Terence Tao, a child prodigy turned Fields Medalist and UCLA’s youngest full professor, discusses how artificial intelligence is changing mathematical practice and the role of mathematicians. He argues that math has been slower than other sciences to scale and crowdsource work, but AI and formal-verification tools now make it possible to run large, dataset-driven “clinical trial” style experiments on techniques, improve the quality of amateur contributions, and massively accelerate the production of verified proofs. Tao embraces citizen science, online literature searches and AI-assisted reference gathering, and sees formal verification as a crucial filter that can transform how discoveries are made and validated.
He also warns about concrete downsides and risks: over-reliance on AI can erode student learning (an analogue to early calculators), reduce serendipity that comes from informal research habits, and strip away the broader roles mathematicians play - teaching, connecting ideas, and public advocacy (the “doorman fallacy”). AI systems still make ungrounded errors, so verification is essential. To address this, Tao leads a DARPA-funded ALPHA project (3 years, $5 million) to build neuro-symbolic tools for formal proof synthesis and expansion of the library of formalized mathematics, and he warns that a weakened U.S. science funding ecosystem makes defending basic research more urgent.
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