It used to mean things like false positives in computer vision, where it is sort of appropriate: the AI is seeing something that's not there.

Then the machine translation people started misusing the term when their software mistranslated by adding something that was not present in the original text. They may have been already trying to be misleading with this term, because "hallucination" implies that the error happens when parsing the input text - which distracts from a very real concern about the possibility that what was added was being plagiarized from the training dataset (which carries risk of IP contamination).

Now, what's happening is that language models are very often a very wrong tool for the job. When you want to cite a court case as a precedent, you want a court case that actually existed - not a sample from the underlying probability distribution of possible court cases! LLM peddlers don't want to ever admit that an LLM is the wrong tool for that job, so instead they pretend that it is the right tool that, alas, sometimes "hallucinates".

oh definitely, it's fucking terrible question-begging. I'd like to know when it traces back to, and how good faith it was or wasn't

Of course is the term stupid. Neither is an LLM an AI, nor is any AI in the current state intelligent. In the end it all boils down to being answer machines. Complex ones, but still far away from anything even remotely being am AI.

LLMs bullshit all the time

Bullshitting to me is giving intentionally wrong statements. LLMs do not generate intentionally wrong statements. Saying they do, means that you imply intelligence.

LLMs know nothing nor are they intelligent. They also are not right or wrong, they generate output based on statistics.

"Hallucination" as a term for "AIs" making things up is used since the early 2000s (even if it's meaning has changed since then).