a proof in Lean, and then using that as currency in the media to increase their stock value, undermines this process because it produces "proofs" without producing the understanding that actually allows humans to think better. All of this is then marketed as being the same as doing mathematics which it manifestly is not. If mathematicians lose the media war though, we'll have a generation of people who believe "math has been automated" and are unlikely to put in the effort to learn how to think for themselves.

To the extent that this event is intending to help the mathematical community find ways to use LLMs in pursuit of improving human understanding and intelligence, as the organizers seem to say it is, I think it's a very laudable goal. But I don't really see how this event is supposed to do that. It sounds a lot more like another fundraiser for team "isn't it cool that AI can produce useless chunks of computer code that compile to prove statements that the vast majority of the people commenting on these results don't even understand." For example, if it's really about finding ways to use LLMs to produce mathematics that improves human understanding, why is there even a requirement to solve a new problem? Why not make it explicitly about using LLMs to produce pedagogical content? Or if you really want it to be a new problem, why not add a requirement that the final product has to be accessible to a broad audience (say relying only on material in the undergraduate curriculum)?

P.S. There's another scenario where "not solving the problems" is morally justifiable: the scenario where the "solution" provides very little value (say because of what I said above - the solution just being a Lean artifact that adds very little to anyone's understanding), and the cost of solving the problem is extremely large. I know a lot of AI people are effective altruists, but before they could smell the IPO money I didn't see any of them talking about how if they had $20 million the most effective thing they could do with it is spend it in an extremely environmentally costly way in order to prove Navier-Stokes. Back before AI I seem to remember these folks talking about like... mosquito nets and malaria treatments?

user:	maths_math
created:	September 10, 2026
karma:	3