Roman Yampolskiy on Shoggoth, Scaling Laws, and Evidence for AI being Uncontrollable
Roman Yampolskiy joins the podcast again to discuss whether AI is like a Shoggoth, whether scaling laws will hold for more agent-like AIs, evidence that AI is uncontrollable, and whether designing human-like AI would be safer than the current development path.
Roman Yampolskiy joins the podcast again to discuss whether AI is like a Shoggoth, whether scaling laws will hold for more agent-like AIs, evidence that AI is uncontrollable, and whether designing human-like AI would be safer than the current development path. You can read more about Roman's work at http://cecs.louisville.edu/ry/ Timestamps: 00:00 Is AI like a Shoggoth? 09:50 Scaling laws 16:41 Are humans more general than AIs? 21:54 Are AI models explainable? 27:49 Using AI to explain AI 32:36 Evidence for AI being uncontrollable 40:29 AI verifiability 46:08 Will AI be aligned by default? 54:29 Creating human-like AI 1:03:41 Robotics and safety 1:09:01 Obstacles to AI in the economy 1:18:00 AI innovation with current models 1:23:55 AI accidents in the past and future
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.
