It turns out that picking up tone isn't a purely human thing and hasn't been for a while. Your Google search term is "sentiment analysis". It predates LLMs.

However, LLMs are fantastic at it. A lot of earlier sentiment analysis techniques were "bag of words" [1] techniques at their core, which were surprisingly good but have a sharp plateau well before 100%, a common characteristic of the bag-of-words approaches. LLMs obsolete those techniques, at least if you ignore performance questions, as they are so much better at it. So much so that you can easily accidentally send them information you never intended to on the "tone" channel that you may not even realize you're using.

[1]: https://en.wikipedia.org/wiki/Bag-of-words_model

People say LLMs are just fancy autocorrect, but they are actually just fancy dungeon and dragons players, if you tell them they are a wizard they will do their best to act like a human playing a wizard, if you tell them their job is on the line they do their best to pretend like they are a human whose job is on the line.

It's all just roleplay.

It's getting downvoted in part because it's pedantic and wrong.

It is totally true that they don't think like humans, but this is mostly irrelevant.

The token outputs will change as a result of this particular input, and will be closer to the tokens in training data where people felt hurried or rushed or like their job was on the line.

That doesn't mean the LLM feels at all, but it's definitely going to push the output towards output that came from/was trained on people who were in that state, because the input will push it much closer to that latent space as it starts predicting.

As such, what you are saying is one of those rejoinders that is basically pedantic and wrong.

It is true they do not think, act, or feel like humans. But that doesn't mean it won't output text that looks like hurried or scared humans. It definitely will, because, again, the training data these inputs will be closer to is the training data that came from scared or hurried humans, and thus the predictions will be closer.

So either you don't think this will happen, which would mean you don't understand how the models work (or at least, you aren't giving any sense you do), or you do think this will happen but want to pointlessly argue that this isn't "human feeling", which is true but totally irrelevant to what words it will predict and therefore the actions it will perform.

Either way, i'd downvote you.

And yet they're trained on the corpus of human writing. They may not act like humans but they do act like human writing.

"If you don't make profit, your business will be closed" is a pretty clear ultimatum for an agent tasked with creating a profitable business.

You can literally read their thoughts if you run an open model, they look like pretty human thoughts to me, albeit a neurotic human.