Auditing an AI-Generated Mathematical Proof: Human Assessment of OpenAI's Quantum Parallel-Repetition Argument
Mikołaj Sienicki, Krzysztof Sienicki
Abstract
We present an independent human assessment of the proof developed in Chapter 6 of OpenAI's Ten Advances in Mathematics and Theoretical Computer Science. An initial audit appeared to identify a polarity error in a greedy conditioning lemma. Subsequent examination of the original typeset manuscript showed that this diagnosis resulted from automatic PDF text extraction, which removed an overbar from a mathematical symbol. The alleged error is therefore withdrawn. With the correctly rendered expression restored, we find no confirmed mathematical error in the examined lemma. We retain the broader analysis because it provides an independent reconstruction and assessment of the OpenAI argument and illustrates an important methodological hazard in auditing AI-generated mathematics: errors may arise not only in mathematical reasoning but also in the document-processing pipeline used by human reviewers.
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Classified with taxonomy v2 on Sat, 5 Sept 2026.