Humans "hallucinate" in the AI way constantly, which is why I don't see them as a barrier to LLMs replacing humans in many contexts. It really isn't unusual for a human to make stuff up or be unaware of stuff.
This claim is ambiguous. The use of the word "Humans" here obscures rather than clarifies the issue. Individual humans typically do not "hallucinate" constantly, especially not on the job. Any individual human who is as bad at their job as an LLM should indeed be replaced, by a more competent individual human, not by an equally incompetent LLM. This was true long before LLMs were invented.
In the movie "Bill and Ted's Excellent Adventure," the titular characters attempt to write a history report by asking questions of random strangers in a convenience store parking lot. This of course is ridiculous and more a reflection of the extreme laziness of Bill and Ted than anything else. Today, the lazy Bill and Ted would ask ChatGPT instead. It's equally ridiculous to defend the wild inaccuracy and hallucinations of LLMs by comparing them to average humans. It's not the job of humans to answer random questions on any subject.
Human subject matter experts are not perfect, but they’re much better than average and don’t hallucinate on their subjects. They also have accountability and paper trails, can be individually discounted for gross misconduct, unlike LLMs.
But yes, as an edge case handler humans still have an edge.
It's not obvious to me that they're better at admitting their mistakes. Part of being good at admitting mistakes is recognizing when you haven't made one. That humans tend to lean too far in that direction shouldn't suggest that the right amount of that behavior is... less than zero.
they feed an internet data into that shit, they basically "told" LLM to behave because surprise surprise, human sometimes can be more nasty
(Yes, not everyone, but we do have some mechanisms to judge or encourage)
This is more and more clearly false. Humans get things wrong certainly, but the manner in which they get things wrong is just not comparable to how the LLMs get things wrong, beyond the most superficial comparison.