GoKawiilMathematician Francesco Maggi warns AI could erode human understanding of science
In a guest essay on Terence Tao's blog, mathematician Francesco Maggi argues that large language models have become genuinely powerful tools for generating mathematical proofs, citing examples like an LLM-assisted construction of a finite-time blow-up solution to the Navier-Stokes equations and a proposed proof related to the Riemann Hypothesis. He outlines two possible futures for science: a 'golden age' where AI empowers broader human expertise, or a 'dark age' where output surges but knowledge becomes concentrated among few people and increasingly incomprehensible to humans.
GoKawiil's interpretation of the reporting above, not reported fact.
Maggi's framing suggests the real risk isn't AI failure but AI success without safeguards, where scientific progress could outpace human comprehension and democratic access to knowledge. His call for continuous independent scrutiny implies that verification and transparency practices may need to evolve alongside AI capabilities. The essay positions this as a choice point for the mathematics and broader STEM community, not an inevitable outcome.
- LLMs have produced notable results including a Navier-Stokes blow-up construction and a proposed Riemann Hypothesis-related proof
- Maggi presents two contrasting futures: an open 'golden age' versus a concentrated, less comprehensible 'dark age'
- The essay calls for deliberate integration choices to preserve collaborative, human-understandable scientific progress
Source: terrytao.wordpress.com — Terence Tao, 2026-10-18
Published there as: “Will it be a golden age or a dark age for mathematics (and science)?”
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