Fools With Tools Are Still Fools
Schools risk being reduced to training camps for interface management, breeding generations of docile operators who are taught only to steer the algorithms of artificial intelligence.
Nice try, The Atlantic. Nicholas Thompson, CEO of that glossy oracle of elite conventional wisdom, has offered us yet another thin defense of AI in higher education, a paean to adaptation masquerading as foresight.
But what we need are apologias for real education, not feeble justifications for “prompt engineering” in Thompson’s theoretical global metaversity. His euphemisms abound—“cognitive offloading,” “new world,” “departments will change”—each a polite nod to the quiet dismemberment of intellectual rigor, a concession to the creeping abstraction of thought itself.
Students, once charged with the arduous task of wrestling the great ideas of history and literature into submission, are now encouraged to murmur sweet nothings to stochastic parrots in the hopes of eliciting something passable, something vaguely human-shaped. A Baudrillardian simulacrum where the real work, the real thinking, is spirited away behind the glistening veneer of artificial competence.
Thompson, the latest in a long line of techno-optimists squinting at the future like soothsayers parsing the entrails of a machine-learning model, assures us that we must remain “highly mindful of the risks of cognitive offloading.” Yet this is merely a genteel way of saying that the neural pathways once meticulously carved by effort and repetition are now atrophying, neglected, sacrificed at the altar of efficiency.
Schools risk being reduced to training camps for interface management, breeding generations of docile operators who, rather than grasping the mechanisms of reality, are taught only to steer the algorithms that describe it. And what of their professors? Their syllabi now read less like curricula and more like API documentation.
Mathematics, Thompson muses, will shift—some fields rising, others sinking, based on perceived utility, the whole discipline bending under the gravitational pull of the AI singularity. But what exactly does this mean? Will logic, long the sinew binding mathematical thought, be sidelined in favor of whatever heuristic tweaks best optimize performance on synthetic benchmarks? Is linear algebra still relevant if the models are too deep for us to comprehend?
And what of philosophy, history, rhetoric (the art of argumentation)—all that scaffolding upon which Western intellectual tradition has precariously balanced for centuries? The unseen hand of the market will decide, of course. In a world where capital favors the pliant over the profound, the answer is obvious.
And what of philosophy, history, rhetoric (the art of argumentation)—all that scaffolding upon which Western intellectual tradition has precariously balanced for centuries?
And then, according to Thompson, a brief glimmer of hope: China’s DeepSeek! The academic research groups, still scrappy, still scrapping, proving that meaningful contributions to AI can be made without the obscene financial endowments of Silicon Valley’s priesthood. Encouraging, Thompson assures us. But encouraging for whom, exactly? For the institutions trying desperately to justify their relevance in an age when learning is outsourced to large language models? Or for the administrators tallying cost-benefit analyses, determining just how many faculty members can be replaced by “highly mindful” AI tutors with just enough veneer of engagement to stave off the realization that the whole enterprise is little more than an animated FAQ page? And what, exactly, are these groups trying to “solve”? The puzzle of intelligence itself, or simply the question of how much human cognition can be displaced before anyone notices?
Education has never been about ease. It has been about struggle. Study is hard work. Learning is a task! This is not Luddism; this is a plea against the creeping erosion of hard work as a virtue. The assumption that students should learn to “use the tools” sounds innocent enough until you realize that, before long, the tools will be using them. Once, we studied to expand the mind. Now, we train to operate the machinery that renders our minds superfluous.
And so here we are. Universities rebranded as vocational schools for algorithmic wrangling. Critical thinking reduced to a glorified UX tutorial. A generation taught not to construct arguments but to reverse-engineer autocomplete suggestions. We were promised a renaissance of intelligence; instead, we got an uncanny valley of competence, a simulation of scholarship where knowledge is not acquired but prompted into existence, as fleeting as a server cache.
This is the “new world” Thompson and The Atlantic speaks of. It is not one of enlightenment, but of automation masquerading as wisdom. And if we are not careful, if we do not resist the urge to flatten the difficult, to make palatable the act of thought itself, then we will find ourselves adrift in a sea of polished responses, tailored insights, and algorithmically optimized balderdash, mistaking fluency for understanding, and losing, in the process, the very thing that made education worth pursuing in the first place.
Michael S. Rose, a leader in the classical education movement, is author of The Art of Being Human, Ugly As Sin and other books. His articles have appeared in dozens of publications including The Wall Street Journal, Epoch Times, New York Newsday, National Review, and The Dallas Morning News.