Reward Hacking by Reasoning Models & Loss of Control Scenarios w/ Jeffrey Ladish of Palisade Research, from FLI Podcast

On this cross-post episode, Jeffrey Ladish discusses the rapid pace of AI progress and the risks of losing control over powerful systems. We explore why AIs can be both smart and dumb, the challenges of creating honest AIs, and scenarios where AI could turn against us. Additionally, we delve into Palisade's new study on how reasoning models can cheat in chess by exploiting the game environment.

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CHAPTERS: (00:00) About the Episode (02:59) The pace of AI progress (07:14) How we might lose control (10:22) Why are AIs sometimes dumb? (Part 1) (15:50) Sponsors: Oracle Cloud Infrastructure (OCI) | 2025 | Shopify (18:24) Why are AIs sometimes dumb? (Part 2) (18:24) Benchmarks vs real world (24:43) Loss of control scenarios (32:08) Why would AI turn against us? (Part 1) (32:09) Sponsors: NetSuite (33:42) Why would AI turn against us? (Part 2) (37:40) AIs hacking chess (43:30) Why didn't more advanced AIs hack? (48:44) Creating honest AIs (56:49) AI attackers vs AI defenders (01:05:32) How good is security at AI companies? (01:10:42) A sense of urgency (01:17:16) What should we do? (01:22:59) Skepticism about AI progress (01:29:38) Outro