Something they don’t seem to mention in the article: Does greater model “enjoyment” of a task correspond to higher benchmark performance? E.g. if you steer it to enjoy solving difficult programming tasks, does it produce better solutions?

Pretty easy to test, I’d imagine, on a local LLM that exposes internals.

I’d suspect that the signals for enjoyment being injected in would lead towards not necessarily better but “different” solutions.

Right now I’m thinking of it in terms of increasing the chances that the LLM will decide to invest further effort in any given task.

Performance enhancement through emotional steering definitely seems in the cards, but it might show up mostly through reducing emotionally-induced error categories rather than generic “higher benchmark performance”.

If someone came along and pissed you off while you were working, you’d react differently than if someone came along and encouraged you while you were working, right?