Higher ed has spent four years managing AI through policies, restrictions, and isolated pilots. That approach bought time, but is time running out? Students are caught in a patchwork of incoherent expectations, and the labor market is shifting faster than the curriculum. In this episode featuring Andrea Goldsmith (President, Stony Brook University), Klara Jelinkova (VP and CIO, Harvard University), and Sandra Loughlin (Chief Learning Scientist, EPAM Systems), Jeff and Michael dig into what colleges can do to move from fragmented experimentation to a coherent, campus-wide AI strategy that preserves the right level of friction for students. This episode is made with support from Google for Education.

0:00 - Intro
4:33 - Should Colleges Forge More Coherent AI Policies?
9:29 - What Are the Cost and Benefits of the Patchwork Approach to AI?
12:06 - A Case for a Coherent AI Strategy at Colleges
15:33 - A Case Against Standardization in AI
18:08 - How Can College Leaders Measure AI Progress?
20:46 - The Importance of Stopping Some AI Pilots
20:24 - How to Make Decisions When AI Changes So Rapidly
23:59 - Sponsor Break
24:29 - Should Colleges Build, Buy, or Partner on AI
27:54 - Should Undergrads Learn AI From Day 1?
31:41 - What Research Shows About AI and Learning
34:12 - Convincing Students to Build Human Skills
38:49 - Do Selective Colleges Need to Change?
41:24 - How Can Colleges Show They Teach Durable Skills?
43:50 - Is Higher Ed Ready to Fully Assess Learning?
46:26 - How Will Colleges Deal With the Costs of AI?
48:26 - AI Could Help Some Colleges Leapfrog Others
50:50 - Colleges That Get AI Right Will …
52:15 - Closing Thoughts on AI at Colleges

“Why College Could Matter More than Ever in the AI Era,” by Michael Horn.