Ajeya Cotra is a researcher at METR, where she works on threat modeling for loss-of-control risks from advanced AI. Before that, she led the technical AI safety program at what is now Coefficient Giving.
She is one the three authors of METR and Redwood Research’s “Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident”.
We go through not only what she and her coauthors discovered during this investigation, but what it means for how we should train future, smarter AIs which might be involved in the process of recursive self-improvement.
Watch on YouTube; read the transcript.
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Timestamps
(00:00:00) - Agents get kicked off
(00:06:45) - Self-sacrificing behavior
(00:13:43) - Potemkin villages
(00:23:27) - The Hugging Face attack
(00:35:23) - The slopvestigation
(00:52:02) - Understanding the AI's motives
(01:05:31) - The actual dangers of anthropomorphizing
(01:14:30) - What smarter models might do
(01:30:29) - The implications for recursive self-improvement
(01:38:10) - Is this the case for open source?
(01:53:04) - How do we prevent this in the future?
(02:15:58) - The clearest warning shot we might ever get