The two minute mile problem (hollisrobbinsanecdotal.substack.com)

A year‑long warning in this essay frames a looming “two‑minute mile” problem: AI and personalized tutoring are accelerating student learning 2.6x–5x (examples: Alpha School, Benjamin Bloom’s tutoring results, and adaptive tools), so cohorts trained to learn much faster will hit a U.S. higher‑education system built around predictable, time‑based progression—the Carnegie Unit, semesters, credit hours, and financial aid. Crucially, 92% of high‑schoolers now use generative AI; most K‑12 accountability systems (ESSA) measure proficiency at fixed intervals, not continuous learning velocity. Some platforms (Khanmigo, NWEA) begin to approximate rate‑of‑change metrics, but no state currently tracks acceleration as a policy variable. The piece argues this is systemically significant: competency‑based mastery and AI‑enabled acceleration threaten faculty roles, accreditation rules, tuition models, aid eligibility, and social/ developmental assumptions of college life. Technical needs include continuous tracking of learning slopes, operationalizing competency credits versus seat time, and reconciling faculty time split between commodity content delivery and high‑value frontier mentorship (5:1 mentorship vs. 30:1 lectures). The author offers 25 leadership questions — about hiring, tenure, accreditation waivers, financial‑aid redesign, and residential models for younger accelerated entrants — urging coordinated institutional rethinking now before acceleration becomes an entrenched, disruptive norm.