US Professor Warns OpenAI’s 377 Math Findings Have ‘Destroyed Careers’ of Young Researchers
OpenAI released findings on 377 mathematical problems across five fields. An NYU professor warns of research harm and a conflict of interest tied to AI. Read the artcile to get complete details.
OpenAI has released findings on 377 mathematical problems covering algebra, number theory, theoretical computer science, mathematical logic and topology. The papers came out on Tuesday. The release followed OpenAI’s claim last month that it had solved a problem involving the Navier-Stokes equations. That problem is one of the Millennium Prize Problems and each accepted solution carries a $1 million prize. The sudden progress has left many mathematicians stunned and it has sharpened the debate over the place of AI in mathematics. One working researcher now warns that this race could damage young talent.
Tristan Buckmaster on AI in Mathematics and His Own Research
Tristan Buckmaster is a mathematics professor at New York University. He said solving the Navier-Stokes problem had never been his goal. He said he is super happy to have solved the Euler problem. He still uses AI tools made by Anthropic and he has access to OpenAI Codex. However he avoids entering ideas that he considers original into these systems. He spoke about the developments and about his own chances of winning the million-dollar prize.
Career Damage and Conflict of Interest Concerns
Buckmaster said the recent dump of papers on Tuesday destroyed the careers of early-career mathematicians. He said whole research programmes were wiped out by that dump. He explained that researchers who submit proposals often have their work reviewed by panel members and those members must prepare summaries of the submissions. He suggested those summaries may be prepared with large language models. That can expose original research ideas to AI systems. He said the developers have access to all research proposals. He added that the problem goes beyond the direct use of these models. He argued that AI developers could also learn about research programmes and the methods used to solve problems from the data used to train their systems. He said the same risk applies to scientists in other fields. He warned that this could create a significant conflict of interest.
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