Future-Proofing the University: What AI Is Really Testing in Higher Education

Much of the conversation about AI in higher education has settled into a defensive crouch. Students might cheat, so assignments get locked down; essays can be generated, so exams move back into rooms with pens and paper. On a recent episode of Modem Futura, Andrew Maynard and I spoke with Bryan Penprase, Vice President for Sponsored Research and External Academic Relations at Soka University of America and author of Future-Proofing the University: Innovations in Learning, Technology, and Finances in the Age of AI, who offered a more useful starting point. If AI can complete an assignment, he argues, the assignment probably wasn't asking for much learning, and if a robot can do a professor's job, that job may have drifted toward the mechanical.

AI as a stress test, not a verdict

Penprase's reading is that generative AI is exposing patterns higher education adopted in order to scale: large batches, content delivery, and assessment built around finished artifacts rather than the productive struggle that produces them. The kinds of learning that resist automation, such as projects that are personal, local, and embodied, are also the kinds that tend to serve students best. They don't scale easily, which puts the real question on the table: what should a university scale?

Rethinking scale and the faculty role

Drawing on visits to massively scaled institutions such as ASU, Western Governors University, and Southern New Hampshire University, and on a career spent largely at small liberal arts colleges, Penprase argues that these two worlds have a lot to learn from each other. Large institutions have figured out how to coach and support students at scale, while small ones understand what close relationships make possible. He points toward unbundling the university's many missions, toward experiments like MIT's New Educational Institution project, and toward faculty roles built around designing learning environments rather than delivering content. His physicist's metaphor is an inverse square law of learning: the greater the distance between learners and teachers, the weaker the pull.

Toward a more porous university

Penprase sees AI flattening the classroom, putting faculty and students in the position of learning together, and he sees the same opportunity for institutions and their communities. The Edinburgh Futures Institute, housed in a restored hospital building open to anyone who wants to walk in, is one example of what that can look like in physical space. An image he returns to often comes from a line usually attributed to the minister Ralph W. Sockman: the larger the island of knowledge, the longer the shoreline of wonder.

This raises important questions rather than clear answers. If AI is dissolving some of the scaffolding that held the modern university together, the work ahead is deciding which parts were ever really about learning, and what deserves to be rebuilt by hand.

Listen to the full conversation on Modem Futura, wherever you get your podcasts.

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