Aside from the printing press and the digital computer, mathematics has been relatively free of fundamental perturbation for centuries. AI is changing that, rapidly, and more fundamentally than anything before it, for better and worse. This year, AI began to create sporadic and elemental discoveries in mathematics, then came a steady trickle of even more impressive progress. Now, we have reached a powerful surge with OpenAI solving a problem related to Navier-Stokes equations, one of the most famous in mathematics. How far this progress will continue is unclear, but what is certain is that the role of a mathematician, their ways of working and the processes and norms of the field will all be upset. Advertisement Helen Wilson at University College London says that academics are still processing what’s happening. “With any new development I have colleagues who I can guarantee will think it’s the end of the world, and colleagues who I can guarantee will think it’s the best thing since sliced bread, and this one’s no different,” says Wilson. “I’m in the ‘a bit terrified’ camp.” Some mathematicians fear for their careers in a world where computers can solve problems that they can’t. But that is a reason to be optimistic too. AI seems able to use existing knowledge at rapid speed to crack some of the meatiest mathematical conundrums. Perhaps mathematicians will prosper in the future as the controllers of such powerful tools, pushing the field further than they ever thought possible. “We have so many questions that we don’t know the answer to, and where it was extremely difficult to make progress – like really a struggle of a lifetime. Now we’re gonna be able [to answer them],” say Sébastien Bubeck at OpenAI, speaking to New Scientist before the Navier-Stokes announcement. But other changes are more problematic, like how we train new mathematicians. Currently PhD students are often given a relatively low-level problem to chew over for a few years and hone their skills on,
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