OpenAI’s feud with mathematicians is only escalating

OpenAI 与数学家之间的矛盾正在不断升级

Twenty-five leading mathematicians signed an open letter arguing that AI labs are threatening their intellectual work as they seek to one-up each other with solutions to famous math problems. Each signatory has been awarded the Fields Medal, considered the most prestigious prize in mathematics. 二十五位顶尖数学家签署了一封公开信，指出人工智能实验室在竞相解决著名数学难题的过程中，正在威胁到他们的智力成果。每位签署者都曾获得被视为数学界最高荣誉的菲尔兹奖（Fields Medal）。

This week, 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 wondered if the company had used their work with Codex to produce its own groundbreaking proof over a marathon weekend of inference. On Thursday, OpenAI withdrew its sponsorship of a math event at CalTech after the company was criticized by researchers at the university. 本周，纽约大学教授 Tristan Buckmaster 指责 OpenAI 向他施压，要求他不要将一项重要数学难题的解决归功于一位在 Anthropic 工作的合作者。他还质疑该公司是否利用他们使用 Codex 的工作，在一次马拉松式的推理周末中得出了自己的突破性证明。周四，在遭到加州理工学院研究人员的批评后，OpenAI 撤回了对该校一场数学活动的赞助。

While the ability of AI models to solve the world’s outstanding mathematical challenges could be a boon to humanity, the signatories of the new letter argue that will only be the case if those solutions can be understood and communicated by the math community and, ultimately, the rest of the world. “Often these solutions are announced in a rush, leaving no time for a proper writeup, the isolation of new methods and ideas, and citing relevant previous work of others,” they wrote — and OpenAI’s proof remains unverified. 虽然人工智能模型解决世界性数学难题的能力可能造福人类，但公开信的签署者认为，只有当这些解决方案能够被数学界乃至全世界理解和传播时，这种益处才能实现。他们写道：“这些解决方案往往被匆忙公布，没有时间进行适当的撰写、提炼新方法和新思想，也没有引用他人的相关前作。”而 OpenAI 的证明目前仍未得到验证。

“As in all creative professions, this raises severe attribution and plagiarism questions. Moreover, without the willing mathematicians who must take care of their development and integration into the mathematical canon, AI-conceived ideas would never become fully alive and the crucial human transmission chain between mathematicians would be lost.” “正如所有创意行业一样，这引发了严重的归属权和剽窃问题。此外，如果没有愿意负责其开发并将其整合进数学体系的数学家，人工智能构思的想法将永远无法真正‘活’起来，数学家之间至关重要的人类传承链条也将断裂。”

With other mathematicians growing paranoid and wondering if their Codex use was in turn fed into OpenAI’s new models, there is real fear that the culture of open research will be threatened. Today, 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 will incentivize secrecy. 随着其他数学家变得忧心忡忡，怀疑他们使用 Codex 的记录是否被反过来喂给了 OpenAI 的新模型，人们确实担心开放研究的文化将受到威胁。如今，如果前沿实验室发现了一条通往发现的有效路径，他们可以花费数千万美元利用大语言模型（LLM）抢在原始研究人员之前得出证明——这种动态将助长保密之风。

This letter follows the Leiden Declaration, released by a working group of mathematicians in June. That document also grapples with the ways that LLM proofs will change their work and offers a set of recommendations for mathematicians, institutions, and policymakers. As with software engineering and other areas where AI tools are changing workflows, mathematicians find a justification in the work around the work: The value in math isn’t just the proofs and who gets credit, but the intellectual super-structure that nourishes students, finds new questions and ideas, and integrates them into broader human civilization. 这封信继今年 6 月由一个数学家工作组发布的《莱顿宣言》（Leiden Declaration）之后发出。该文件同样探讨了 LLM 证明将如何改变他们的工作，并为数学家、机构和政策制定者提供了一系列建议。正如在软件工程和其他人工智能工具正在改变工作流程的领域一样，数学家们在“工作之外的工作”中找到了意义：数学的价值不仅在于证明本身以及谁获得了功劳，更在于那个滋养学生、发现新问题和新思想，并将其融入更广泛人类文明的智力上层建筑。

And if you don’t particularly care about the cutthroat world of high-stakes mathematical proofs, don’t forget: Your field of interest is next. “The issues the mathematical community faces now are similar to issues that other scientific and creative professions are facing, and indicate issues that all of humanity might face: how to make sure that, as AI changes the way work is done, we do not lose sight of what that work was meant to achieve in the first place,” they wrote. 如果你并不关心高风险数学证明那残酷的世界，请别忘了：你所关注的领域将是下一个。他们写道：“数学界现在面临的问题，与其他科学和创意行业面临的问题相似，这也预示着全人类可能面临的问题：如何确保在人工智能改变工作方式的同时，我们不会忘记这项工作最初旨在实现的目标。”