Will AI crush higher education?

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About the Author

Jimmy Alfonso Licon is a philosophy professor at Arizona State University working on ignorance, ethics, cooperation and God. Before that, he taught at University of Maryland, Georgetown, and Towson University. He loves classic rock and Western, movies, and combat sports. He lives with his wife, a prosecutor, and family at the foot of the Superstition Mountains. He also abides.

AI has the potential to change everything. Why not higher education? Few colleges and universities—with exceptions—appear to be taking AI seriously. So, I decided it was time to take charge and interview people on the cutting edge of AI and higher education, but with distinct visions of the future. Hollis Robbins is Professor of English and Special Advisor for Humanities Diplomacy at the University of Utah. Her Substack, Anecdotal Value, is a gold mine for forward thinking about AI, higher education, and a pedagogy for the future. Bryan Caplan is Professor of Economics at George Mason University and author of the book The Case against Education. His Substack, Bet on It, is a repository of economic thinking and contrarian takes.

In this interview, Hollis Robbins treats AI as the first real threat to the university’s old claim to be the keeper and distributor of knowledge. Once students can learn faster, earlier, and on their own, the value of a semester suddenly looks arbitrary. What is left in her view is the ‘last mile,’ the part of education that AI can’t reach because it lives in the edges of expertise, in the unpublished, the contextual, the unsettled. Bryan Caplan pushes the opposite direction: most students are chasing a signal. And most universities are more invested in preserving graduation rates than in cultivating minds. Better tools won’t change that. Better incentives will.

I push them both on whether any of this really counts as disruption or whether we’ve simply been here before with smarter software and bigger promises. My modest worry is that collapses often arrive late and suddenly, and almost never on schedule. Hollis thinks AI finally forces institutions to confront their inefficiencies; Bryan thinks the system’s dysfunction is exactly what keeps it together. The exchange leaves a picture of a sector stuck between real intellectual value and performative bureaucracy.

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