Those claiming AI training on copyrighted works is “theft” misunderstand key aspects of copyright law and AI technology. Copyright protects specific expressions of ideas, not the ideas themselves. When AI systems ingest copyrighted works, they’re extracting general patterns and concepts - the “Bob Dylan-ness” or “Hemingway-ness” - not copying specific text or images.

This process is akin to how humans learn by reading widely and absorbing styles and techniques, rather than memorizing and reproducing exact passages. The AI discards the original text, keeping only abstract representations in “vector space”. When generating new content, the AI isn’t recreating copyrighted works, but producing new expressions inspired by the concepts it’s learned.

This is fundamentally different from copying a book or song. It’s more like the long-standing artistic tradition of being influenced by others’ work. The law has always recognized that ideas themselves can’t be owned - only particular expressions of them.

Moreover, there’s precedent for this kind of use being considered “transformative” and thus fair use. The Google Books project, which scanned millions of books to create a searchable index, was ruled legal despite protests from authors and publishers. AI training is arguably even more transformative.

While it’s understandable that creators feel uneasy about this new technology, labeling it “theft” is both legally and technically inaccurate. We may need new ways to support and compensate creators in the AI age, but that doesn’t make the current use of copyrighted works for AI training illegal or unethical.

For those interested, this argument is nicely laid out by Damien Riehl in FLOSS Weekly episode 744. https://twit.tv/shows/floss-weekly/episodes/744

  • @calcopiritus
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    210 days ago

    Don’t need to get philosophical about what is the difference between human and AI learning.

    “Consumed by AI” and “consumed by a human” are two distinct use cases that can have different terms in a license.

    • @[email protected]
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      110 days ago

      Why do we need to differentiate those two use cases, anyway? It’s not like they differentiate between a single human or multiple humans consuming the content, or if there are non-humans also consuming it. Differentiating those two use cases is just another example of publishers wanting more money due to greed. I’m not sure why Lemmy is so supportive of that.

      • @calcopiritus
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        010 days ago

        We need to differentiate between those cases because they are 2 distinct cases. And they are very different.

        They don’t even have the same purpose. The purpose of a human learning is: fulfill a desire to learn or acquiring a new skill that will be useful to fulfill another desire. The purpose of AI learning is: increase the value of the model so it can be sold for more.

        Lemmy is not an entity that is capable of thought. And I’m not Lemmy. I’m just another person and what you are reading is my opinion.

        “Publishers are bad and greedy, therefore everything that hurts them is good for society” is a childish take imo. Not everything is black and white. Copyright exists for a reason. Just removing it won’t make the world better. A law being flawed doesn’t make it worse than not existing.