Professors Fight for Thinking Without AI

Professors Fight for Thinking Without AI

Generative artificial intelligence burst into universities not as just another digital tool but as a force that changes the very logic of the learning process. It used to be a debate about where to draw the line between using a calculator and solving a problem yourself. Now the question is harsher: what is left of education if a machine can write an essay in seconds, assemble arguments, summarize a book and even imitate a student's "personal style"?

That is why more and more instructors, especially in the humanities, no longer talk only about cheating. What worries them is a more fundamental problem: the risk of losing the habit of slow thinking, of the inner work of memory, of interpretation as a personal effort rather than a service on demand.

Against this backdrop, the experience of Stanford University professor Lee Pao, who is trying to bring students back into offline learning spaces, is telling. She proposes that students memorize poems, perform at public readings and look at works of art in person rather than on a screen. At first glance such practices can seem archaic, almost demonstratively out of step with the times.

In reality, they contain an important pedagogical answer to the age of AI. Pao starts from the view that protecting assignments from neural networks is almost pointless: "AI-proof" formats do not exist. So the main task is not total control but showing students the value of an experience that cannot be fully delegated to a machine, because it involves bodily presence, attention, nervousness, memory and personal interpretation.

This shift matters especially for the humanities, where the outcome of learning is not reducible to a set of correct answers. Literature, philosophy, art history and cultural studies require not just reproducing information but inner processing of a text or an image. Reciting a poem by heart is not a decorative practice from the past but a way to literally "build" language into your own memory and rhythm of thought.

A public reading is not only a check of preparation but also an encounter with an audience, in which words acquire intonation, pause, vulnerability. When a student looks at a painting in a museum rather than a digital reproduction, they confront scale, texture, space and the time of their own perception. All of this is hard to speed up, automate or outsource to an algorithm.

That is exactly why such practices are becoming not a conservative whim but a form of intellectual resistance.

The problem, however, is wider than the lecture hall. If students get used to turning to AI not as an auxiliary tool but as a permanent stand-in for mental effort, that changes the very culture of knowledge. There is a temptation to treat understanding as instantly generated text rather than a process of doubt, error, rereading and the slow clarification of thought.

In the short term this raises productivity: work gets done faster, wording becomes smooth, arguments become orderly. In the long term, though, there is a danger of intellectual atrophy. A person who trains memory, attention and the ability to connect ideas independently less and less loses not only academic skills but also civic competence: the ability to read critically, to tell nuances apart, not to give in to ready-made forms of persuasiveness.

That is why instructors' current reaction is not nostalgia for the pre-digital era but an attempt to redefine what exactly the university should protect. Obviously, a total ban on AI is hardly realistic: the technology is already embedded in everyday life, and students will use it regardless of formal restrictions. But that is precisely why the fight is shifting from the level of prohibition to the level of pedagogical design.

A good course must now not only deliver content but also create forms of experience in which independent thinking feels like a value rather than a waste of time. That means more oral discussion, more assignments built on observation and presence, more work in which the process matters, not just the final text.

In this sense Lee Pao's words sound symptomatic of an entire era. Behind the irritation with ChatGPT is not simply an instructor's fatigue with a technological fad but a fear of a society that is gradually unlearning how to think without an intermediary. Universities have ended up on the front line of this change because it is there that it is most visible how easily an intellectual path can be replaced by a plausible imitation of it.

The answer many humanities scholars offer is not to flee from technology but to return to the forms of learning in which thought passes through voice, body, memory and personal risk. It is quite possible that the future of education will be determined not by how skillfully it integrates AI but by whether it can preserve a space where people still learn to think for themselves.