‘I’m Really Terrified’: A Mathematician Grapples With AI’s Recent Breakthroughs

Mathematician and author Steven Strogatz starts to cry when he talks about the artificial-intelligence-driven breakthroughs in his field over the past week.

“The science is thrilling,” the Cornell University professor says, “but there’s a lot of human unpleasantness going with it.”

On Tuesday, OpenAI said it had used tens of thousands of agents to solve a 90-year-old math problem, which had a $1 million prize attached. The solution—which still needs to be independently verified—builds on a strategy developed by Spanish mathematicians Diego Córdoba and Luis Martínez-Zoroa. The announcement was marred by claims from another mathematician, Tristan Buckmaster, who says that OpenAI rushed ahead to solve the problem after learning of his work alongside Anthropic researcher Levent Alpöge. Buckmaster claims OpenAI also tried to influence who got credit for the work.

The rupture is a symptom of the rapid changes taking place in the field due to AI advancements and what Strogatz—who cowrote Big Math, a book about how math is slipping away from human understanding that will be out in November—describes as corporate labs’ race to grab headlines ahead of blockbuster IPOs.

Last week, Anthropic said Claude had proved 29,500 small theorems while formalizing an existing proof of the infamous Fermat’s Last Theorem—a project other mathematicians had been working on for years. In August, OpenAI announced it had made advancements in 10 other long-standing mathematical problems. AI is making mathematical breakthroughs happen faster, Strogatz says, but what it means for the experts who have dedicated their lives to the field is decidedly less clear.

“I think the year 2026 is going to be remembered as either an annus mirabilis or annus horribilis for mathematics because so much has happened,” Strogatz tells WIRED, sitting in front of a wall covered in framed university honors. “You will not be able to compete without AI in the future if you want to do breakthrough math,” he adds.

His book collaborator, Alex Townsend has already been using the technology to accelerate their research. He recently used ChatGPT to help solve a decades-old numerical linear algebra problem. Toward the end of the interview, Townsend walks into Strogatz’s attic. Townsend and his coauthor said that without the technology, the volume of work required and cost-reward ratio would have been unfeasibly high. But while AI has helped his work, it’s also changing how Townsend views the field and his role in it.

“I actually feel kind of upset that I’ve dedicated 15 years of my life to research mathematics, and at a point in my career where I’m very productive and at my peak strength as a mathematician, that peak skill is no longer there. Something is able to surpass me,” he says. “Before, it was so exciting because you’re world-class, doing great research, pushing back the frontier of knowledge, and now I don’t feel like I’m the one at the frontier of knowledge. I’m the one with an AI agent, which feels very different actually. And I feel totally threatened by it.”

For his part, Strogratz likens the current moment for math to a horror movie, as AI, driven by systems that are not well understood, creeps closer and closer. “But we’re not at the end of the movie yet,” Strogratz says. “Instinctively, I’m really terrified.”

Here, he reflects on what the AI breakthroughs of 2026 mean for math, mathematicians, and humanity. His answers have been lightly edited for brevity.