“A lot of the reason why people do pure math, even though it pays so much less than industry, is because you get to author your own creative contributions and then give them to a community that appreciates them for their intellectual beauty,” Chu said. “This environment where mathematical discourse is centered around machines talking and humans listening, I don’t think it’s a very attractive one.”

And AI is itself undermining the kind of education that would be necessary for that role. This came up at the Berkeley colloquium, too. “There’s a serious risk that 20, 30, 40 years from now, there will be no people around who have the same classical mathematics training,” one student said. “I’m worried about a world where the full body of mathematical knowledge is inaccessible.”

The result could be a lost generation. Goh is one of many young mathematicians struggling with the angst such a future is producing, and with what he sees as a lack of effort on the part of working mathematicians (at least until very recently) to remake the incentives to avoid it.

“There’s something sick about the culture,” he told me. “I didn’t think so, but now I do.”

Goh is alarmed by how some have taken up AI without enough critical thought, and he feels pressured to use it so that he doesn’t get left behind. “I was just very depressed about that,” he said. “That doesn’t feel inspiring to me. … It didn’t have to be this way.”

He likens it to Saruman from The Lord of the Rings, corrupted by the promise of unlimited knowledge and power. Goh and a growing number of mathematicians are starting to consider themselves AI “vegetarians,” (opens a new tab) consciously measured in their use of the technology. There’s nothing rewarding or interesting or fun about offloading their cognition to a machine, they argue.

This is a very thorough discussion of how AI interacts with cutting edge science and math, I know this is a well worn topic here and elsewhere but this along with the linked podcast is the best, most up to date, perspective I have found from science experts about AI and science/math.

see this podcast about AI "solving" the Navier-Stokes equation for fluids.

https://www.newscientist.com/podcasts/ai-just-solved-one-of-the-hardest-problems-in-mathematics/

^ TL;DL All scientific advance is people building on people, the great man hypothesis reflected into computers into a great computer hypothesis is what this AI hype really is, the AI was able to connect the dots between converging research faster than a human could... but ok....?

True scientific advance involves a one-two punch to your face, first you get the jab of proving something novel or that has stumped scientists for a long time up until that point and then you hit them with a full power punch of insight to seal the deal. This is only the first part, and to say "AI did it" is to again lean into the "great man hypothesis" but you have replaced the great man with a great computer...