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Empathy is what language is for. It's language itself that is doing the empathy: and that isn't simulated at all. It was all written by people.

All an LLM can do is follow the structural patterns, and use them to shuffle.



This doesn't make any sense. Empathy itself is qualia; the language is merely a medium to communicate it, and far from the only one (e.g. facial expressions are generally better at it).

As for LLMs "following the structural patterns" of empathetic language - sure, that's exactly what simulating empathy is.


> the language is merely a medium to communicate it

Precisely. What else is communication if not empathy accomplished via language? Failed communication?

Language is not the only tool for communication, and communication is not the only tool for empathy.

> As for LLMs "following the structural patterns" of empathetic language - sure, that's exactly what simulating empathy is.

It's a matter of perspective: a character in a story follows the patterns of emphatic language. Do they empathize directly with the reader?

An LLM cannot break the fourth wall. It can only present one that was already broken.

An LLM doesn't look at the patterns in its model objectively. It only uses them in the process of modeling more patterns.

An LLM itself cannot reason, it can only model the patterns of reason that humans have already encoded into language into text.


I don't see what practical difference any of this makes. We can play word games all day long, but that won't convince Blake Lemoine or countless Replika users. To them, it's not "a character in a story", and that's the important point here.


The character of a story does not think, or do anything outside of what the writer of that story writes them to. The character cannot write itself!

That is the distinction I am making here.

Any person using an LLM is effectively playing "word games"; except instead of words, the game uses tokens; and instead of game rules, they follow pre-modeled token patterns. Those patterns are wholly dependent on the content of the training corpus text. The user only gets to interact by writing prompts: each prompt gets tokenized, the tokens get modeled, and the resulting difference gets printed back to the user.

No new behavior is ever created from within the model itself.




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