> Terence Tao (2026) lists many goals of mathematics beyond problem solving. These include developing new theories and techniques, understanding the world, sustaining a community, training the next generation of mathematicians, contributing to cumulative knowledge, and creating works of aesthetic value. Of course, these have been positively correlated with genuine solutions.

> If, instead, mathematicians treat AI as a technology for advancing its long-standing and centrally human purposes, the technology may come to contribute to an accelerated flourishing and enrichment of the discipline.

For the longest time, people who conducted research (not just math) ranked and measured their peers (albeit quasi-subjectively) by 1.) their ability to solve difficult problems, 2.) the cleverness of their solutions, and 3.) the clarity of their explanations.

With the advent of these models, we're understandably worried because #1 and maybe #2 may be gone (maybe even #3).

Are researchers going to shift the ranking/measuring of their peers over to ... "so-and-so is a world-class explainer of AI proofs"?

If you go around telling people, "no no no. You don't understand. The important part of our intellectual work is now going to be <something that was never weighted highly>", well, then it feels like you're handing me a participation trophy and telling me I came in 1st place.

I have no idea how the next 5 years will shake out, but I think that's why there's a lot of anxiety at the moment.