this post was submitted on 06 Sep 2024
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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

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[–] rainynight65@feddit.org 30 points 7 months ago* (last edited 7 months ago) (2 children)

Generative AI is not 'influenced' by other people's work the way humans are. A human musician might spend years covering songs they like and copying or emulating the style, until they find their own style, which may or may not be a blend of their influences, but crucially, they will usually add something. AI does not do that. The idea that AI functions the same as human artists, by absorbing influences and producing their own result, is not only fundamentally false, it is dangerously misleading. To portray it as 'not unethical' is even more misleading.

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[–] knighthawk0811@lemmy.one -4 points 7 months ago

don't human artists also learn by looking at copyrighted material? one of us is missing something

[–] intensely_human@lemm.ee -1 points 7 months ago (1 children)

The push to require paying to read content that is shared openly on the web is designed to drive a feasibility wedge between large and small operations.

It means that a small handful of organizations will actually have the funds to be able to buy enough training data, and that all other smaller AI ventures will be illegal.

This is designed to concentrate AI power into a few hands.

Think critically about the narratives being fed to you. AIs must be allowed to read the web, because if they are not then we will have a unipolar AI ecosystem and the future of humanity will be extremely dark.

We need a multipolar AI ecosystem and the only way to do that is to have lots of small players making their own AI.

If we have a multipolar AI ecosystem, then AI will be forced to play nice because of the effects of parity, and therefore AI will develop along a prosocial, negotiating, respectful path.

Unipolar AI will be tyrannical, cruel, and evil. Unipolar AI will be the result of making it illegal to train AI on web content.

Please see past the propagandistic narrative. Today it is OpenAI that is fighting for this right. Tomorrow it will be smaller players. That is a good thing. That is what we want.

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[–] knF@lemmy.world 17 points 7 months ago (1 children)

This process is akin to how humans learn by reading widely and absorbing styles and techniques, rather than memorizing and reproducing exact passages.

Many people quote this part saying that this is not the case and this is the main reason why the argument is not valid.

Let's take a step back and not put in discussion how current "AI" learns vs how human learn.

The key point for me here is that humans DO PAY (or at least are expected to...) to use and learn from copyrighted material. So if we're equating "AI" method of learning with humans', both should be subject to the the same rules and regulations. Meaning that "AI" should pay for using copyrighted material.

[–] fruitycoder@sh.itjust.works 7 points 7 months ago (1 children)

Do we expect people to pay to learn from copyrighted but freely accessible works?

[–] hamsterkill@lemmy.sdf.org 6 points 7 months ago* (last edited 7 months ago) (9 children)

In general — yes. Most of the time they do so by subjecting their eyeballs or ears to ads. Do you think it's a good idea to flood AI models with ads as well?

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[–] schnurrito@discuss.tchncs.de 13 points 7 months ago (1 children)

I've been thinking since my early teens if not earlier that copyright is an outdated law in the digital age. If this dispute leads to more people realizing this, good.

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[–] sentientity@lemm.ee 49 points 7 months ago* (last edited 7 months ago)

Disagree. These companies are exploiting an unfair power dynamic they created that people can't say no to, to make an ungodly amount of money for themselves without compensating people whose data they took without telling them. They are not creating a cool creative project that collaboratively comments on or remixes what other people have made, they are seeking to gobble up and render irrelevant everything that they can, for short term greed. That's not the scenario these laws were made for. AI hurts people who have already been exploited and industries that have already been decimated. Copyright laws were not written with this kind of thing in mind. There are potentially cool and ethical uses for AI models, but open ai and google are just greed machines.

Edited * THRICE because spelling. oof.

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