Long read: The University As We Know It Is Finished

We have been writing about the failure of the Indian university education system where graduates are increasingly struggling to find employment compared to their non-graduate counter parts. Turns out, India isn’t unique. Globally, in particular the much-laureled American university system is under threat. And AI is just a catalyst that accelerates its fall. This is a brilliant essay by Nils Gilman, a former Associate Chancellor of UC Berkeley about what has been ailing the system even prior to the advent of AI and how to fix it. He begins by referring to the view of Clark Kerr, the former president of University of California on the purpose of the university system during the 1960s.

“In Kerr’s account, the modern university was no longer to be understood as a community of scholars united by a shared ideal of learning, but rather as a sprawling institutional conglomerate serving at once as a research engine, a job-training facility, a credentialing mechanism, a coming-of-age experience, and an incubator of the national technical elite.

…It was the nexus at which basic scientific knowledge was produced, technical and professional talent was credentialed, democratic citizenship was cultivated, and the national project of technological supremacy was advanced.”

The author reckons that model is no longer relevant today: “It is time to acknowledge that Kerr’s model of higher education is finished: long on its last legs, the arrival of AI announces its death-knell. What comes next is disaggregation: the multiversity as we know it being disassembled into its component parts. This need not, however, be a catastrophe for higher education. Actually, in many ways, it represents an opportunity to return to roots, in a classical model of education and in attentive pedagogical instruction.”

What went wrong: “…slow-motion privatization of university finances, producing a slow-motion tuition hyperinflation that has burdened a generation of students with debt while hollowing out the public mission of the university. The shift from grants to loans, from tenured faculty to mass adjunctification, and from a broad education in the liberal arts to vocational credentialism all occurred under the banner of making universities more “responsive to market demands.” In practice, this has meant transferring cost from the public to the individual “student consumer,” while defunding the parts of the institution that didn’t produce monetizable outputs. The net result has been the ever-upward-spiraling costs of undergraduate education, without a corresponding increase in the value of educational training or credentialling, and a loss of political support for the mission of universities.”

Throw AI into this mix and it all unravels quickly: “When a student can produce a plausible term paper in twenty minutes using Claude Opus or Google Gemini, what is the point of assigning term papers? When an AI tutor can explain any concept at any level of sophistication with infinite patience, what is the value of a lecturer reading from notes? When AI can ace most standardized professional examinations, what is a credential certifying?”

Much like the office system (compared to solo or remote work enabled by technology) highlighted by a piece we featured last week, there is a larger purpose of the university system which remains intact: “…there is evidence that learning works differently when embedded in community, that chance hallway encounters with faculty members, late-night bull sessions in the dormitory common room, and heated dining hall debates are often the most generative moments of learning. Students’ own accounts of what matters most in college consistently center on relationships, belonging, and dialogue. The argument for residential education, for the ancient model of the Platonic Academy as gymnasium and garden as much as classroom, is stronger now than it has been in decades.

….This is continuous with a long-standing function of universities as sites for passage from childhood to adulthood, for coming to a new understanding of oneself. In the 1960s more than four fifths of college freshmen reported that a major goal of college was to help themselves “develop a meaningful philosophy of life,” a number which collapsed by half in the 1970s and 1980s. A reemphasis on the co-curricular could help revivify this ideal, which would in turn help prepare students for the AI-forward world they are entering. As Anthropic cofounder Jack Clark recently argued, the people who will most benefit from AI are those who have first built deep, idiosyncratic human capacities through “repetitive practice and creation.” The machines will work best when helping you to amplify what you’ve already made of yourself.”

For AI cannot do everything: “AI cannot build the trust on which institutional cooperation depends, because trust is not a conclusion reached by processing information about another agent but instead is a relationship constituted over time between persons who have staked something on each other, and who can be betrayed. AI cannot give a person good taste or style, because taste and style are about personal distinctiveness within a community which shares an aesthetic. AI cannot constitute goals, because that act requires a valuing subject.”

So, the core of the curriculum in the new paradigm remains unchanged: “…if the goal of a college curriculum is (as it should be) to inculcate oral reasoning and persuasion, ethical analysis and moral judgment, historical and comparative thinking, and the cultivation of taste and discrimination, then we are precisely in the domain of the classical curriculum of the liberal arts. Skills such as goal constitution, situated judgment, and value alignment are exactly the capacities that a serious engagement with history, philosophy, literature, and political theory develops. History trains temporal imagination and frame revision; philosophy trains epistemic precision and the discipline of distinguishing solid argument from vapid sophistry; literature sharpens an appreciation for style and a feeling for hidden meaning; political theory trains the recognition of suppressed goal contestation and the conditions for legitimate alignment. Together they enable students to imagine lives unlike their own, a hugely valuable experience in a world changing as fast as ours.”

But the mode of delivery and the skills of the faculty need to adapt: “How to convey the content of these disciplines to students is going to have to change dramatically from the homogenous one-to-many mass-delivery model of the postwar multiversity, but the content is perfectly classical. The university’s present crisis of purpose is, in this light, at least in part a crisis of having abandoned its own best tradition in pursuit of vocational or technical training that AI is now rendering obsolete.

…The skills required of faculty will also need to change substantially. Under the old model, a brilliant researcher delivered expected value simply by speaking one-to-many; the new model requires someone with the pedagogic sensitivity to calibrate each student’s specific confusions and capacities—qualities that research prowess neither produces nor rewards. Elite universities in particular have built their faculties almost entirely around research achievement, with teaching treated as a secondary obligation.”

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