[ForTheKidz]

> There are various results that suggest that LLMs do internally have everything they'd need to know that they're hallucinating/wrong

We need better definitions of what sort of reasonable expectation people can have for detecting incoherency and self-contradiction when humans are horrible at seeing this, except in comparison to things that don't seem to produce meaningful language in the general case. We all have contradictory worldviews and are therefore capable of rationally finding ourselves with conclusions that are trivially and empirically incoherent. I think "hallucinations" (horribly, horribly named term) are just an intractable burden of applying finite, lossy filters to a virtually continuous and infinitely detailed reality—language itself is sort of an ad-hoc, buggy consensus algorithm that's been sufficient to reproduce.

But yea if you're looking for a coherent and satisfying answer on idk politics, values, basically anything that hinges on floating signifiers, you're going to have a bad time.

(Or perhaps you're just hallucinating understanding and agreement: there are many phrases in the english language that read differently based on expected context and tone. It wouldn't surprise me if some models tended towards production of ambiguous or tautological semantics pleasingly-hedged or "responsibly"-moderated, aka PR.)

Personally, I don't think it's a problem. If you are willing to believe what a chatbot says without verifying it there's little advice I could give you that can help. It's also good training to remind yourself that confidence is a poor signal for correctness.