A post-debate debrief from Stefan and Anand after a provocative campus resolution: “UMW should be an AI university.” Using three data sources—59 survey responses, transcript analysis, and five student reflections—this episode unpacks why the debate increased familiarity dramatically but moved the persuadable middle toward “no.” The core takeaway: the campus largely supports AI integration, but resists the identity label. Along the way, the hosts explore what debates reveal that workshops and keynotes often miss—and why debate may be one of the most effective forms of AI professional development in higher ed.You can find the UMW debate video here: https://youtu.be/dLCaRaunV7I?si=CUU-bjuXYc8byg2O Chapters0:04 — The stakes and the framing: urgency vs. institutional purpose; “shape the transformation or be shaped by it”0:45 — What this episode is: debriefing the Feb 4, 2026 UMW debate + what the data reveals1:44 — The roadmap & methodology: 59 surveys + transcript analysis + 5 student reflections (triangulation)2:58 — Why debates matter as pedagogy: learning over “who won”; debates as civic discourse and PD4:22 — Headline numbers: AI use predicts vote (r=.62); familiarity gains (large effect); event rating (4.44/5)5:16 — The vote puzzle: informed audience, but movement toward “no” (neutral shrinks; opposition grows)5:40 — The ‘branding problem’ emerges: audience independently echoes the same resistance to the label6:54 — Experience drives opinion: daily vs. never-users and what that predicts about institutional identity7:48 — Familiarity shifts: “0% not familiar” after the debate; why that matters even amid disagreement8:40 — Persuasion dynamics: neutral middle moves most (inverted-U pattern); “lower risk” wins9:24 — Why the negative frame won: “do everything without the rebrand” as a hard-to-beat offer10:24 — Student reflections: flourishing framing, Kodak analogy, preparedness signals, and deeper processing13:24 — Five propositions table: universal agreement on AI’s impact + AI literacy; resistance to the label14:24 — Comparing three debates: biggest familiarity gain here, but lowest “informed” rating—why?15:26 — Validation vs. information: confirming existing concerns can feel like “less learning”15:49 — Unaddressed concerns to debate next: environment, copyright, governance, cheating vs. curriculum17:04 — Why students want more debates: engagement, civil discourse, liberal arts identity in action18:14 — Six implications: lead with substance; define what “AI university” means; engage non-users; more debates19:49 — Closing synthesis: support for what universities do, resistance to what they call themselves