First, some have criticized experiments (by us and others) showing AI misalignment as artificial, or creating unrealistic environments that essentially “entrap” the model by giving it training or situations that logically imply bad behavior and then being surprised when bad behavior occurs. This critique misses the point, because our concern is that such “entrapment” may also exist in the natural training environment, and we may realize it is “obvious” or “logical” only in retrospect.
I know the linked posts were focused on agentic misalignment, but in context I read this to be pointing at dismissal of the broader set of papers like Alignment Faking etc. (ex)
I know the linked posts were focused on agentic misalignment, but in context I read this to be pointing at dismissal of the broader set of papers like Alignment Faking etc. (ex)