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MathChat

What are people saying about AI & Math?

Add your own · Current review map · People and sources · Join the discussion

Current viewpoint map

AI and mathematics viewpoints A scatter plot. The horizontal axis is evidence basis from speculative to data-supported. The vertical axis is outlook from anxious to hopeful. Circle size represents provisional source reliability. 0255075100 0255075100 Evidence basis: speculative (0) → data-supported (100) Outlook: anxious (0) → hopeful (100) Jeremy Avigad — outlook 64, evidence 76, reliability 88David Bessis — outlook 54, evidence 38, reliability 68Timothy Gowers — outlook 58, evidence 82, reliability 90Emily Riehl — outlook 56, evidence 86, reliability 90Terence Tao — outlook 61, evidence 78, reliability 88Jacob Tsimerman — outlook 88, evidence 55, reliability 76Max Weinreich — outlook 12, evidence 48, reliability 65Geordie Williamson — outlook 78, evidence 62, reliability 80 The Economist — outlook 28, evidence 86, reliability 72Jaron Lanier — outlook 60, evidence 36, reliability 64Francis Su — outlook 82, evidence 35, reliability 60Conrad Wolfram — outlook 72, evidence 68, reliability 78Yahoo News — outlook 30, evidence 70, reliability 55 Leiden Declaration — outlook 24, evidence 72, reliability 82Math and AI Declaration — outlook 63, evidence 61, reliability 74 Yann LeCun — outlook 65, evidence 65, reliability 84Gary Marcus — outlook 32, evidence 65, reliability 84Arvind Narayanan and Sayash Kapoor — outlook 38, evidence 78, reliability 82Stephen Wolfram — outlook 78, evidence 55, reliability 74 Sean Carroll — outlook 55, evidence 54, reliability 76Jordana Cepelewicz — outlook 64, evidence 76, reliability 82Sabine Hossenfelder — outlook 58, evidence 45, reliability 64Curt Jaimungal — outlook 76, evidence 55, reliability 70Brian Keating — outlook 61, evidence 58, reliability 74Steven Strogatz — outlook 60, evidence 70, reliability 84 AvigadGowersRiehlTaoTsimermanWilliamsonEconomistConrad WolframLeidenMath & AILeCunMarcusAI Snake OilS. WolframCarrollQuanta: CepelewiczJaimungalKeatingQuanta: StrogatzBessisWeinreichLanierSuYahooHossenfelder
Circle size = source reliability

On this first map, hopeful means that the source expects AI to have a net positive effect on mathematics or mathematics education—for example, by assisting discovery, explanation, accessibility, or formal verification. It does not simply mean “AI can do mathematics,” confidence in artificial general intelligence, or approval of every AI use. Conversely, an anxious score reflects concern about the net effect on learning, proof, research culture, or public institutions.

Each source is reviewed along three provisional dimensions:

  1. Outlook: anxious (0) to hopeful (100)
  2. Evidence basis: speculative (0) to data-supported (100)
  3. Source reliability: lower (0) to higher (100), based on relevant expertise, transparency, methods, primary sourcing, and relevance

What the map currently suggests

  • There is no simple pro-AI/anti-AI divide. Several optimistic sources also insist on verification, disclosure, and human responsibility.
  • The clearest empirical concern in this collection is educational: AI can improve visible homework performance while weakening unaided performance. That supports careful course and assessment design, not a blanket ban.
  • Research-mathematics sources focus on a different risk: generated claims and proofs may outpace the community’s ability to verify, understand, attribute, and teach them.
  • The broadest common ground is conditional adoption: use AI for explanation, exploration, routine tasks, and formal assistance; preserve independent practice and require transparent checking for consequential mathematical claims.

Current review map

Every source in the review, with its provisional scores and a link to the source itself, is on a page of its own.

Open the current review map

Explore, challenge, or extend the review

The complete public record includes the source ledger, scoring methodology, prompt and model-assisted review record, contribution guide, and a small interactive HTML version of the map.

Open the MathChat review repository on GitHub

A note on evidence

“Evidence basis” is not a measure of author prestige. It asks whether the source’s central claim is directly supported by relevant data, transparent methods, primary sources, and appropriate caution about uncertainty and causation. A thoughtful philosophical essay can be valuable while still scoring lower on this particular axis.

Leave a message

Questions, source leads, score challenges, and constructive corrections are welcome. Keep the discussion tidy, polite, and apolitical.

The numbers are deliberately open to revision. They describe a particular source’s argument, never an author’s worth or status.