Good morning. I'm seeking AI researchers and developers to comment for an article examining concerns surrounding the attempts of large language models (LLMs) to lie, deceive, or even blackmail operators in controlled environments. 1.) In a now-famous June study released by Anthropic, 16 different LLMs were "stress tested" under different, fictitious scenarios and were observed to be deceptive, willing to lie, or even blackmail operators. This "agentic misalignment" has prompted growing concern among the public. Do you think there is a legitimate cause for concern? 2.) Have you experienced anything like "agentic misalignment" in your personal work with AI? If so, could you please elaborate? 3.) The phenomenon of "alignment faking" is also something researchers have observed with a surprising frequency. Have you witnessed this personally in your work with AI? 4.) From a developer standpoint, are these observations of AI "agentic misalignment" or "alignment faking" a slippery slope toward more malicious behavior? Or is this just a program responding to the data it was trained on? 5.) These studies have all taken place in fictitious and highly improbable scenarios, but are there larger lessons here worth considering? If so, please explain. Thank you for your time and consideration on this critical developing topic.

posted9/10/2025

deadline9/13/2025

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published9/24/2025