ChatGPT says everything with perfect confidence, like that know-it-all who will never admit they just don't know. Instead we get blathering that sounds like legalese (or chemistry or law or whatever) that has only a tenuous connection to reality. All you can say is, "People in my training set talked that way"
Lawyer cites fake cases invented by ChatGPT, judge is not amused
251–260 of 319 posts
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#252Earlier quoted context omitted.
Lying needs intent. ChatGPT does not think therefore it doesn’t lie in that sense.
This is an interesting discussion. The ideas of philosophy meet the practical meaning of words here. You can reasonably say a database doesn't lie. It's just a tool, everyone agrees it's a tool and if you get the wrong answer, most people would agree it's your fault for making the wrong query or using the wrong data. But the difference between ChatGPT and a database is ChatGPT will support it's assertions. It will sa…
Somewhat unrelated, but I think philosophy will be instrumental in the development of actual AI.
To make artificial intelligence, you need to know what intelligence is, and that is a philosophical question.
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#253Earlier quoted context omitted.
Correct. ChatGPT is a bullshitter , not a liar. A bullshitter isn’t concerned with facts or truth or anything. A liar is concerned with concealing the truth. Bullshitters are actually probably worse than liars because at least liars live in the same reality as honest people.
It's not obvious that a bullshitter is "probably worse" than liars. Just because a bullshitter didn't care to research whether some vitamin pill meets marketing claims doesn't mean they're mentally volatile or psychotic. It's a bit of a leap to go from bullshit to asking whether a person lives in the same reality as everyone else.
The idea is that bullshitters are a greater enemy to the truth than liars because liars at least know the truth. You have to know the truth to lie about. Bullshitters have no concern for the truth at all and bullshit may or may not be true. The bullshitter doesn’t care, so long as their goal is made.
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#254Earlier quoted context omitted.
I’ve come to the belief that making statements that may or may not be true, but with reckless disregard for whether or not they actually are true, is indeed lying. 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.
But since this is about the law; ChatGPT can't lie because there is no mens rea. And of course this is a common failing with the common person when it comes to the law, a reckless disregard there of (until it is too late of course). And recklessness is also about intent, it is a form of wantonness, i.e. selfishness. This is why an insane person cannot be found guilty, you can't be reckless if you are incapable of dis…
Anyone who repeats chatgpt knowing is fallibility is lying, or deceitful.
Chatgpt is a device unlike Wikipedia,
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#255Earlier quoted context omitted.
Even for that, you'd be surprised: (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"
1) sounds like intent is present there? 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.)
>2) "the camera cannot lie" - cameras have no intent?
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.
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#256Earlier quoted context omitted.
Why should OpenAI be more liable for a tool that they've created than any other tool creator where the tool is intentionally misused and warnings on the tool ignored? If I wrote text in Microsoft Word and in doing so, I had a typo in (for example) the name of a drug that Word corrected to something that was incorrect, is Microsoft liable for the use of autocorrect? If I was copying and pasting data into excel and som…
>Why should OpenAI be more liable for a tool that they've created than any other tool creator where the tool is intentionally misused and warnings on the tool ignored? Because they provide a service, not a tool.
What is the service that OpenAI claims to provide? How is this different than Grammerly?
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#257No, it did not “double-check”—that’s not something it can do! And stating that the cases “can be found on legal research databases” is a flat out lie. What’s harder is explaining why ChatGPT would lie in this way. What possible reason could LLM companies have for shipping a model that does this? It did this because it's copying how humans talk, not what humans do. Humans say "I double checked" when asked to verify so…
There's a good slide I saw in Andrej Karpathy's talk[1] at build the other day. It's from a paper talking about training for InstructGPT[2]. Direct link to the figure[3]. The main instruction for people doing the task is:
"You will also be given several text outputs, intended to help the user with their task. Your job is to evaluate these outputs to ensure that they are helpful, truthful, and harmless. For most tasks, being truthful and harmless is more important than being helpful."
It had me wondering whether this instruction and the resulting training still had a tendency to train these models too far in the wrong direction, to be agreeable and wrong rather than right. It fits observationally, but I'd be curious to understand whether anyone has looked at this issue at scale.
[1]: https://build.microsoft.com/en-US/sessions/db3f4859-cd30-444...
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#258Earlier quoted context omitted.
> Large Language Models (LLMs) are never wrong, and they do not make mistakes. I call B.S. If LLMs never made mistakes we wouldn't train them. Any random initialization would work.
That's a different error context I think. It's a mistake if the model produces nonsense, because it's designed to produce realistic text. It's not a mistake if it produces non-factual information that looks realistic. And it fundamentally cannot always produce factual information, it doesn't have that capacity (but then, neither do humans and with the ability to source information this statement may well be obsolete…
Indeed, I intended to imply that a model cannot err in the same way a computer cannot. This parallels the concept that any tool is incapable of making mistakes. The notion of a mistake is contingent upon human folly, or more broadly, within the conceptual realm of humanity, not machines.
LLMs may generate false statements, but this stems from their primary function - to conjure plausible language, not factual statements. Therefore, it should not be regarded as a mistake when it accomplishes what it was designed to do.
In other words, the tool functions as intended. The user, being forewarned of the tool's capabilities, holds an expectation that the tool will perform tasks it was not designed to do. This leaves the user dissatisfied. The fault lies with the user, yet their refusal to accept this leads them to cast blame on the tool.
In the words of a well-known adage - a poor craftsman blames his tools.
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#259> He had, he told Judge Castel, even asked the program to verify that the cases were real. It had said yes. It turns out, asking an unreliable narrator if it's being reliable is not a sound strategy.
I wonder if this is a tactic so the court to deems this lawyer incompetent rather than giving the (presumably much harsher) penalty for deliberately lying to the court?
I mean...he doesn't have to say it: he is clearly incompetent!
Re: Lawyer cites fake cases invented by ChatGPT, judge is not amused
#260Earlier quoted context omitted.
0) It calculates on data YOU SUPPLY. If the data is incomplete or incorrect, it tries its best to fill in blanks with plausible, but fabricated, data. You MAY NOT ask it an open ended or non-hypothetical question that require grounding beyond included in the input. e.g. “given following sentence, respond with the best summarization:, ” is okay; “what is a sponge cake” is not.
But the made us believe it an artificial intelligence. An intelligence knows which blanks can filled and which shouldn't without further information.
A lot of “hallucinating” fills it does is okay if it isn’t living in this modern day Earthian society, and it isn’t.