AI is lowering the barriers to mathematical discovery.
One prominent math professor says that means hiring practices in academia need to get a whole lot more personal, and mathematicians need to get a whole lot more eloquent at communicating their ideas.
“I am looking for a narrative of where you want mathematics to go, the technical ability to explain why this may be possible,” Frank Calegari, a math phenom at the University of Chicago, wrote in a recent essay about what he’s looking for in a researcher.
At issue for Calegari is the distinct possibility that low-level researcher positions across academia will be filled by students who only got there by churning out AI-generated proofs.
A 30-minute discussion, though, would differentiate those slop-producers from promising candidates with a clear vision and a talent for communication.
“The hiring process is going to have to be much more about personal interactions than a paper file,” Calegari said in his essay, which was posted on Terence Tao’s blog.
Calegari slammed what he described as “lazy committees” that hired students based on a single paper or academic publication, which could now be sired by AI.
“Once we take this approach, we then have the responsibility to train our own graduate students to be better able to communicate mathematics, something that we should take much more seriously,” he said.
Last month, Cornell professor Steven Strogatz remarked that mathematicians with “rizz,” a slang term for charisma, had newfound stock because they could explain AI-generated results and turn them into new questions.
The brusque push by AI companies into mathematics has caused consternation and head-scratching among many a math geek, as the field ponders how to stay relevant while OpenAI floods the field with hundreds of proposed solutions to the world’s most complex problems.
Some professors have sworn off AI altogether. Most, however, are trying to find ways to incorporate the technology into their work.
Students across the country are also struggling to adapt, demanding that their professors publish clear guidance on how to use AI, if at all.
“We are lacking high-level leadership from across the academic community,” one student wrote in a recent MIT survey.
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