OpenAI’s October 6 rollout of more than 700 research papers claimed solutions to numerous landmark questions, sparking both awe and fierce professional backlash. The release directly touched leading figures like Hugo Duminil-Copin, who saw claims resolving every open problem he had publicly cited across his entire career. However, the machine-generated work made barely a dent in other central challenges, including functoriality and reciprocity within the Langlands program. Because scholars still retain control over hiring, publishing, and student training, they possess the agency to channel these computational breakthroughs into productive, deeper mathematical exploration.
Key points
Academic researchers must proactively modernize their publication, hiring, and mentorship…: Academic researchers must proactively modernize their publication, hiring, and mentorship practices rather than resisting artificial intelligence tools.
Solving prominent benchmark questions risks dampening broader research interest, echoing…: Solving prominent benchmark questions risks dampening broader research interest, echoing historical precedents like Dan Gorenstein's finite simple group classification.
Scholarly communities retain full institutional authority to set research priorities that…: Scholarly communities retain full institutional authority to set research priorities that reward deep inquiry over automated proof generation.
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[This is a guest post by Frank Calegari. This blog post was initially written in a different file format and converted using AI. — T.]
Why we should not be sad
The release by OpenAI on October 6 of over 700 research papers was a watershed in the history of mathematics. AI is now undeniably capable of making groundbreaking contributions across many areas of mathematics. So why are some mathematicians so unhappy?
Some of it is the apparent disregard by AI companies for the practice of mathematics. The OpenAI papers — despite some tremendous ideas — are atrociously written and violate our community expectations of attribution. Some of them are even wrong. We have much more control over how we hire mathematicians, publish papers, and train students than over the behavior of trillion-dollar companies, and that is where our efforts would be better spent.
Much of the reaction seems to reflect a feeling that the subject that they love is under attack, and is being “hollowed out”. The recent OpenAI dump made barely a dent on the general problems of…
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