AI Is Killing the Universities — Good. Let Them Die the Death They’ve Earned! By Professor X

According to the latest panic piece doing the rounds, AI, artificial intelligence, is about to destroy universities. Students are using chatbots to write essays, complete with all the hallucinations AI generate. Employers are cutting internships. Degrees are losing signalling power. Professors are staring into the abyss and seeing GPT-shaped reflections. The tone is tragic: civilisation's great knowledge institutions are under existential threat. Ivory tower panic!

Allow me to respond in the traditional academic manner: citation needed — that this is a bad thing: please explain!

The real story is not that AI is killing universities. The real story is that universities killed themselves decades ago, and AI has merely arrived to kick the corpse and expose the smell. This is less the fall of Athens and more the collapse of Blockbuster — a once-useful institution that replaced its core purpose with revenue extraction and branding exercises, then acted shocked when technology noticed. And then things moved on.

The Futurism article (link below), frames the crisis in employment terms. Students are struggling to find internships because companies are using AI instead. Employers increasingly care less about degrees and more about skills. The old bargain — "pay us tens of thousands, endure four years of institutional nonsense, and we'll credential you into the middle class" — is collapsing. And academics are aghast. How will students learn? How will they think critically? How will civilisation survive without mandatory essays on Foucault and compulsory PowerPoint slides on stakeholder engagement?

To which one must reply: where, exactly, has civilisation been learning to think critically for the past thirty years?

Modern universities no longer exist primarily to pursue truth. They exist to pursue revenue, compliance metrics, international Asian student markets/the Great White Replacement, branding partnerships, bureaucratic growth, and reputational signalling, within closed managerial ecosystems. The pursuit of truth survives only in pockets — usually tolerated as a legacy function, like decorative gargoyles in a shopping mall.

In Australia, this transformation has been especially clean and brutal. Universities restructured themselves into Asian immigration brokers with lecture theatres attached. Entire faculties were redesigned around overseas fee pipelines. Academic standards quietly became elastic. Dissenting staff learned that challenging ideological orthodoxies or managerial directives was an excellent way to acquire "performance issues." Students learned that grievance systems were more effective than argument, and that intellectual discomfort counted as trauma. Meanwhile, administrators learned the sacred truth of late capitalism: you don't need excellence if you have throughput. And the ethno-racial profile changed, so that many universities are now majority non-white. And it is early days yet.

This is not education. This is credential manufacturing — with pastoral care overlays and sustainability branding.

Into this hollowed-out structure wanders AI, politely demonstrating that if the main output of universities is boilerplate essays, PowerPoint summaries, and generic assessments graded by exhausted casual staff using rubrics no one believes in, then machines can obviously do this faster, cheaper, and without demanding wellbeing days. AI did not attack education. It simply exposed how little education was left.

The panic about AI writing student essays is revealing. If a chatbot can produce indistinguishable work from your average undergraduate submission, the problem is not that the machine is too smart. The problem is that the assessment is too stupid. But universities cannot say this, because the entire mass-education model depends on scalable, standardised, low-friction assessment. Genuine intellectual difficulty does not scale. Truth-seeking does not scale. Thinking does not scale. Credential production does. AI just dumbs down what was already in intellectual free fall.

So instead, universities panic and announce "AI policies," convene taskforces, hold workshops on "ethical use," and quietly accept that nothing structural will change — because nothing structural can change without threatening the business model. The crisis is therefore framed as technological disruption, rather than institutional bankruptcy. It's not that universities stopped educating; it's that the LLMs are cheating. Always blame the thermometer.

But the Futurism article's deeper implication is more damning than its tone suggests. Employers no longer care about degrees because degrees no longer signal competence. They signal endurance. They signal compliance. They signal the ability to sit through meetings, write polite nonsense, and not upset administrators. That used to be valuable in corporate bureaucracies. Now AI does that too — faster, cheaper, and without HR complications.

Which leaves universities with a problem: what exactly are they for?

They used to be places where truth mattered more than comfort, where argument mattered more than inclusion slogans, where error was tolerated in pursuit of insight, and where students were trained to confront difficult ideas rather than curate emotional safety. Now they are institutions where "harm" is defined as disagreement, "rigour" means procedural compliance, and "excellence" means hitting recruitment targets while issuing statements about belonging.

If universities had remained truth-seeking institutions, AI would be a tool, not a threat. But since they became credential factories and ideological training camps, AI becomes an existential competitor — because factories are replaceable.

There is also a delicious irony here. For years, academics insisted that education was about "process, not product," about "thinking, not outcomes," about "learning journeys, not skills." Now that employers are bypassing the process and hiring based on demonstrable ability, universities are furious. Suddenly outcomes matter. Suddenly skills matter. Suddenly the market is unfair. One is tempted to say: welcome to the epistemic free market you've been imposing on students for decades.

The correct response to AI's disruption of universities is therefore not panic, but triage. Some parts deserve to survive. Research institutions pursuing real discovery. Scholars doing serious work. Small, demanding programs where intellectual honesty still exists. These should be protected and strengthened. But the mass-degree industry — the bloated managerial superstructure feeding off student debt, immigration arbitrage, and compliance bureaucracy — deserves exactly what technological disruption brings to all hollowed-out systems: extinction.

Let them die the deaths they've earned.

Not because knowledge is obsolete — but because credentialism without truth is worse than useless. It actively corrodes public trust in expertise, debases intellectual culture, and trains generations to confuse conformity with intelligence. That rot did not begin with AI. It began when universities decided that discomfort was oppression, argument was violence, and truth was negotiable.

AI is not killing education. It is killing fake education. And that is a public service.

The genuinely tragic thing is not that universities may collapse. It is that they collapsed internally long before anyone noticed — and now want sympathy for being technologically disrupted after spending decades disrupting their own intellectual foundations.

If universities want to survive, the solution is not plagiarism detectors and AI guidelines. It is to return to the one thing machines cannot replace: genuine inquiry, disciplined reasoning, intellectual courage, and the willingness to offend fashionable nonsense in pursuit of truth. Looking at my own corrupt university, I say: good luck seeing that!