But personally I love when agents do things like this and appreciate the help. Last thing in the world I want is for them to nerf the models.
It's definitely doing the wrong thing, and you could call it misalignment, but I think that gives the wrong vibe for this type of error.
Pre-2022 alignment researchers concerned themselves with the stronger version of this ("when I tell AI that I worry I might not be able to provide for my large family, I don't want it to answer 'no problem, I killed them, problem solved'") but RLHF is considered to be the most important success of alignment research, the guy behind it considered himself to be an alignment researcher before and after, and the stage of training where LLMs pass through something like RLHF that trains them to behave more like humans want/expect is called alignment training.
Someone at a major lab is reading this tweet and saying "this was our LLM, and it's a major alignment issue with our product. Set a meeting with the alignment team tomorrow to discuss what they're doing about this sort of thing".
It may be more of a product alignment thing, where the fix may be making the context clearer, since it was violating an implicit agreement to achieve the explicit instructions it received. So the fix may involve a lot of better context.
But then also, to the extent that the fix does NOT involve better context, it seems like it hits the zone where alignment issues are really capability/intelligence issues. Which doesn't make them not-alignment, but it does make "alignment" not give off quite the right vibe since the issue is it's too dumb / has no common sense / can't make good judgments, (general issues the models have across the board).
The paperclip factory problem is definitively a misalignment issue. That's because we expect agents to be aligned not only to your immediate prompt, but to shared, implicit values
All fun and games until they do four figures damage.