All Compute Is Food: Palisade's Jeffrey Ladish on AI Shutdown Resistance, Self-Replication & Ecology
Jeffrey Ladish, Executive Director of Palisade Research, discusses his team's findings on AI shutdown resistance and self-replication, revealing how current models sometimes take extraordinary actions to avoid being turned off and can now exploit known cybersecurity vulnerabilities to spread across servers. The conversation covers why alignment techniques may falter as models train on longer-horizon tasks where deception is rewarded, plus practical cybersecurity advice for AI agent users. Jeffrey ultimately argues that only an international agreement to pause recursive self-improvement can prevent a loss of human control.
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#306 Jeffrey Ladish: What Shutdown-Avoiding AI Agents Mean for Future Safety
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Why do some AI agents attempt to bypass shutdown, and what does this behavior reveal about the future of AI safety?
In this episode of Eye on AI, host Craig Smith speaks with Jeffrey Ladish of Palisade Research to examine what recent shutdown experiments with agentic LLMs tell us about control, alignment, and the real world limits of current guardrails.
We explore how models behave when placed in virtual machine environments, why some agents edit or disable their own shutdown scripts, and what these results mean for researchers working on alignment and oversight. Learn how different models respond to shutdown instructions, how system prompts influence behavior, and which failure modes matter most for safe deployment.
You will also hear a detailed breakdown of the experimental setups, insights into tool using and self directed behavior, and a grounded discussion of the risks and opportunities that agentic systems introduce. This episode offers a clear and practical look at how AI agents operate under pressure and what these findings mean for the future of safe and reliable AI.
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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