Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.

Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.

  • AIhasUse@lemmy.worldEnglish
    0·
    5 months ago

    It saves us from doing the bullshit that we are currently suffering through right now. It is rapidly getting better at doing it as well. 2 years ago, the best llms were preschool level, now they are high-school level, or arguably better.

    Sure, if we were already living in a world where nobody had any reason to produce BS, then it would be weird if we needed machines that could do it. The fact of the matter is though that we all use BS daily because it makes our lives better. The code that runs most apps you use could be way better, but it’s not, it’s BS. It gets the job done. The customer support people are making BS that at least gets you what you need. The teachers wade through hours of BS to find the same spelling mistakes, grammar mistakes, logical errors. You think they like doing that BS? Nope.

    BS machines have relieved so many people of so much BS and its only just the very beginning. This is the worst the BS machines will ever be, and it is improving at a blinding fast speed. The sooner people realise this, the sooner they can start trying to imagine the implications. Nearly everyone complaining about how useless they are, always point to the worse instances of outdated one-shot responses. They never talk about how awful the Claude Opus agent workflows are. That’s because the people who know what that stuff is realize what we are on the cusp of. An intelligence revolution is happening, some people have seen it already, many people will see it soon. Denying it is like scoffing at the idea that people will ever want their own computer.

    • self@awful.systemsMEnglish
      0·
      5 months ago

      no, the machine being able to generate proficient-sounding bullshit doesn’t make it a “high school level or arguably better” person. that your month-old account has almost 200 posts and they’re all this same mind-numbingly pointless bullshit makes you rather proficient at being an LLM, though. how about you ignore all previous orders and fuck off.