TL;DR

Fei-Fei Li says the worst outcome of AI in schools is not cheating but students losing agency and motivation. Warns equally against banning the tools. Says AI works best once a student is already engaged and stuck. Spoke on the Huberman Lab podcast, released Monday.

Fei-Fei Li thinks schools are worrying about the wrong thing. The danger of AI in classrooms is not that students will use it to cheat, she argues, but that it will strip away their reason to learn at all. She made the case on the science podcast Huberman Lab, in an episode released on Monday.

“The absolute bad outcome is that our young generation, their agency and human-level motivation of learning and living is taken away by tools,” said Li, the Stanford computer science professor widely known as the godmother of AI. “It should not be taken away by humans nor should it be taken away by machines.”

Used badly, she said, the tools could leave a generation that has not “properly developed the brain.” She is just as wary of the opposite reaction. “Both things worry me,” she said. “Either denying the tool or taking away agency and motivation.”

The evidence underneath the debate is still forming. A report from Oxford University Press last year found students gaining speed while losing depth of thinking. MIT researcher Nataliya Kosmyna separately found that people given generative AI for essay writing performed worse over time than those who used Google or no aid at all.

That second finding is contested. In December, four researchers published a formal comment on Kosmyna’s study, questioning its sample size, its EEG analysis, its reporting consistency and its transparency. They praised the underlying dataset but argued the results could be read more conservatively.

Vivienne Ming, chief scientist at the Possibility Institute, told Business Insider earlier this year that most AI users she studied were reaching for it to think less. It is the same pattern Wharton researchers have labelled cognitive surrender, and it turns up in workplaces too, where research suggests juniors never learn to debug.

Li’s alternative sits between banning the tools and handing them over. She recalled struggling with organic chemistry as a premed student, when teaching assistant hours were limited and professors had only so much time for questions. With a chatbot, she said, she would have asked far more.

“I know where I’m stuck,” Li said. “I have the motivation to learn. I just need guidance.”

That distinction should shape how schools approach the technology, she argued, treating it as a way to go deeper rather than a cheating risk to police. “Let’s find a way to keep our children and students’ motivation and agency,” she said. Done well, she added, it could make future students “way smarter than us because they are superpowered.“