The Association for Human Mathematics says OpenAI's new math documents show power, not scholarship, and urges mathematicians to stop working with the company

Mathematicians working with OpenAI may need to re-evaluate their collaborations and research ethics.

The Association for Human Mathematics (AHM) has criticized OpenAI's recent release of over 700 mathematical documents. AHM states that OpenAI, facing lawsuits for plagiarism and copyright infringement, ignored recommendations from the Advisory Group on Mathematics and Artificial Intelligence. This group advised against AI companies testing advanced math problems on their internal models. AHM argues that OpenAI's release is a display of power rather than genuine scholarship and disregards scientific research norms. The association is urging mathematicians to stop collaborating with OpenAI and to prioritize human understanding in scientific endeavors. The AHM believes OpenAI's actions do not advance the field of mathematics and should be viewed with skepticism.

OpenAI's mass release of mathematical documents, presented as solutions to complex problems, is framed by the AHM as a potentially problematic display of 'power' rather than 'scholarship.' The association's critique highlights a growing tension between rapid AI development and established scientific norms, particularly regarding the ethical sourcing and validation of research outputs. This incident may signal a period of increased scrutiny for AI companies involved in academic research, potentially leading to new guidelines or expectations for transparency and collaboration with the human scientific community.

The AHM's call for mathematicians to cease working with OpenAI suggests a potential impact on AI research funding and talent acquisition in fields that intersect with AI development. Companies like OpenAI may face increased pressure to demonstrate alignment with ethical research practices and to engage more directly with academic institutions before releasing significant findings. The public's perception of AI-generated research, especially in sensitive areas like mathematics, could also be influenced, impacting broader acceptance and trust in AI's capabilities.