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What happens to mathematics when doing mathematics is no longer an exclusively human activity?

For years, we’ve watched artificial intelligence get progressively better at math: solving equations, passing exams, succeeding at mathematical competitions, and generating proofs. But recent developments seem to cross a different kind of threshold. This month, OpenAI announced that an internal AI system had produced a solution to the Navier–Stokes existence and smoothness problem—one of the seven Millennium Prize Problems, designed to represent some of the most difficult unsolved questions in mathematics.

The announcement has generated excitement, skepticism, and controversy. But it also raises a much larger set of questions. What does it actually mean to do mathematics? Is mathematics about arriving at a correct answer, or understanding why that answer is true? What happens to ideas like discovery, creativity, and authorship when machines can participate in producing new mathematical knowledge? And what does that tell us about artificial intelligence—and about ourselves?

My guest today is Dr. Noah Giansiracusa, a math professor at Bentley University and a faculty associate at Harvard, with a PhD in algebraic geometry from Brown University.

Noah is cohost of the podcasts Breaking Math and AI in Academia, and his writing has appeared in The Washington Post, Scientific American, TIME, Wired, Slate, and The Boston Globe, among others.

His first book, How Algorithms Create and Prevent Fake News, examined the mathematics and technology underlying our information ecosystem. His latest, Robin Hood Math, asks how people from all backgrounds can use mathematics to navigate—and reclaim some control over—a world increasingly governed by algorithms.

Today, we’re talking about what happens when those algorithms begin doing mathematics themselves.