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
Maya Ackerman discusses human and machine creativity, exploring its definition, how AI alignment impacts it, and the role of hallucination. The conversation also covers strategies for human-AI collaboration.
Adam Gleave, CEO of FAR.AI, discusses post-AGI scenarios, risks of gradual disempowerment, defense-in-depth safety strategies, scalable oversight for AI deception, and the challenges of interpretability, as well as FAR.AI's integrated research and policy work.
Beatrice Erkers discusses the AI pathways project, focusing on approaches to maintain human oversight and control over AI, including tool AI and decentralized development, and examines trade-offs and strategies for safer AI futures.
