College Students Losing Ability to Participate in Class Discussions Because They Offloaded Their Thinking to AI
“Everyone now kind of sounds the same.”
By Joe Wilkins
Published Apr 7, 2026 2:01 PM EDT
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It’s well known that students from grade schools to the big universities are increasingly outsourcing their thinking to large language models (LLMs). The consequences are already measurable: elementary students are losing cognitive skills, leading them to tank their exams.
Harder to quantify — but impossible to miss if you’ve spent any time in school lately — is the situation unfolding across classrooms, where students from all layers of society have become empty vessels that parrot the outputs of AI without critically engaging with the subject matter at hand.
One student at Yale University, identified as Amanda, told CNN that the monotonous prose of ChatGPT is even seeping into Ivy-league seminars. As the student and her classmates have observed, in-class conversations among peers are becoming increasingly flat and predictable, a symptom of students leaning on AI to think through discussions for them.
During one memorable awkward silence in class, Amanda told CNN she saw “someone typing ferociously on their laptop, asking [AI] the question my professor just asked about the reading.”
“Everyone now kind of sounds the same,” the Yale student said. “I feel like during my freshman year in college, I would sit in seminars where everyone had something different to contribute. Although people would piggyback off each other, they approached from different angles and offered different commentary.”
Amanda isn’t alone. One of her peers, Jessica, said that the start of every class kicks off an AI mad dash. “At the beginning of class, you could see every single person putting every single PDF [into AI],” the Yale senior told CNN.
Numerous studies have explored AI’s impact on human expression. One recent paper, published in the journal Trends in Cognitive Sciences, argued that LLMs dull the ways their users approach issues, deploy language, and reason through problems. When we use AI chatbots to think, the authors posit, we’re silently exchanging our own human thoughts for LLM output: a homogenized aggregate of our chosen model’s training data.
Morteza Dehghani, a professor of psychology and computer science at the University of Southern California and co-author of the paper told CNN that the implications of this are “quite scary.”
“If people lose [cognitive] diversity or get into intellectual laziness, of course, that is going to affect our society greatly,” Dehghani said.
Joe Wilkins
Correspondent
I’m a tech and labor correspondent for Futurism, where my beat includes the role of emerging technologies in governance, surveillance, and labor.
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