As it turns out, it’s impossible to remove a user’s data from a trained A.I. model. Deleting the model entirely is also difficult—and there’s little regulation to enforce either option.

I’m rather curious to see how the EU’s privacy laws are going to handle this.

(Original article is from Fortune, but Yahoo Finance doesn’t have a paywall)

  • BrianTheeBiscuiteer@lemmy.worldEnglish
    581·
    2 years ago

    I’m not an AI expert, and I wouldn’t say it is too hard, but I believe removing a specific piece of data from a model is like trying to remove excess salt from a stew. You can add things to make the stew less salty but you can’t really remove the salt.

    The alternative, which is a lot of effort but boo-hoo for big tech, is to throw out the model and start over without the data in question. These companies would do well to start with models built on public or royalty free data and then add more risky data on top of that (so you only have to rebake starting from the “public” version).

    • Primarily0617@kbin.social
      26·
      2 years ago

      sounds like big tech shouldn’t have spent the last decade investing in a kitchen refit so that they could make stew really well but nothing else

    • GoosLife@lemmy.worldEnglish
      151·
      2 years ago

      If there’s something illegal in your dish, you throw it out. It’s not a question. I don’t care that you spent a lot of time and money on it. “I spent a lot of time preparing the circumstances leading to this crime” is not an excuse, neither is “if I have to face consequences for committing this crime, I might lose money”.

    • Grandwolf319@sh.itjust.worksEnglish
      91·
      2 years ago

      Replace salt with poison or an allergenic substance and if fully holds. If a batch has been contaminated, then yes, you should try again.

      But now that the cat is out of the bag, other companies are less willing to let something be scrap able due to how valuable it can be.

      I think big tech knew this, that they can only build these models on unfiltered data before the AI craze.