Twenty-five Fields Medal-winning mathematicians have signed an open letter arguing that AI labs are threatening their intellectual work as those labs race to produce solutions to famous math problems. The letter contends that AI-generated proofs are often announced in a rush, leaving no time for proper writeups, isolating new methods, or citing prior work, which raises severe attribution and plagiarism questions. The signatories also warn that without mathematicians to develop and integrate AI-conceived ideas into the mathematical canon, those ideas would never become fully alive, and the human transmission chain between mathematicians would be lost.

The conflict escalated this week on multiple fronts. NYU professor Tristan Buckmaster accused OpenAI of pressuring him not to credit a collaborator who works for Anthropic for solving an important math problem, and he questioned whether OpenAI used his team’s work with Codex to produce its own groundbreaking proof over a marathon weekend of inference. OpenAI‘s proof remains unverified. Separately, OpenAI withdrew its sponsorship of a math event at CalTech after researchers at the university criticized the company. The article notes that some mathematicians now fear that their own Codex use was fed into OpenAI‘s new models, and that the culture of open research is at risk: if frontier labs see a useful path to a discovery, they can spend tens of millions of dollars using LLMs to beat the original researchers to a proof, a dynamic that incentivizes secrecy.

The open letter follows the Leiden Declaration, released in June by a working group of mathematicians, which also addresses how LLM proofs will change mathematical work and offers recommendations for mathematicians, institutions, and policymakers. The core argument, as with software engineering and other AI-affected fields, is that the value in math is not just proofs and credit, but the intellectual superstructure that nourishes students, finds new questions and ideas, and integrates them into broader human civilization. The mathematicians explicitly frame their concerns as a preview for everyone else: the issues their community faces now are similar to issues other scientific and creative professions face, and indicate issues all of humanity might face—how to ensure that as AI changes how work is done, we do not lose sight of what that work was meant to achieve.