AI and the Future of Mathematics — Mathematics Münster, CRC 1442, TRR 326 and TRR 358

Martin Raum describes how AI entered his mathematical workflow, focusing on manuscript review and research infrastructure while retaining human mathematical judgment. Joint work with Olav Richter and Matt Ortiz provides a case study of human-guided, AI-generated research. The project uses ordinary subscription tools rather than specialized opaque models, offering a workflow adaptable to other mathematical projects. It also raises questions about standards for solid intermediate research and the possible future of research at the highest level.

Thomas Kahle reflects on how using AI changes mathematical researchers as well as their work. Drawing on his own experience as an early adopter, he examines why the trust between mathematicians does not automatically extend to technology companies. A second concern is the effect of outsourcing writing to AI: turning notes into polished drafts can be efficient, but may displace the slow, unfinished process through which core ideas develop. The talk considers the distinction between routine writing assistance and retaining human ownership of mathematical thought.

Ken Ono surveys how AI systems contribute to mathematical discovery, research-level reasoning and formal verification. Examples include AI-guided searches, progress on longstanding problems and formalization in Lean. The talk also examines reliability, attribution, unequal access, education and the future role of mathematicians. It argues for using AI to extend exploration while retaining mathematical judgment and strengthening trust through machine-checkable proofs.