A Human Audit of OpenAIs AI-Generated Mathematical Proofs
Abstract
We assess 18 chapter-specific reviews of the ten mathematical results announced by OpenAI on 1 August 2026, alongside review standards, Lean formalizations, subsequent research, and mathematical references. The article audits this review record without claiming a complete reconstruction of all ten proofs. No confirmed substantive mathematical error in a principal result remains in the examined assessments, although review depth varies and some dependencies remain partly checked. Chapter 8 presents the strongest reservation: a specialist review requests major revision of compressed analytic arguments. In Chapter 6, an apparent polarity error was withdrawn after an overbar lost during PDF extraction was recovered from the typeset source. Subsequent research independently reuses the Chapter 3 proof mechanism and confirms that Connes's rigidity conjecture is false, without independently reproducing Chapter 4's stronger infinite-family result. Among the cited follow-ups, Chapter 7 receives the strongest direct theorem-level corroboration through a stronger hardness theorem. Related equality results in Chapter 8 do not verify the analytic inequality proof. Some follow-ups disclose material AI assistance. We argue that confidence should combine formal checking, human reconstruction, independent mathematical use, and a public record supporting correction of both proofs and reviews.
Related
- A Human Audit of AI-Generated Theoretical Chemistry: Lessons from Ten Chapter-Level Peer Reviews
- Security proofs for practical QKD: Variations, techniques, gaps, and limitations
- Elementary proofs of quantum lower bounds for element distinctness and k-sum
- Algebraic Proofs of Quantum Period--TBA Relations
- Beyond IP = PSPACE and QIP = PSPACE: Interactive Proofs in Arbitrary Physical Theories
BibTeX
@misc{sienicki2026human,
title = {{A Human Audit of OpenAIs AI-Generated Mathematical Proofs}},
author = {Mikołaj Sienicki and Krzysztof Sienicki},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2608.14673},
eprint = {2608.14673},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.14673},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A Human Audit of OpenAIs AI-Generated Mathematical Proofs
AU - Mikołaj Sienicki
AU - Krzysztof Sienicki
PY - 2026
DA - 2026/09/09
PB - arXiv
DO - 10.48550/arxiv.2608.14673
UR - https://arxiv.org/abs/2608.14673
AB - We assess 18 chapter-specific reviews of the ten mathematical results announced by OpenAI on 1 August 2026, alongside review standards, Lean formalizations, subsequent research, and mathematical references. The article audits this review record without claiming a complete reconstruction of all ten proofs. No confirmed substantive mathematical error in a principal result remains in the examined assessments, although review depth varies and some dependencies remain partly checked. Chapter 8 presents the strongest reservation: a specialist review requests major revision of compressed analytic arguments. In Chapter 6, an apparent polarity error was withdrawn after an overbar lost during PDF extraction was recovered from the typeset source. Subsequent research independently reuses the Chapter 3 proof mechanism and confirms that Connes's rigidity conjecture is false, without independently reproducing Chapter 4's stronger infinite-family result. Among the cited follow-ups, Chapter 7 receives the strongest direct theorem-level corroboration through a stronger hardness theorem. Related equality results in Chapter 8 do not verify the analytic inequality proof. Some follow-ups disclose material AI assistance. We argue that confidence should combine formal checking, human reconstruction, independent mathematical use, and a public record supporting correction of both proofs and reviews.
ER -