Comment on AI Is Scheming, and Stopping It Won’t Be Easy, OpenAI Study Finds
zarkanian@sh.itjust.works 3 days agoThe 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.
Jakeroxs@sh.itjust.works 3 days ago
zarkanian@sh.itjust.works 3 days ago
I’m aware that it’s a computing term. My argument is that it’s a bad one.
MentalEdge@sopuli.xyz 3 days ago
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 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.
zarkanian@sh.itjust.works 3 days ago
You could say something like “the model’s output was inaccurate” or something like that, but it would be much more stilted.