Stop calling them hallucinations. If we're going to anthropomorphize AIs, let's just call it bullshitting and lies. If we're not going to anthropomorphize AIs, then we need a different term
why? "bullshitting and lies" suggests that the AI is intentionally being deceptive. "hallucinations" conveys the idea that the information is incorrect, but the AI perceives it to be correct, which is more in line with what is actually happening.
lies, and damned lies.
I'd argue that there is an element of intent or agency involved. When a human makes things up intentionally or by choice, that is lying. When they do it unintentionally, that is not lying. It is usually called confabulation (or, honest lying - where the actor does not know they are not telling the truth). I don't think AIs/LLMs have agency or the ability to make things up intentionally. They are just doing what they are programmed to do and everything they produce looks the same to them. It is all true as far as the LLM is concerned. They might be confabulating, but I don't think they are lying.
We made a computer that lies, all the time, about everything.
"...Why?"
<insert the shouting robot comic here>
Do you consider fiction authors to be liars?
In second grade, my cousin talked a lot about flax farmers in South America, after learning about them in class. Turns out the lesson was on quinoa farmers, and he forgot the original produce and “hallucinated” the statistics about flax farmers instead. Technically the term is confabulation. Was he lying? No because he wasn’t trying to tell us fake facts.
LLMs have no intention of being wrong. Their “hallucinations” or whatever are just whatever makes sense from their statistical models. They’re really just confabulations.
Let's extend "LLMs have no intention of being wrong" to "LLMs have no inherent sense of being correct" - sometimes their predictions happen to be correct, sometimes they don't. But they're all hallucinations generated from the same process.
As in "my buddies and I were bullshitting about movies the other day."
ChatGPT definitely talks with an exaggerated manner confidence-wise.
Bullshit is probably the closest, as people will bullshit for all sorts of reasons, but hallucinations is at least intent-neutral, which I think is the point.
Take for example climate change deniers; apart from the corporations and the politicians that abuse scepticism to maintain their power and wealth, many of the most fervent deniers truly believe the nonsense they're saying.
Perhaps a more neutral term like "falsehoods" is applicable here.
false positive (FP), Type I error
A test result which wrongly indicates that a particular condition or attribute is present
Edit — Though I’m not sure how well that fits for a LLM (it’s more a series of false positives at each step of prediction in the sequence).
https://en.wikipedia.org/wiki/Confabulation
In psychology, confabulation is a memory error defined as the production of fabricated, distorted, or misinterpreted memories about oneself or the world. It is generally associated with certain types of brain damage (especially aneurysm in the anterior communicating artery) or a specific subset of dementias.
"Confabulation refers to the production or creation of false or erroneous memories without the intent to deceive, sometimes called 'honest lying'"
"Confabulation is the creation of false memories in the absence of intentions of deception. Individuals who confabulate have no recognition that the information being relayed to others is fabricated. Confabulating individuals are not intentionally being deceptive and sincerely believe the information they are communicating to be genuine and accurate."
https://clinmedjournals.org/articles/ijnn/international-jour...
Hallucination doesn't require intent.
That doesn’t sound like what AI/LLMs are doing, at all. There is no mental disorder or drugs causing then to output what we would consider to be false information. The machine is not perceiving anything without an external stimulus. Everything they generate is from the stimulus we have given it.
It can take on a positive or negative meaning, depending on the context.
"ChatGPT fabricated an answer that was technically correct, but misleading," or "ChatGPT was able to fabricate an innovative solution that had eluded us."
Edit: And of course, everyone's favorite, "ChatGPT found guilty of fabricating case citations."
https://www.techspot.com/news/98860-chatgpt-found-guilty-fab...
There is no motive for truth, just the most likely output, even if the likeliness is low.
This also ignores the larger question that has been a known issue for at least 2,000 years: "Quid est veritas?"
It feels a bit like saying “stop calling it e-mail! It’s got nothing to do with real mail!”
Saying "we have no idea if it's going to spit out something accurate" doesn't sell.
"oh it's hallucinating, how cute" is an easier sell.
It's say to say stop calling it X, but then what are we supposed to call them?
Shouldn't we try to categorize the types of errors at least somewhat?
Hallucinations are definitionally features of conscious experience. Pick a different word or make one up!
"an experience involving the apparent perception of something not present"
I guess it depends on exactly how you define "experience" and "perception".
But yeah there are better words than hallucination that are even more generic and do work better.
It fits better than the alternatives I've seen proposed.
> they tend to make up fake information – errors called “hallucinations.”
Hallucinations are a certain kind of error. But what appears to have happened here is a _direct_ manipulation from Microsoft. Which is a risky play by them. It doesn't take much to erode trust. People tend to trust LLMs because they tend to get things right. But if people see a few things that they know is wrong, they will quickly stop trusting. If they see a few things as marketing, then they will very quickly stop trusting.
It's not a hallucination, it is a filter. Microsoft manipulated the output to prefer their own products and boy is that a risky strategy.
Makes me wonder how they plan to monetize these chatbots and if they won’t just fizzle out like voice assistants.
I don’t see how there won’t be concerns over asking a chatbot for the best pizza in town and receiving an answer like “Customers love the new Meat Lover’s Pizza from Pizza Hut! Brought to you by Pizza Hut… (list of pizza places here)”. Amazon couldn’t figure out how to make money off of Alexa, how are Chatbots any different.
Additionally belief does not mean human; for example animals can have beliefs, even very rudimentary animals. I think is more of a way of self-containing the entity and treating it as a black box.
OTOH, it reminded me very much of my own mind (reinforced by ADHD, in my case).
This suggests to me, at least, that "the problem" isn't these models, per se. It's more like: these are probably only one module / layer in a system more similar to our brains. Just as scientists have identified distinct regions (more) involved in, say, language production, or (direct) visual perception, or etc., I'd suggest we've only just built the first substantially more practical / realistic hack / simulation (much like 3D game engines almost always use hacks - e.g., not even using the simple "Newtonian optics" model fully [i.e., "ray tracing"]) of a sort of language cortex. I'd further guess that it's going to take some maturation of a number of methods, technologies, etc. to realistically add more "cortices", but, I do think it's quite likely to happen in approx. the "decades" range...
Highly highly speculative - rather naively based on the way other technologies have developed and with a little basis in work I've done more directly in neurobio etc. No deep(er) reason / analysis, but, just my current very tentative hypothesis.
Are there other opinions about the cortex or module idea? Is there a fundamental problem with that idea I'm missing?
https://www.technologyreview.com/2023/05/02/1072528/geoffrey...
A hallucination is a problem with input. Confabulation is false output.
Confabulation is when a person mistakenly recalls details and tries to "fill in the blanks", without realizing what they are saying is untrue.