Why the AI Race Undermines Safety (with Steven Adler)
Former OpenAI safety researcher Stephen Adler discusses governing increasingly capable AI, including competitive race dynamics, gaps in testing and alignment, chatbot mental-health impacts, economic effects on labor, and international rules and audits before training superintelligent models.
Stephen Adler is a former safety researcher at OpenAI. He joins the podcast to discuss how to govern increasingly capable AI systems. The conversation covers competitive races between AI companies, limits of current testing and alignment, mental health harms from chatbots, economic shifts from AI labor, and what international rules and audits might be needed before training superintelligent models.
Andrea Miotti, founder of Control AI, discusses the extreme risks from superintelligent AI and his case for a global ban on systems that could outsmart humans, touching on industry lobbying, regulation strategies, public awareness, and citizen actions.
Ryan Kidd of the MATS program joins The Cognitive Revolution to discuss AGI timelines, model deception risks, dual-use alignment, and frontier lab governance, and outlines MATS research tracks, talent needs, and advice for aspiring AI safety researchers.
Deric Cheng of the Windfall Trust discusses how AGI could transform the social contract, jobs, and inequality, exploring labor displacement, resilient work, new tax and welfare models, and long-term visions for decoupling economic security from employment.
