Tao and Fields Medalists' two objections to AI in math, and why they're weak
RexDouglass · x · 2026-09-12
Stefanos Batzoglou summarizes and pushes back on the misalignment points Terence Tao and other Fields Medalists see in AI's use in mathematics:
- Advancing understanding: solving problems is only a proxy for developing theories and methods, and AI solutions may be unreadable/incomprehensible.
- Training mathematicians: AI stronger than humans that clears human-accessible open problems reduces the incentive to train mathematicians in constructing hard proofs.
He argues both are weak: mathematicians themselves show little interest in communicating results understandably — even top researchers struggle with adjacent fields — and AI may actually vastly improve the comprehensibility of math. The thread stems from a Terence Tao reference shared by Andrew Curran.
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