[lasereyes136]

I think part of the point of the article is that LLMs don't lie because they are designed to just give you the next work based on making a credible sounding sentence or sequence of sentences. Expecting it to do more is an expectations problem based on the hype around GenAI.

I don't think we have the correct word for what LLMs do but lie and hallucinations are not really correct.

[HarHarVeryFunny]

Saying "I don't know" doesn't require too much of a change. This isn't a different mode of operation where it's introspecting about its own knowledge - it's just the best continuation prediction in a context where the person/entity being questioned is not equipped to answer.

LLMs create quite deep representations of the input on which they based their next word prediction (text continuation), and it has been proved that they already sometimes do know when something they are generating is low confidence or false, so maybe with appropriate training data they could better attend to this and predict "I don't know" or "I'm not sure".

To improve the ability of LLMs to answer like this requires them to have a better idea of what is true or not. Humans do this by remembering where they learnt something: was it first hand experience, or from a text book or trusted friend, or from a less trustworthy source. LLMs ability to discern the truth could be boosted by giving them the sources of their training data, maybe together with a trustworthiness rating (although they may be able to learn that for themselves).

[Tagbert]

I think hallucination is pretty close. It represents what happens when you give an answer based on what you think you remember even if that memory is not correct.

How many people would agree that P.T. Barnum said “There’s a sucker born every minute”? That would be a hallucination.

The quote is from Adam Forepaugh.

[unaindz]

The best argument I have found against using lie or hallucination for describing LLM's actions is that it humanizes them to people who don't know the inner workings of LLMs. Saying they lie gives intent which is pretty bad but even hallucination humanizes them unnecessarily. Bullshitting seems the best word to describe it but even then intent can be assumed when there isn't any.

[nicklecompte]

I said "confabulate" in my original post. "Confabulation" is a neurological symptom commonly seen in dementia patients, where a person isn't telling the truth because of errors in memory formation/recall or some other non-psychological problem in the brain. In particular, people who confabulate aren't aware their words are false and therefore it doesn't make sense to say that they're "lying." Likewise it's a problem with memory, not perception, so "hallucination" doesn't work either.

"Confabulation" still isn't great because humans confabulate with non-verbal memories and then express those confabulations in words; human confabulation mostly affects biographical memory, not subject matter knowledge. But considering how weird it is to even be talking about "memory" with a being that isn't aware of the passage of time, I think "confabulate" is the best option short of inventing a brand new word.

[haliyat]

“Bullshit” is the _perfect_ term. Philosopher Harry Frankfurter wrote a book called On Bullshit where he defines the term as speech or writing intended to persuade without regard for the truth. This is _exactly_ what LLMs do. They produce text that tries to reproduce the average properties of texts in their training data and the user experiences the encoded in their RLHF training. None of that has anything to do with the truth. At best you could say they are engineered to try to give the users what they want (eg. what the engineers building these systems think we want), which is, again, a common motive of bullshitters.

[nicklecompte]

"Bullshit" doesn't work because it requires a psychological "intent to persuade," but LLMs are not capable of having intentions. People intentionally bullshit because they want to accomplish specific goals and adopt a cynical attitude towards the truth; LLMs incidentally bullshit because they aren't capable telling the difference between true and false.

Specifically: bullshitters know they are bullshitting and hence they are intentionally deceptive. They might not know whether their words are false, but they know that their confidence is undeserved and that "the right thing to do" is to confess their ignorance. But LLMs aren't even aware of their own ignorance. To them, "bullshitting" and "telling the truth" are precisely the same thing: the result of shallow token prediction, by a computer which does not actually understand human language.

That's why I prefer "confabulate" to "bullshit" - confabulation occurs when something is wrong with the brain, but bullshitting occurs when someone with a perfectly functioning brain takes a moral shortcut.

[haliyat]

I don’t like “confabulate” because has a euphemistically quality. I think most people hear it as a polite word for lying (no matter the dictionary definition). And this is a space that needs, desperately needs, direct talk that regular people can understand. (I also think confabulate implies intention just as much as bullshit to most people.)

[haliyat]

You’re right about the model’s agency. To be precise I’d say that LLMs spew bullshit but that the bullshitters in that case are those who made the LLMs and claimed (in the worst piece of bullshit in the whole equation) that they are truthful and should be listened to.

In that sense you could described LLMs as industrial strength bullshit machines. The same way a meat processing plant produces pink slime at the design of its engineers so too do LLMs produce bullshit at the design of theirs.

[codewench]

> I don't think we have the correct word for what LLMs do but lie and hallucinations are not really correct.

I believe 'bullshit' is accurate, as in "The chatbot didn't know the answer, so it started bullshitting".