Dear Stack Overflow, Inc.
openletter.mousetail.nl

and as always, the culprit is ChatGPT. Stack Overflow Inc. won’t let their mods take down AI-generated content

  • pAULIE42o@beehaw.orgEnglish
    1·
    1 year ago

    I’m no pro here, but I think the underlying ‘issue’ is that soon these types of sites will be driven by AI. Mods will just look over the content, but sadly I think the days of mods being the most intelligent person in the room are numbered.

    I don’t trust AI output/answers today, but tomorrow they’re going to be spot-on and answer better than we can. :/

    I think the Inc. [corporations] know the writing on the wall and are just getting everyone ready for the inevitable asap.

    What say you?

    • Pigeon@beehaw.orgEnglish
      1·
      1 year ago

      I dunno about “tomorrow”. Eventually, maybe. But today’s AI are just language models. If there are no humans answering questions and creating new reporting for new events/tech/etc, then the AI can’t be trained on their output and won’t be able to say a single thing about those new topics. It’ll pretend to and make shit up, but that’s it.

      Being just language models - really great ones, but still, without any understanding of the content of what they say whatsoever - they’re currently in a state of making shit up all the time. All they care about is the likelihood that one word or phrase or paragraph might typically follow another, for truthy sounding language, but that’s often very far from actual truth.

      The only way to get around that is to create AI that isn’t just a pile of language algorithms, and that’s an entirely different beast than what we’re dealing with now, who knows how far off, if it’s even possible. You can’t just iteratively improve a language algorithm into not being just a language algorithm anymore.

      • kevin@beehaw.orgEnglish
        1·
        1 year ago

        I imagine it’ll be possible in the near future to improve the accuracy of technical AI content somewhat easily. It’d go something along these lines: have an LLM generate a candidate response, then have a second LLM capable of validating that response. The validator would have access to real references it can use to ensure some form of correctness, ie a python response could be plugged into a python interpreter to make sure it, to some extent, does what it is proported to do. The validator then decides the output is most likely correct, or generates some sort of response to ask the first LLM to revise until it passes validation. This wouldn’t catch 100% of errors, but a process like this could significantly reduce the frequency of hallucinations, for example.

        • Tutunkommon@beehaw.orgEnglish
          1·
          1 year ago

          Best description I’ve heard is that LLM is good at figuring out what the correct answer should look like, not necessarily what it is.