Increasingly, I'm able to empathise with people who use this psychobable language (hallucination, bullshit, etc.) to describe associative statistical models.

They just don't know how they work, really want to believe they work like a person, or have otherwise been duped by the boards of the ad-ai industrial complex whose spiel is whatever increases market valuation (google, fb, ms, openai, etc.).

I guess if you have absolutely no idea how these systems work there really isn't anything better than analogizing to people -- it is this 'failure of analogical reasoning' which ai/ad corps exploit in their desire to dupe ever more misinformed investors.

This realisation helps me, only, since I can now fathom better when i'm wasting my time talking to someone whose basis for understanding stats is human psychology -- the amount of discussion needed to undo that is possibly a lot.

Incidentally, all statistical systems of this kind (almost all ML, including NNs) work in the same way. They compress data into a smaller representation, and take a weighted average of pieces of that data relevant (by freq association) to the prediction.

There is no reasoning, no truth, no falsehood, no lies, no bullshit, no hallucination, no veridical perception, no interiority, no subjectivity, no capacity to represent the world.

There is something much more like a few pages of a book stuck together, with the second shinning through the first.