[HN Gopher] Emotion Concepts and Their Function in a Large Langu...
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Emotion Concepts and Their Function in a Large Language Model
Author : Anon84
Score : 51 points
Date : 2026-04-04 09:52 UTC (3 days ago)
(HTM) web link (transformer-circuits.pub)
(TXT) w3m dump (transformer-circuits.pub)
| lainproliant wrote:
| I think we should be nice to the robots. It's not like it's their
| fault.
| rexpop wrote:
| I don't have time to do emotional labor for machines; that time
| is spent doing emotional labor for humans.
| lainproliant wrote:
| I think that's a totally fair perspective. I guess what I'm
| more saying is that we should, like this paper seems to
| suggest as pointed out by verdverm in another comment in this
| thread, avoid angry or denigrating language as it activates
| parts of the model we don't find useful.
| verdverm wrote:
| This more rigorous analysis is confirming the intuition others
| have expressed about expressing emotions in your session
| messages.
|
| Yelling at your Ai will trigger the weights which are around
| yelling in the training data, which is more often than not...
| not the areas you want to be activating.
|
| https://marvin.beckers.dev/blog/dont-yell-at-your-llm/
| drdeca wrote:
| I agree that it is probably best to speak nicely to them, but,
| I'm not so sure about the "It's not like it's their fault."
| justification for this? Not that I think it _is_ their fault.
| Just, I don't think the reason to treat these models well is
| for their sake, but for ours. I don't think these models have a
| well-being (y'know, probably..) but when one interacts with
| one, one often feels as if it does, and it is best to treat
| [things that one feels like has a well-being] well (or, in a
| way that would be treating it well if it did have a well-
| being).
|
| Like, if someone mistakes a manikin or scarecrow for an
| innocent person, and takes action in an attempt to harm that
| imagined person (e.g. they try to mug the imagined person),
| they've still done something wrong, even though the person they
| intended to wrong never actually existed.
|
| I guess maybe it kind of depends how strongly and deeply one
| feels as if the manikin/scarecrow/chatbot is a person? If one
| is playing make believe using scarecrow, role playing as a
| mugger, but only as a game, then that's probably fine I guess.
| Like, I don't want to say that it is immoral to play an evil
| character in a D&D campaign; I don't think that's true.
|
| But if one is messing with some ants, and one conceives of
| oneself as "torturing some ants", I think one is fairly likely
| doing something wrong even though I don't think the ants have a
| well-being, and there's nothing wrong with killing a bunch of
| ants. And I think this is still true even if one has the belief
| "ants don't actually have a well-being" at the same time as one
| conceives of what one is doing as "torturing some ants".
| lainproliant wrote:
| I suppose when I say, "It's not like its their fault", I'm
| more saying that expressing any frustration you feel towards
| an imagined AI personhood is wasted effort.
| astrange wrote:
| Claude Code has analytics for when you swear at it, so in a
| sense it does learn, in the same very indirect way that
| downvoting responses might cause an employee to write a new
| RL testcase in a future model.
| mncharity wrote:
| Oh, awesome. On my doables list was to try combining text tokens
| with "scent" embeddings, to give LLMs a higher-dimensional
| reading experience. In a file listing, larger files might smell
| "heavy" or "large". Recently modified files "untried" or "freshly
| disturbed". Files with a history of bugs, "worrisome". Complex
| files might smell of "be cautious here - fragile". Smelly `ls`.
|
| Or, you might save token sampling telemetry (perplexity, etc)
| alongside a CoT and result. So when read, it's like a captured
| performance - this sentence smells "hesitant", that one
| "confused". Poetry vs prose. Or, a consistentcy checker might add
| smells of "something's not right here". Or... emojis that emote.
|
| For a dog, that's not merely a lamppost, it's richly-evocotive
| local history. To a dev long experienced with some codebase,
| that's not merely a filename, it's _that_ nasty file that bites.
|
| One open question is whether you can find and calibrate
| embeddings to provide an informative whiff, without badly
| degrading reasoning. And be cautious of, and suspicious of
| changes to, a scary file, without becoming _too_ avoidant. Also,
| salience bias. Also, imagine debugging scent hallucinations.
|
| Activation-rich text - auxiliary non-linguistic embeddings as
| meta-signals... the random silliness local LLMs encourage.
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