Knowledge Collapse - Boston Review

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June 10, 2026

Eleven years ago, the mathematician Stefaan Vaes, upon receiving the prestigious Francqui Prize for young scientists from the hands of Belgium’s Queen Mathilde, took the opportunity to tell Her Majesty why we mathematicians choose such a misunderstood profession. “Omdat wij dit graag doen,” he said—because we like it. A few years before that, another Belgian, Pierre Deligne, on the occasion of his selection for the Abel Prize—often called the mathematician’s Nobel Prize—explained that he decided on a career in mathematical research when he learned that “one could earn one’s living by playing.”

What both Belgians were saying is that mathematical research constitutes what Henri Poincaré, the great French mathematician, called a “free creative art”—one of the rare remaining examples of unalienated labor. For how much longer?

AI has been targeting mathematics, as both a challenge and a trophy, since its beginnings in the 1950s. Three years after the phrase “artificial intelligence” was coined in the run-up to a legendary 1956 conference at Dartmouth, Alan Newell and Herbert Simon predicted that within a decade, digital computers would reach four milestones—matching human capabilities in mathematics, music, chess, and psychotherapy—on the road to a “world in which [human] intellectual power and speed are outstripped by the intelligence of machines.” The deadlines, periodically revived, came and went; finally, in 1997, IBM’s Deep Blue defeated Garry Kasparov. Progress toward the other milestones largely stalled until the deep learning revolution of the 2010s, when the Newell-Simon program took on new life, amplified by the colossal wealth and ambition of Silicon Valley.

With the rise of generative AI, we are now seeing regular predictions that human mathematical power is at last on the verge of being outstripped, whether or not anyone likes it. From the New York Times publishing an article under the title “AI Is Coming for Mathematics, Too,” to serious journals like Science and Nature repeating industry talking points, the general public is repeatedly being told that mathematics will be the next domino to fall on the inevitable march to artificial general intelligence (AGI). Among mathematicians, versions of the following syllogism have been circulating in recent years with increasing urgency:

They said an AI could never solve Go

But AlphaZero solved Go

Go is a game

Mathematics is also a game [see “playing”]

Therefore, AI will “solve” math.

The annual International Mathematical Olympiad, once a contest for talented high school students, is now the occasion for DeepMind and OpenAI to announce the success of their latest models: silver medal in 2024, gold medal in 2025. Students training to be mathematicians—because they like it—are asking whether their chosen life path has a human future, and the mathematical community has generated its own versions of boomers and doomers.

“Computational Intelligence is the manifest destiny of computer science,” Edward Feigenbaum wrote more than twenty years ago: “the goal, the destination, the final frontier.” Mathematical boomers share Feigenbaum’s romantic vision; in this they are encouraged by funding agencies like the National Science Foundation (NSF), whose new Institute for Computer-Aided Reasoning in Mathematics at Carnegie Mellon aims to “empower mathematicians to take advantage of new technologies for mathematical reasoning,” as well as by established industry labs and startups like Axiom, which promises, “We stand at the threshold of a mathematical renaissance.” The collective market capitalization of such ventures would suffice to fund 200 math PhDs—the number lost this year in the United States due to cuts to graduate programs—every year for the next 500 years.

For their part, the doomers take the syllogism literally: they agree with the New Scientist that AI “is rewriting what it means to be a mathematician,” and while they “are still hopeful there will be a place for them in an increasingly machine-led future,” they anticipate “a world in which AI mathematicians take humans ‘out of the loop’ entirely.” Meanwhile, to the simmering frustration of those keyed in to our profession’s purported manifest destiny, the vast majority of mathematicians go about their routine, and like it, oblivious to the looming boom and/or doom.

To those not already convinced that work ought to be a source of pleasure, talk of earning one’s living by playing doesn’t sound very serious, so mathematicians typically look for a more respectable name for what we seek. Given the subject’s reputation for impenetrability, it might be surprising to learn how often we choose the word understanding. “You do mathematics,” the number theorist Barry Mazur writes, “because you want to apply your findings to real-life questions or because you are seeking some pure understanding.” The word “understand” appears in the...