Twenty-five prominent mathematicians signed an open letter warning that AI laboratories’ race to achieve breakthroughs in famous mathematical problems could harm the open structure on which scientific research is based. All the signatories hold the Fields Medal, considered one of the highest honors in mathematics.
The letter comes as a dispute escalates between OpenAI and several academic researchers. Tristan Buckmaster, a professor at New York University (NYU), accused the company of pressuring him not to credit a collaborator working at Anthropic, following the solution of an important mathematical problem. He also questioned whether OpenAI had used work completed through Codex to produce its own proof during an extended period of reasoning. According to the article, OpenAI’s proof remains undocumented or unverified.
In another development, OpenAI withdrew its sponsorship this week of a mathematics event at the California Institute of Technology (Caltech), following criticism from researchers at the institute. The source provides no additional details about the reasons for the withdrawal or the nature of the criticism, but places the move within the context of growing tensions between laboratories and universities.
The Problem Is Not Just Solving the Problem
The letter acknowledges that models’ ability to solve open mathematical problems could benefit humanity, but links that benefit to the mathematical community’s ability to understand and explain the solutions and integrate them into existing knowledge. The signatories warn that rapid announcements of results may leave insufficient time to prepare a mathematically reviewable presentation, isolate new methods and ideas, and cite previous work.
According to the letter, this raises sharp questions about attribution and the possibility of plagiarism, particularly when an AI-assisted result is presented before other researchers can verify it or determine its relationship to earlier work. The letter also emphasizes that mathematics consists of more than proofs; it involves a broader process that includes teaching students, posing new questions, developing ideas, and passing them between generations.
Why Does This News Matter?
The practical issue highlighted by the dispute is an incentive imbalance. AI laboratories capable of spending tens of millions of dollars to run models may be able to reach a useful path toward a problem before the researchers who began working on it. If the rules governing attribution, documentation, and reciprocal use of tools are unclear, this could lead researchers to share less of their work or avoid using AI tools out of fear that their results will be incorporated into later models or attributed to another party.
The letter follows the “Leiden Declaration,” issued by a group of mathematicians in June, which likewise addressed the impact of language-model proofs on the profession and offered recommendations for mathematicians, institutions, and policymakers. This indicates that the discussion is no longer about an isolated incident, but about an early attempt to establish standards for transparency, review, and attribution.
Fundamental questions remain open, including how to establish the source of ideas used in a proof generated with model assistance, who bears responsibility for verifying it, and how to protect the culture of open research without hindering the benefits of new tools. The website argues that these questions concern more than mathematics; the tension between the speed of AI systems and the requirements of documentable creative work could emerge in the same way in other scientific and professional fields.