European Union lawmakers are set to give final approval to the 27-nation bloc’s artificial intelligence law.

European Union lawmakers are set to give final approval to the 27-nation bloc’s artificial intelligence law Wednesday, putting the world-leading rules on track to take effect later this year.

Lawmakers in the European Parliament are poised to vote in favor of the Artificial Intelligence Act five years after they were first proposed. The AI Act is expected to act as a global signpost for other governments grappling with how to regulate the fast-developing technology.

“The AI Act has nudged the future of AI in a human-centric direction, in a direction where humans are in control of the technology and where it — the technology — helps us leverage new discoveries, economic growth, societal progress and unlock human potential,” said Dragos Tudorache, a Romanian lawmaker who was a co-leader of the Parliament negotiations on the draft law.

Big tech companies generally have supported the need to regulate AI while lobbying to ensure any rules work in their favor. OpenAI CEO Sam Altman caused a minor stir last year when he suggested the ChatGPT maker could pull out of Europe if it can’t comply with the AI Act — before backtracking to say there were no plans to leave.

  • General_Effort@lemmy.world
    0·
    6 months ago

    all models carry bias (see recent gemini headlines for an extreme example), and what exactly those are can range from important to extremely important, depending on the use case!

    it’s also important if you want to iterate on a model: if you use the same data set and train the model slightly differently, you could end up with entirely different models!

    Meaning what?

    (and your definition of open source is…unique.)

    I omitted requirements on freely sharing it as implied, but otherwise?

    • 9bananas@lemmy.world
      0·
      6 months ago

      Meaning what?

      meaning the models training data is what lets you work around or improve on that bias. without the training data, that’s (borderline) impossible. so in order to tweak models and further development, you need to know what exactly went into the model, or you’ll spend a lot of wasted time guessing around.

      I omitted requirements on freely sharing it as implied, but otherwise?

      you disregarded half of what makes an AI model. the half that actually results in a working model. without the training data, you’d only have some code that does…something.

      and that something is entirely dependent on the training data!

      so it’s essential, not optional, for any kind of “open source” AI, because without it you’re working with a black box. which is by definition NOT open source.