I have many conversations with people about Large Language Models like ChatGPT and Copilot. The idea that “it makes convincing sentences, but it doesn’t know what it’s talking about” is a difficult concept to convey or wrap your head around. Because the sentences are so convincing.

Any good examples on how to explain this in simple terms?

Edit:some good answers already! I find especially that the emotional barrier is difficult to break. If an AI says something malicious, our brain immediatly jumps to “it has intent”. How can we explain this away?

  • HorseRabbit@lemmy.sdf.org
    1·
    6 months ago

    Not an ELI5, sorry. I’m an AI PhD, and I want to push back against the premises a lil bit.

    Why do you assume they don’t know? Like what do you mean by “know”? Are you taking about conscious subjective experience? or consistency of output? or an internal world model?

    There’s lots of evidence to indicate they are not conscious, although they can exhibit theory of mind. Eg: https://arxiv.org/pdf/2308.08708.pdf

    For consistency of output and internal world models, however, their is mounting evidence to suggest convergence on a shared representation of reality. Eg this paper published 2 days ago: https://arxiv.org/abs/2405.07987

    The idea that these models are just stochastic parrots that only probabilisticly repeat their training data isn’t correct, although it is often repeated online for some reason.

    A little evidence that comes to my mind is this paper showing models can understand rare English grammatical structures even if those structures are deliberately withheld during training: https://arxiv.org/abs/2403.19827