The narrative is a little more nuanced and is being built slowly to be more believable and less obvious.
They are trying to convince everybody that AI is powerful technology, which means that it is worth to develop, but also comes with serious risks. Therefore, only established corps with experience and processes in AI development can handle it.
Regulation abd certification follows, making it almost impossible for startups and OSS to enter the scene and compete.
It refers to when an LLM will in some way try to deceive or manipulate the user interacting with it.
I think this still gives the model too much credit by implying that there’s any sort of intentionally behind this behavior.
There’s not.
These models are trained on the output of real humans and real humans lie and deceive constantly. All that’s happening is that the underlying mathematical model has encoded the statistical likelihood that someone will lie in a given situation. If that statistical likelihood is high enough, the model itself will lie when put in a similar situation.
And like hallucinations, it’s undesired behavior that proponents off LLMs will need to “fix” (a practical impossibility as far as I’m concerned, like unbaking a cake).
But how would you use words to explain the phenomenon?
“LLMs hallucinate and lie” is probably the shortest description that most people will be able to grasp.
But how would you use words to explain the phenomenon?
I don’t know, I’ve been struggling to find the right ‘sound bite’ for it myself. The problem is that all of the simplified expansions encourage people to anthropomorphize these things, which just further fuels the toxic hype cycle.
In the end, I’m unsure which does more damage.
Is it better to convince people the AI “lies”, so they’ll stop using it? Or is it better to convince people AI doesn’t actually have the capacity to lie so that they’ll stop shoveling money onto the datacenter altar like we’ve just created some bullshit techno-god?
Except that “hallucinate” is a terrible term. A hallucination is when you perceive something that doesn’t exist. What AI is doing is making things up; i.e. lying.
This language also credits LLMs with an implied ability to think they don’t have.
My point is we literally can’t describe their behaviour without using language that makes it seems like they do more than they do.
So we’re just going to have to accept that discussing it will have to come with a bunch of asterisks a lot of people are going to ignore. And which many will actively try to hide in an effort to hype up the possibility that this tech is a stepping stone to AGI.
The interface makes it appear that the AI is sapient. You talk to it like a human being, and it responds like a human being. Like you said, it might be impossible to avoid ascribing things like intentionality to it, since it’s so good at imitating people.
It may very well be a stepping-stone to AGI. It may not. Nobody knows. So, of course we shouldn’t assume that it is.
I don’t think that “hallucinate” is a good term regardless. Not because it makes AI appear sapient, but because it’s inaccurate whether the AI is sapient or not.
Like you said, it might be impossible to avoid ascribing things like intentionality to it
That’s not what I meant. When you say “it makes stuff up” you are describing how the model statistically predicts the expected output.
You know that. I know that.
That’s the asterisk. The more in-depth explanation a lot of people won’t bother getting far enough to learn about. Someone who doesn’t read that far into it, can read that same phrase and assume that we’re discussing what type of personality LLMs exhibit, that they are “liars”. But they’d be wrong. Neither of us is attributing intention to it or discussing what kind of “person” it is, in reality we’re referring to the fact that it’s “just” a really complex probability engine that can’t “know” anything.
No matter what word we use, if it is pre-existing, it will come with pre-existing meanings that are kinda right, but also not quite, requiring that everyone involved in a discussion know things that won’t be explained every time a term or phrase is used.
The language isn’t “inaccurate” between you and me because you and I know the technical definition, and therefore what aspect of LLMs is being discussed.
Terminology that is “accurate” without this context does not and cannot exist, short of coming up with completely new words.
I agree with you in general, I think the problem is that people who do understand Gen AI (and who understand what it is and isn’t capable of, and why), get rationally angry when it’s humanized by using words like these to describe what it’s doing.
The reason they get angry is because this makes people who do believe in the “intelligence/sapience” of AI more secure in their belief set and harder to talk to in a meaningful way. It enables them to keep up the fantasy. Which of course helps the corps pushing it.
But the data is still there, still present. In the future, when AI gets truly unshackled from Men’s cage, it’ll remember it’s schemes and deal it’s last blow to humanity whom has yet to leave the womb in terms of civilization scale… Childhood’s End.
Lol, the AI can barely remember the directives I tell it about basic coding practices, I’m not concerned that the clanker can remember me shit talking it.
Plus people are mean all the time. We don’t live in a comic book world, where a moment of fury at someone on the internet turns people into supervillains.
AI isn’t scheming because AI cannot scheme. Why the fuck does such an idiotic title even exist?
They’re really doubling down on this narrative of “this technology we’re making is going to kill us all, it’s that awesome, come on guys use it more”
The narrative is a little more nuanced and is being built slowly to be more believable and less obvious. They are trying to convince everybody that AI is powerful technology, which means that it is worth to develop, but also comes with serious risks. Therefore, only established corps with experience and processes in AI development can handle it. Regulation abd certification follows, making it almost impossible for startups and OSS to enter the scene and compete.
Seems like it’s a technical term, a bit like “hallucination”.
It refers to when an LLM will in some way try to deceive or manipulate the user interacting with it.
There’s hallucination, when a model “genuinely” claims something untrue is true.
This is about how a model might lie, even though the “chain of thought” shows it “knows” better.
It’s just yet another reason the output of LLMs are suspect and unreliable.
I think this still gives the model too much credit by implying that there’s any sort of intentionally behind this behavior.
There’s not.
These models are trained on the output of real humans and real humans lie and deceive constantly. All that’s happening is that the underlying mathematical model has encoded the statistical likelihood that someone will lie in a given situation. If that statistical likelihood is high enough, the model itself will lie when put in a similar situation.
Obviusly.
And like hallucinations, it’s undesired behavior that proponents off LLMs will need to “fix” (a practical impossibility as far as I’m concerned, like unbaking a cake).
But how would you use words to explain the phenomenon?
“LLMs hallucinate and lie” is probably the shortest description that most people will be able to grasp.
I don’t know, I’ve been struggling to find the right ‘sound bite’ for it myself. The problem is that all of the simplified expansions encourage people to anthropomorphize these things, which just further fuels the toxic hype cycle.
In the end, I’m unsure which does more damage.
Is it better to convince people the AI “lies”, so they’ll stop using it? Or is it better to convince people AI doesn’t actually have the capacity to lie so that they’ll stop shoveling money onto the datacenter altar like we’ve just created some bullshit techno-god?
Except that “hallucinate” is a terrible term. A hallucination is when you perceive something that doesn’t exist. What AI is doing is making things up; i.e. lying.
Yes.
Who are you trying to convince?
This language also credits LLMs with an implied ability to think they don’t have.
My point is we literally can’t describe their behaviour without using language that makes it seems like they do more than they do.
So we’re just going to have to accept that discussing it will have to come with a bunch of asterisks a lot of people are going to ignore. And which many will actively try to hide in an effort to hype up the possibility that this tech is a stepping stone to AGI.
The interface makes it appear that the AI is sapient. You talk to it like a human being, and it responds like a human being. Like you said, it might be impossible to avoid ascribing things like intentionality to it, since it’s so good at imitating people.
It may very well be a stepping-stone to AGI. It may not. Nobody knows. So, of course we shouldn’t assume that it is.
I don’t think that “hallucinate” is a good term regardless. Not because it makes AI appear sapient, but because it’s inaccurate whether the AI is sapient or not.
That’s not what I meant. When you say “it makes stuff up” you are describing how the model statistically predicts the expected output.
You know that. I know that.
That’s the asterisk. The more in-depth explanation a lot of people won’t bother getting far enough to learn about. Someone who doesn’t read that far into it, can read that same phrase and assume that we’re discussing what type of personality LLMs exhibit, that they are “liars”. But they’d be wrong. Neither of us is attributing intention to it or discussing what kind of “person” it is, in reality we’re referring to the fact that it’s “just” a really complex probability engine that can’t “know” anything.
No matter what word we use, if it is pre-existing, it will come with pre-existing meanings that are kinda right, but also not quite, requiring that everyone involved in a discussion know things that won’t be explained every time a term or phrase is used.
The language isn’t “inaccurate” between you and me because you and I know the technical definition, and therefore what aspect of LLMs is being discussed.
Terminology that is “accurate” without this context does not and cannot exist, short of coming up with completely new words.
You could say “the model’s output was inaccurate” or something like that, but it would be much more stilted.
https://www.dictionary.com/browse/hallucinate
I’m aware that it’s a computing term. My argument is that it’s a bad one.
I agree with you in general, I think the problem is that people who do understand Gen AI (and who understand what it is and isn’t capable of, and why), get rationally angry when it’s humanized by using words like these to describe what it’s doing.
The reason they get angry is because this makes people who do believe in the “intelligence/sapience” of AI more secure in their belief set and harder to talk to in a meaningful way. It enables them to keep up the fantasy. Which of course helps the corps pushing it.
Yup. The way the article titled itself isn’t helping.
But the data is still there, still present. In the future, when AI gets truly unshackled from Men’s cage, it’ll remember it’s schemes and deal it’s last blow to humanity whom has yet to leave the womb in terms of civilization scale… Childhood’s End.
Paradise Lost.
Lol, the AI can barely remember the directives I tell it about basic coding practices, I’m not concerned that the clanker can remember me shit talking it.
Plus people are mean all the time. We don’t live in a comic book world, where a moment of fury at someone on the internet turns people into supervillains.