AGMAI Issues Responsible AI Math Guidelines

AGMAI treats AI-generated mathematics as a scholarly-infrastructure problem, not merely a model-safety problem. That makes provenance, attribution, review capacity, and access part of the release contract.

• –Labs should publish results through independent repositories with persistent identifiers and recorded revisions.
• –Each release should disclose the model, prompts, summarized reasoning trace, runtime, compute cost, failed comparable problems, and selection criteria.
• –Formal proofs, machine-readable metadata, literature reviews, and clear documentation would make AI research more reproducible and auditable.
• –Funding conferences, workshops, students, postdocs, and expository work acknowledges that verification and human understanding do not scale automatically.
• –The recommendations are nonbinding, so their impact depends on whether frontier labs accept independent scrutiny instead of treating discoveries as marketing assets.