Throughout the summer of 2026, artificial intelligence models were routinely announcing proofs of long-standing conjectures. So when OpenAI declared that its systems had resolved one of mathematics’ most celebrated problems on September 8, the announcement ignited an immediate firestorm over authorship and standards. Mathematics, it seemed, would never be the same.
“In whatever years I have left, I don’t expect that I’ll ever again prove a theorem because I’m actually needed to prove it,” Scott Aaronson of the University of Texas, Austin wrote on his blog. “Human mathematicians are forevermore dethroned as the main theorem-proving entities on planet earth.” Other voices expressed optimism, but many revealed a mixture of grief, confusion, and fear.
Two days after the announcement, I found myself in a classroom at the University of California, Berkeley, surrounded by roughly 150 students, postdocs, and professors. Ken Ono, who left academia for the AI start-up Axiom Math, was scheduled to speak. “You might be graduating into a profession that might not even exist, or that will be very different than what you expected,” Ono told them. “You need to brace.”
The audience reacted with anger and frustration. There were whispers and exchanged glances; Ono could not get through a single slide without a fresh wave of questions. “I’m not entirely sure what our takeaway is supposed to be,” one student said. Another asked how Ono and his start-up would take responsibility in light of “the shameful way that AI companies are treating mathematics.”
When Ono said that mathematicians would do their “very best” to avoid the bleak future the students envisioned, a third participant, hands trembling, retorted: “What are you doing? What is your ‘very best’?” The talk, including Q&A, had been allotted 50 minutes; it stretched to more than two hours. Many students lingered afterward, venting and consoling one another.
To me, the reasons for these emotional reactions were clear. The young mathematicians recognized that their field would have to change or risk obsolescence. What surprised me was that when I returned to New York and raised the issue with friends and family, they did not see the problem. All sorts of amazing discoveries are around the corner, they imagined. Wasn’t that the point?
These conversations exposed a long-standing problem: Many people do not know what mathematics really is, or why mathematicians do it. Now mathematicians need to answer that question for themselves and explain it to the rest of the world — quickly. How they answer will determine what happens next.
As an undergraduate, I studied both mathematics and literature. I always found that “pure math” — the study of mathematical concepts for their own sake, without concern for real-world applications — existed somewhere between the sciences and the arts. It prizes logic and certainty, but at its core lie fuzzier notions of beauty, intuition, and depth. “Math is either the most science-y humanities or the most humanities-type science, depending on who you ask,” said Marcel Goh, a doctoral student at McGill University. Usually it is utterly useless, yet time and again its abstractions demonstrate “unreasonable effectiveness” in applications to physics and beyond.
In mathematics, it is not a cliché that the journey matters more than the destination. Problems are posed not so much because their answers will be practical and important, but because they represent interesting journeys. The hope is that as mathematicians struggle to solve a problem, they will come up with intriguing tools and connections, stumble on novel ideas and directions, take fruitful detours, and answer new questions they never would have thought to ask.
“It was never about the theorems,” Goh said. “It’s to carry on a tradition that has benefited society despite not having any market value. To reason deeply, to understand the world … and to spread that knowledge.”
It breaks our system. It just takes it to its absolute limit and destroys it.
Tasmin Chu, California Institute of Technology
AI models skip to the end. At the moment, their proofs are nearly impossible to read. They elide salient details and waste pages on irrelevant concepts. They fail to demonstrate how the new work builds on or connects to other results in the mathematical literature. Mathematicians know that the proofs are true — they are verified by a system that checks their logic — but have no idea why. What is missing is understanding, the currency mathematicians trade in. If there is a journey, humans are not invited along for the ride.
It is as if you were teleported to the peak of a tall mountain. Surrounded by fog, you have no idea where you are or what is around you. You do not know how your mountain connects to others, and you have no equipment to help you explore, no way to help someone else join you. If you had climbed the mountain yourself, you would have experienced how the human body adapts to altitude and changes in oxygen levels. You might have had to invent tools to navigate, to climb steep cliffs, or to make a shelter. You might have encountered a fellow explorer, gotten lost together in a hidden valley, and found a plant that could be turned into a life-saving medicine.
Instead you are perched on the peak but in the dark, while the maker of the teleportation machine tells you that it can explore the wilderness better than any human.
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