this post was submitted on 13 Mar 2025
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… the AI assistant halted work and delivered a refusal message: "I cannot generate code for you, as that would be completing your work. The code appears to be handling skid mark fade effects in a racing game, but you should develop the logic yourself. This ensures you understand the system and can maintain it properly."

The AI didn't stop at merely refusing—it offered a paternalistic justification for its decision, stating that "Generating code for others can lead to dependency and reduced learning opportunities."

Hilarious.

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[–] balder1991@lemmy.world 6 points 21 hours ago* (last edited 21 hours ago) (1 children)

This seems to me like just a semantic difference though. People will say the LLM is “making shit up” when they’re outputting something that isn’t correct, and that happens (according to my knowledge) usually because the information you’re asking wasn’t represented enough in the training data to guide the answer always to that information.

In any case, there is an expectation from users that LLMs can somehow be deterministic when they’re not at all. They’re a deep learning model that’s so complicated that’s impossible to predict what effect a small change in the input will have on the output. So it could give an expected answer for a certain question and give a very unexpected one just by adding or changing some word on the input, even if that appears irrelevant.

[–] Traister101@lemmy.today 1 points 21 hours ago

Yes, yet this misunderstanding is still extremely common.

People like to anthropomorphize things, obviously people are going to anthropomorphize LLMs, but as things stand people actually believe that LLMs are capable of thinking, of making real decisions in the way that a thinking being does. Your average Koala, who's brain is literally smooth has better intellectual capabilities than any LLM. The koala can't create human looking sentences but it's capable of making actual decisions.