Podcast Recommendation: Journalist Garrison Lovely Discusses the 'Obsoleting Project' and Concrete Paths to Freezing Frontier AI Development
In this episode of The Cognitive Revolution, host Nathan Labenz interviews journalist Garrison Lovely about his new book Obsolete. Lovely reframes the pursuit of AGI as a distinct 'obsoleting project' aimed at replacing human labor, proposing concrete steps like unionizing AI researchers and freezing frontier development to mitigate risks.
The Cognitive Revolution podcast released an episode on September 29, 2026, featuring journalist Garrison Lovely, author of the new book Obsolete: The AI Industry's Trillion-Dollar Race to Replace Us — and How to Stop It. Hosted by Nathan Labenz, the conversation moves beyond general AI capabilities to explore the sociological and political dimensions of the current AGI race. Lovely, who has reported extensively from inside the AI industry, presents a reframed view of the technology's trajectory, distinguishing between beneficial narrow AI applications and what he terms the 'obsoleting project'—the deliberate effort to build a general substitute for human labor.
Lovely argues that the primary motivation for leading AI companies is not purely profit maximization but a mix of idealism, inevitability, and a desire to be 'in the room where it happens.' He contends that this mission-driven culture, now pressured by large investors like Thrive Capital, creates a dangerous dynamic where safety commitments are often revised when they conflict with commercial shipping schedules. To counter this, he proposes specific operational mechanisms for slowing down frontier development, including banning training runs larger than previous ones, prohibiting reinforcement learning from verifiable rewards, and preventing recursive self-improvement. He also advocates for embedding auditors within labs and establishing international verification treaties, drawing parallels to Cold War arms control agreements.
A key component of Lovely's argument focuses on the leverage held by AI researchers themselves. He posits that their bargaining power is near its peak because they are still essential to the development process, but will rapidly decline if recursive self-improvement succeeds. Consequently, he urges these workers to organize into unions to demand higher safety standards and pace the frontier collectively. For professionals interested in AI governance, labor economics, and the societal impact of automation, this episode offers a detailed look at the political strategies being proposed to manage the transition away from human-centric labor models.