Twenty-five Fields Medallists, mathematics' highest honor, have issued an urgent declaration warning that artificial intelligence companies' push to solve major mathematical problems as benchmarks is fundamentally misaligned with how mathematics actually advances. The mathematicians argue that AI's focus on producing fast answers threatens to undermine the collaborative, human-centered process through which mathematical insights are developed, refined, and integrated into the broader scientific canon.

Why Are the World's Top Mathematicians So Concerned About AI?

Over recent months, large language models (LLMs), which are AI systems trained on vast amounts of text to predict and generate human language, have become dramatically better at solving complex mathematical problems. This capability has generated headlines and attracted significant investment from technology companies eager to use mathematical problem-solving as a benchmark to demonstrate AI progress. However, the mathematical community sees a fundamental problem with this approach.

The issue isn't that AI can solve problems. Rather, it's that solving problems has never been mathematics' true goal. According to the declaration signed by luminaries including Terence Tao, Peter Scholze, and James Maynard, the real purpose of mathematics is conceptual understanding and insight. When AI companies rush to announce solutions without proper writeups, without isolating new methods and ideas, and without crediting previous work, they're treating mathematics like a competitive sport rather than a collaborative intellectual endeavor.

"Solving problems is only a tool and proxy for achieving the primary goal of conceptual understanding and insight. Forgetting this in the world of AI may turn the tool against the primary goal. Indeed, the mass production at faster and faster pace of 'true/false' statements could destroy fertile ground instead of breathing life into new ideas," the declaration states.

Fields Medallists Declaration, September 2026

What Makes This Different From Previous Scientific Breakthroughs?

Mathematics has historically functioned as a miniature version of human society, with individuals using diverse approaches united by shared values. The profession's most precious resources are students and ideas, which the community nurtures carefully over time. When a mathematician solves a famous problem, the real work begins: the solution must be written up clearly, connected to previous ideas, simplified for broader audiences, and eventually integrated into textbooks that future generations study.

This process takes time and depends entirely on human interaction. A graduate student learning from a professor doesn't just absorb an answer; they absorb methods, intuition, and ways of thinking that enable them to formulate new questions and solve new problems. This transmission chain is what keeps mathematics alive and growing. When AI produces solutions without this human integration, something crucial is lost.

How Are AI Companies' Goals Misaligned With Mathematics?

The declaration identifies several specific ways that AI companies' incentives conflict with the mathematical community's values:

• Speed Over Understanding: AI companies announce solutions in a rush, leaving no time for proper writeups, isolation of new methods, identification of novel ideas, or citation of relevant previous work.
• Attribution and Plagiarism Risks: Without careful documentation and human review, it becomes impossible to determine whether an AI solution represents genuinely new mathematical insight or is simply recombining existing ideas from its training data.
• Loss of Human Transmission: Without mathematicians willing to take care of developing and integrating AI-conceived ideas into the mathematical canon, those ideas never become fully alive and the crucial human knowledge transfer between mathematicians is broken.
• Benchmark Obsession: The focus on solving famous problems as AI benchmarks treats mathematics as a collection of discrete challenges to overcome, rather than as an interconnected landscape of understanding that builds over generations.

The signatories include Fields Medallists from across the globe and across decades of mathematical achievement, spanning from Pierre Deligne (Fields Medal 1978) to Yu Deng (Fields Medal 2026). Their collective concern suggests this isn't a niche complaint but a widespread anxiety about the direction of the field.

Is This Problem Limited to Mathematics?

The mathematicians explicitly frame their concerns as part of a broader alignment problem affecting multiple fields. They note that similar issues are emerging in other scientific and creative professions, and may eventually confront all of humanity. The core issue is that years of training in any field traditionally serve two purposes: producing a final answer or product, and developing understanding and the ability to formulate new questions. As AI becomes capable of producing results directly, these two goals cease to align.

"We are witnessing a general threat to intellectual work, with misalignment between the outcome of the use of AI and its initial purpose," the declaration warns.

Fields Medallists Declaration, September 2026

This concern extends to how AI might reshape education, research incentives, and the very structure of knowledge work across society. If AI can produce publishable results without the human learning process that traditionally accompanies such work, what happens to the next generation of scientists, mathematicians, and thinkers who need that training to advance their fields?

What Do the Mathematicians Want to Happen Now?

The declaration calls for urgent action at multiple levels. The mathematical community itself must adapt to these changes thoughtfully. Technology companies developing these systems must reconsider how they deploy AI in ways that respect the goals and values of the fields they're disrupting. And society more broadly must grapple with how to ensure that as AI changes the way work is done, we don't lose sight of what that work was meant to achieve in the first place.

The mathematicians acknowledge that AI offers genuine potential to enhance and accelerate mathematical study and understanding. The question is not whether AI should be used in mathematics, but how it should be used in ways that strengthen rather than undermine the field's core mission. Whether these changes ultimately benefit mathematics or have a destructive effect will largely depend on decisions made by the humans in control of this new technology.

The declaration has already been translated into French and published in Le Monde, and it continues to gather additional signatures from mathematicians worldwide. The urgency with which the Fields Medallists released their statement, without waiting for the more consultative process used in previous declarations like the Leiden Declaration, underscores how seriously they view the situation.