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submitted 2 months ago by FatCat@lemmy.world to c/technology@lemmy.world

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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[-] LANIK2000@lemmy.world 38 points 2 months ago

This process is akin to how humans learn...

I'm so fucking sick of people saying that. We have no fucking clue how humans LEARN. Aka gather understanding aka how cognition works or what it truly is. On the contrary we can deduce that it probably isn't very close to human memory/learning/cognition/sentience (any other buzzword that are stands-ins for things we don't understand yet), considering human memory is extremely lossy and tends to infer its own bias, as opposed to LLMs that do neither and religiously follow patters to their own fault.

It's quite literally a text prediction machine that started its life as a translator (and still does amazingly at that task), it just happens to turn out that general human language is a very powerful tool all on its own.

I could go on and on as I usually do on lemmy about AI, but your argument is literally "Neural network is theoretically like the nervous system, therefore human", I have no faith in getting through to you people.

[-] ZILtoid1991@lemmy.world 13 points 2 months ago

Even worse is, in order to further humanize machine learning systems, they often give them human-like names.

[-] ulterno@lemmy.kde.social 7 points 2 months ago* (last edited 2 months ago)

Now just if we had all famous people saying stuff like this.
But they won't. Guess why? Because the "won't" is what made them famous (and rich),


Lay people give more heed to those acting from the start, like they have the answers. That's what "charisma" is about.
Also one of the reasons why religion gets easier wins. Because when people hear something that makes them have to think more, they ignore it more.

this post was submitted on 06 Sep 2024
1720 points (90.1% liked)

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