Child safety org flags new CSAM with AI trained on real child sex abuse images
arstechnica.com
AI will make it harder to spread CSAM online, child safety org says.

Today, a prominent child safety organization, Thorn, in partnership with a leading cloud-based AI solutions provider, Hive, announced the release of an AI model designed to flag unknown CSAM at upload. It’s the earliest AI technology striving to expose unreported CSAM at scale.

  • Todd Bonzalez@lemm.eeEnglish
    17·
    10 hours ago

    No. This is an inference model, not a generative model. You generally cannot train a model for both, unless you do it on purpose, and they certainly did not (especially since inference models are way easier to train than generative models).

    • sexual_tomato@lemmy.dbzer0.comEnglish
      4·
      10 hours ago

      A generative model uses the classifier as part of its training. If you generate a picture of pure random noise, then iteratively pick random noise that the classifier says “looks” more like csam, then you can effectively generate images that the classifier says it’s 100% certain is csam. Whether or not that looks anything like what a human would consider to be csam depends on other factors but it remains a possibility.

      • Todd Bonzalez@lemm.eeEnglish
        2·
        7 hours ago

        You are describing the way deepdream works, not the way modern Diffusion models work. It’s the difference between psychedelic dog faces and a highly adherent generative image of a German Sheppard.

        I can’t imagine you’re going to get anything out of this model that actually looks like CSAM, unless there’s some sort of breakthrough in using these models for previously unrealized generative purposes.