Tom Davidson joins the podcast to discuss how AI could quickly automate most cognitive tasks, including AI research, and why this would be risky. Timestamps: 00:00 The current pace of AI 03:58 Near-term risks from AI 09:34 Historical analogies to AI 13:58 AI benchmarks VS economic impact 18:30 AI takeoff speed and bottlenecks 31:09 Tom's model of AI takeoff speed 36:21 How AI could automate AI research 41:49 Bottlenecks to AI automating AI hardware 46:15 How much of AI research is automated now? 48:26 From 20% to 100% automation 53:24 AI takeoff in 3 years 1:09:15 Economic impacts of fast AI takeoff 1:12:51 Bottlenecks slowing AI takeoff 1:20:06 Does the market predict a fast AI takeoff? 1:25:39 "Hard to avoid AGI by 2060" 1:27:22 Risks from AI over the next 20 years 1:31:43 AI progress without more compute 1:44:01 What if AI models fail safety evaluations? 1:45:33 Cybersecurity at AI companies 1:47:33 Will AI turn out well for humanity? 1:50:15 AI and board games
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.
Researcher Oly Sourbut discusses how AI tools might strengthen human reasoning, from fact-checking and scenario planning to honest AI standards and better coordination, and explores how to keep humans central while building trustworthy, society-wide sensemaking.
Technical specialist Nora Ammann of the UK's ARIA discusses how to steer a slow AI takeoff toward resilient, cooperative futures, covering risks from rogue AI and competition to scalable oversight, formal guarantees, secure infrastructure, and AI-supported bargaining.
