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This does not quite fall under culture wars, but I thought it's still relevant given that it's a big story.
On October 6, OpenAI released a large batch of mathematical results, with more than 700 manuscripts covering hundreds of problems: Sharing AI progress in mathematics.
This has led to another round of controversy and discussion about AI making mathematicians obsolete or disrupting research programs that people have spent years working on. The Verge covers some of these reactions in “Mathematicians will need years to make sense of OpenAI’s latest drop”.
Many of the results are still being checked, but the release has called into question if mathematics can survive as a profession, or what purpose it serves if machines can outpace humans. Research programs have supposedly been gutted by these results. "Careers ruined," as the narrative goes. I think that is an exaggeration or overreaction. There are thousands of mathematicians and their interests are very wide ranging. The odds of someone's research program or problem being "solved" by AI are very small.
I don't see anything changing much. The status quo of journals and academia will remain intact even with rapid progress in AI, save for the occasional breakthrough in an unsolved problem. What is overlooked or ignored is the massive gap between cotemporary research-level math vs. LLM-produced math. A math PhD program, especially from a good school, teaches or guides future researchers towards productive areas of research that are of interest to the "math community," rather than results that are merely "personally interesting". AI cannot recreate such communities or networks.
AI is great for generating computation-laden results on-the-fly, but research-level math is more concerned with abstractions and relations between them, than crunching. I recall one example where ChatGPT’s Astra program tried to pass off a finite computational cutoff as a “theorem.” Um, you can't do that unless you prove that the bound is sufficient.
To test this, I produced some AI papers which I thought were great and novel, and the AI said so, and journals rejected them (although others are still pending at various stages of peer review). I had some knowledge in said area and could assess novelty, but still not good enough. I don't see laypeople doing better in this regard, although could be wrong. I ran my ideas through the Ai and got 12 papers out of it, which saved considerable time had I written them myself. It also found non-obvious connections and results. I am really satisfied with the results, but does this meet the bar for publication? Time will tell. I bet not.
Also, success is heavily dependent on the prompt. It's not as easy as blindly prompting something. I made a post about that https://greyenlightenment.com/2026/10/11/the-nuance-the-math-debate-is-missing/ I suspect many of these successful proofs were prompted by experts who knew what to look for, rather than just naively trying. What is touted by the media as an AI breakthrough, may involve surgically precise prompting in the background by an expert in said field.
Alluding to the "airplane meme," there is also survivorship bias: you don't see all the failed attempts with AI . Sometimes it works great, but other times hit or miss. Presumably , the "top unsolved problems" have been queried by frontier models and using large token budget, with few proofs to show for it (save for the Open AI "dump").
It would be cool to see AI truly shake -up math and breathe new life into ignored areas, but that is not going to happen, imho. But I do see AI leading to a 2-track system of decentralized preprints and GitHub repositories of AI-produced results, alongside established academia and journals. They will coexist, rather than the later being obsolete. Overall, mathematicians don't have to fear losing their jobs anytime soon (unless of course you happen to have the precise problem you are working on scooped by AI, and even then, your skills would presumably transfer to new problems.
I'm not a mathematician, but if I were one, a significant one of my goals and motivations would be to find an elegant proof/disproof for some conjecture which is fairly widely known and unresolved. I would like the satisfaction of having solved a significant problem which nobody (no person or artificial entity) had solved before and I would also like the respect from my peers for having been first to come up with my elegant proof/disproof.
Do you think that AI threatens to take this possibility away in the near future? I'm not an expert, but it seems to me that the answer is "clearly yes."
As alluded to above, I work in a different field. A few years back I started a business with a creative idea, put the business together, encountered a decent amount of success and eventually sold for a substantial amount of money. Not tech billionaire level wealth, but still a respectable amount. I feel pretty good about the whole experience and I worry that the next generation probably won't have that kind of opportunity. Because AI will be just a lot better at coming up with creative ideas and then executing on them.
I feel like we humans are basically John Henry facing off against the steam shovel. Yes, we can put up a romantic fight, but at the end of the day it's a losing battle.
Come to think of it, I've consumed a lot of media about this topic, and for some reason I think this is the first time I've seen John Henry brought up. Even though it's kind of the obvious parable...?
I would guess that over the years, the legend of John Henry has become more of a racial thing than a man vs. machine thing. Which is really a shame in my opinion, because I think his value as a folk hero vastly outweighs his significance as a black person.
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Perhaps because those of us who have thought of it prefer not to bring it up.
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