ChatGPT is full of sensitive private information and spits out verbatim text from CNN, Goodreads, WordPress blogs, fandom wikis, Terms of Service agreements, Stack Overflow source code, Wikipedia pages, news blogs, random internet comments, and much more.

  • NevermindNoMind@lemmy.world
    link
    fedilink
    English
    arrow-up
    46
    arrow-down
    1
    ·
    1 year ago

    This is interesting in terms of copyright law. So far the lawsuits from Sarah Silverman and others haven’t gone anywhere on the theory that the models do not contain a copies of books. Copyright law hinges on whether you have a right to make copies of a work. So the theory has been the models learned from the books but didn’t retain exact copies, like how a human reads a book and learns it’s contents but does not store an exact copy in their head. If the models “memorized” training data, including copyrighten works, OpenAI and others may have a problem (note the researchers said they did this same thing on other models).

    For the silicone valley drama addicts, I find it curious that the researchers apparently didn’t do this test on Bard of Anthropic’s Claude, at least the article didn’t mention them. Curious.

    • Excrubulent@slrpnk.net
      link
      fedilink
      English
      arrow-up
      23
      ·
      edit-2
      1 year ago

      “Copyrighten” is an interesting grammatical construction that I’ve never seen before. I’d assume it would come from a second language speaker.

      It looks like a mix of “written” and “righted”.

      “Copywritten” isn’ta word I’ve ever heard, but it would beca past tense form of “copywriting”, which is usually about writing text for advertisements. It’s a pretty niche concept.

      “Copyrighted” is the typical form for works that have copyright.

      I’m not a grammar nazi - what’s right & wrong is about what gets used which is why I talk about the “usual” form and not the “correct” form - but “copyrighted” is the clearest way to express that idea.

    • BetaDoggo_@lemmy.world
      link
      fedilink
      English
      arrow-up
      15
      ·
      1 year ago

      The paper suggests it was because of cost. The paper mainly focused on open models with public datasets as its basis, then attempted it on gpt3.5. They note that they didn’t generate the full 1B tokens with 3.5 because it would have been too expensive. I assume they didn’t test other proprietary models for the same reason. For Claude’s cheapest model it would be over $5000, and bard api access isn’t widely available yet.