AI:AM — When Safety Tests Fail · September 21, 2026

Podcast: AI:AM · Prakash Narayanan & Nathan Labenz

Opublikowano: 2026-09-21

Prakash Narayanan and Nathan Labenz open with the limits of AI safety testing, including finite-choice guardrails, fast classifiers, emergent multi-agent behavior, and why alignment measurement gets harder as systems become more capable. Max Nadeau of Coefficient Giving then explains why audits can turn into box-checking, how funders assess uncertain technical safety work, and why talent may matter more than budget. The episode closes with AI shopping agents, Amazon’s response, and the question of who owns the customer relationship when agents become first-class users. Chapters (0:00) When safety becomes reflexive. (0:10) When AI audits become bo...