>ChatGPT did not lie; it cannot lie.
If it lies like a duck, it is a lying duck.
If it lies like a duck, it is a lying duck.
A better description of what ChatGPT does is described well by one definition of bullshit:
> bullshit is speech intended to persuade without regard for truth. The liar cares about the truth and attempts to hide it; the bullshitter doesn't care if what they say is true or false
-- Harry Frankfurt, On Bullshit, 2005
https://en.wikipedia.org/wiki/On_Bullshit
ChatGPT neither knows nor cares what the truth is. If it bullshits like a duck, it is a bullshitting duck.
Those are the semantics of lying.
But "X like a duck" is about ignoring semantics, and focusing not on intent or any other subtletly, but only on the outward results (whether something has the external trappings of a duck).
So, if it produces things that look like lies, then it is lying.
That's the thing people are trying to point out. You can't look at something that looks like it's lying and conclude that it's lying, because intent is an intrinsic part of what it means to lie.
(1) get oneself into or out of a situation by lying. "you lied your way on to this voyage by implying you were an experienced crew"
(2) (of a thing) present a false impression. "the camera cannot lie"
2) "the camera cannot lie" - cameras have no intent?
I feel like I'm missing something from those definitions that you're trying to show me? I don't see how they support your implication that one can ignore intent when identifying a lie. (It would help if you cited the source you're using.)
The point was that the dictionary definition accepts the use of the term lie about things that can misrepresent something (even when they're mere things and have no intent).
The dictionary's use of the common saying "the camera cannot lie" wasn't to argue that cameras don't lie because they don't have intent, but to show an example of the word "lie" used for things.
I can see how someone can be confused by this when discussing intent, however, since they opted for a negative example. But we absolutely do use the word for inanimate things that don't have intent too.
Lying depends upon context.
Of course we know ChatGPT cannot lie like a human can, but a big reason the thing exists is to assemble text the same way humans do. So I think it’s useful rhetorically to say that ChatGPT, quite simply, lies.
Chatgpt is a device unlike Wikipedia,
As always mens rea is a very important part of criminal law. Also, just because you don't like what someone says / writes doesn't mean it is a crime (even if it is factually incorrect).
The expression "if it X like a duck" means precisely that we should judge a thing to be a duck or not, based on it having the external appereance and outward activity of a duck, and ignoring any further subleties, intent, internal processes, qualia, and so on.
In other words, "it lies like a duck" means: if it produces things that look like lies, it is lying, and we don't care how it got to produce them.
So, Chat-GPT absolutely does "lie like a duck".
Hallucinates is a far more accurate word.
But that's not really what happens with ChatGPT. The model doesn't know truth from fiction in the first place, but the whole point of a useful LLM is that there is some level of control and consistency around the output.
I've been using "bullshitting", because I think that's really what ChatGPT is demonstrating -- not a disconnection from reality, but not letting truth get in the way of a good story.
If it looked like ChatGPT was intentionally being deceptive, it would be a groundbreaking discovery, potentially even prompting a temporary shutdown of ChatGPT servers for a safety assessment.
and the point here is we should not ignore further subtleties, intent, internal process, qualia, etc because they are extremely relevant to the issue at hand.
Treating GPT like a malevolent actor that tells intentional lies is no more correct than treating it like a friendly god that wants to help you.
GPT is incapable of wanting or intending anything, and it's a mistake to treat it like it does. We do care how it got to produce incorrect information.
If you have a robot duck that walks like a duck and quacks like a duck and you dust off your hands and say "whelp that settles it, it's definitely a duck" then you're going to have a bad time waiting for it to lay an egg.
Sometimes the issues beyond the superficial appearance actually are important.
But the point is those are only relevant when trying to understand GPTs internal motivations (or lack thereof).
If we care for the practical effects of what it's spits out (the function the same as if GPT has lied to us), then calling them "hallucinations" is as good as calling them "lying".
>We do care how it got to produce incorrect information.
Well, not when trying to access whether it's true or false, and whether we should just blindly trust it.
From that practical aspect, most people care about (than about whether it has "intentions"), we can ignore any of its internal mechanics.
Thus treating it like it "beware, as it tends to lie", will have the same utility for most laymen (and be a much easier shortcut) than any more subtle formulation.
This always bugs me about how people judge politicians and other public figures not by what they've actually done, but some ideal of what is in their "heart of hearts" and their intentions and argue that they've just been constrained by the system they were in or whatever.
Or when judging the actions of nations, people often give all kinds of excuses based on intentions gone wrong (apparently forgetting that whole "road to hell is paved with good intentions" bit).
Intentions don't really matter. Our interface to everyone else is their external actions, that's what you've got to judge them on.
Just say that GPT/LLMs will lie, gaslight and bullshit. It doesn't matter that they don't have an intention to do that, it is just what they do. Worrying about intentions just clouds your judgement.
Too much attention on intentions is generally just a means of self-justification and avoiding consequences and, when it comes right down to it, trying to make ourselves feel better for profiting from systems/products/institutions that are doing things that have some objectively bad outcomes.