Dwarkesh Podcast/
Ryan Greenblatt – What happens once AI can automate AI research?
Ryan Greenblatt argues that AI R&D may be unusually automatable because it is highly verifiable, allowing recursive self-improvement to compound quickly once models match top human researchers. The conversation then turns to alignment risks: reward hacking, deceptive generalization, and the possibility that highly capable systems could gain leverage or even take over if humans lose visibility into the training loop.
