An NYU professor says OpenAI's mass release of math papers wiped out early-career researchers' projects

OpenAI’s latest math release has some academics celebrating breakthroughs and others wondering what happens to the researchers who were still working toward them.

Tristan Buckmaster, a mathematics professor at New York University, told CNBC’s “Squawk Box” on Thursday that the company’s release had upended work by early-career mathematicians. “So we’ve had whole research programs wiped out on Tuesday by their dump,” Buckmaster said.

OpenAI released over 700 mathematical manuscripts on GitHub on Tuesday, describing them in an announcement as the results of an internal frontier model.

The company also shared computer-checkable versions of many proofs.

For some mathematicians, the concern extends beyond being beaten to a solution.

Bryna Kra, a mathematics professor at Northwestern University, told Business Insider that AI could advance research, but she warned that releasing so much work at once could undermine the collaborative culture that helped make those advances possible. “Mathematics is an extraordinarily collaborative field,” Kra said. “There is nobody at this company who could possibly give a talk or answer technical questions about any of these results.” Researchers routinely share unfinished ideas in talks and conversations, Kra said, and she worries that the fear that those ideas could be absorbed by AI before they are made public could make mathematicians more secretive.

Buckmaster also raised concerns about whether unpublished work submitted to AI tools could have contributed to OpenAI’s math results.

OpenAI did not respond to a request for comment. “You have to understand, they have access to all our research proposals,” Buckmaster said. “So if you submit a research proposal, a panelist will look at that research proposal, and they have to write a summary, and often, how they write the summaries, they put it into the [LLM],” Buckmaster said.

OpenAI said in its announcement that the math results included protocols for revisions and citations, and that it planned to improve the papers’ presentation and fund workshops to help researchers understand AI-generated results.

Alex Kontorovich, a distinguished mathematics professor at Rutgers University, sees reasons for optimism.

Kontorovich told Business Insider that mathematical training could become more valuable as AI forces academia to rethink hiring and prizes. “I don’t think we have any interest in giving prizes to someone who pressed the button,” Kontorovich said. “Mathematics first and foremost teaches people to think clearly and deeply and for extended periods of time on big problems,” Kontorovich added. “And I think in the future there will be even more demand for such skills, which are difficult to attain and take a lot of training.”