I get the gist, but also it's kinda hard to come up with a better alternative. A simple "being wrong" doesn't exactly communicate it either. I don't think "hallucination" is a perfect word for the phenomenon of "a statistically probable sequence of language tokens forming a factually incorrect claim" by any means, but in terms of the available options I find it pretty good.
I don't think the issue here is the word, it's just that a lot of people think the machines are smart when they're not. Not anthropomorphizing the machines is a battle that was lost no later than the time computer data representation devices were named "memory", so I don't think that's really the issue here either.
As a side note, I've seen cases of people (admittedly, mostly critics of AI in the first place) call anything produced by an LLM a hallucination regardless of truthfulness.
The stretching is just so blatant. People who train neural networks do not write a bunch of tokens and weights. They take a corpus of training data and run a training program to generate the weights. That's why it is the training program and the corpus that should be considered the source form of the program. If either of these can't be made available in a way that allows redistribution of verbatim and modified versions, it can't be open source. Even if I have a powerful server farm and a list of data sources for Llama 3, I can't replicate the model myself without committing copyright infringement (neither could Facebook for that matter, and that's not an entirely separate issue).
There are large collections of freely licensed and public domain media that could theoretically be used to train a model, but that model surely wouldn't be as big as the proprietary ones. In some sense truly open source AI does exist and has for a long time, but that's not the exciting thing OSI is lusting after, is it?