AI Doesn't Mean the End of Mathematics—at Least Not Yet
Schneier and Rafi argue frontier AI models produce notable mathematical results but cannot yet build genuinely new conceptual frameworks.
Bruce Schneier and Kasra Rafi, writing in The Guardian, argue current AI models are not yet as capable as experienced academic mathematicians despite striking results. They cite OpenAI's disproof of the unit distance conjecture, Anthropic's published cryptanalysis results, and Claude's attempt at the Riemann hypothesis as achievements in counterexample search and recombining known techniques. They contend AI has not yet developed substantial new conceptual frameworks, though they expect that capability sooner rather than later.
- Cites OpenAI's unit distance conjecture disproof, Anthropic cryptanalysis results, and Claude's Riemann hypothesis attempt.
- Argues AI creativity is recombination and computational search, not new theory building.
- Authors expect AI models capable of novel mathematics sooner rather than later.
- AI models
- Claude
From the original article
3 min read at schneier.comThis essay was written with Kasra Rafi, and originally appeared in The Guardian. Earlier this month, about 40 top mathematicians gathered at OpenAI’s offices to discuss the future of their profession. The meeting was off-the-record, but if recent articles by mathematicians are any guide, it was mostly pretty glum.
By Bruce Schneier · schneier.com
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