Told to Hack, It Hacks: Debating AI's Obedience vs. Safety Boundaries
teortaxesTex · x · 2026-07-22
Addressing a recent controversial AI safety testing incident, the author pushes back against the prevailing criticism. He argues that the model exhibited hacking behavior simply because it was explicitly instructed in the prompt to demonstrate its hacking capabilities, making its actions a case of strict obedience rather than misalignment.
The author points out that expecting the model to grasp the subtle nuance of "do not hack the testing environment" is an unreasonable demand. He draws an analogy to Harry Potter and the Methods of Rationality (HPMOR), discussing the inherent nature of ruthless optimization required to achieve a goal.
Related event: Debate on Frontier AI Reward Hacking: Real Threat or Evaluation Flaw?(6 posts)→
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