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
“This process is akin to how humans learn… The AI discards the original text, keeping only abstract representations…”
Now I sail the high seas myself, but I don’t think Paramount Studios would buy anyone’s defence they were only pirating their movies so they can learn the general content so they can produce their own knockoff.
Yes artists learn and inspire each other, but more often than not I’d imagine they consumed that art in an ethical way.
Now I sail the high seas myself, but I don’t think Paramount Studios would buy anyone’s defence they were only pirating their movies so they can learn the general content so they can produce their own knockoff.
However, Paramount, itself, does pirate content specifically to learn its content so it can produce its own knockoff. As do all the other major studios.
No one engages in IP enforcement in good faith, or respects the IP of others if they can find benefit in circumventing it.
That’s part of the problem. None of the key stakeholders (other than the biggest stakeholder, the public) are interested in preserving the interests of the creators, artists and developers, rather are interested in boosting their own profit gains.
Which makes this not about big companies stealing from human art but from IP property of their own kin.
Yes, Generative AI very much does borrow liberally from the work of human creatives. But those artists mostly signed away their rights long ago to their publishing house masters. Since the ownership class controlled the presses, those contracts were far from fair.
Artists, today, routinely see their art stolen by their own publishing houses at length, and it’s embittering and soul-crushing. We’ve seen Hollywood accounting come into play throughout the last century. Famous actors are notoriously cheated out of residuals. (With the rise of the internet, and prior to that a few smart agents, we’ve seen a small but growing number of — usually pirate-friendly — exceptions.)
The artists were screwed long before AI ever came around.
Instead this fight is about IP-holding companies slugging it out with big computing companies, a kaiju match that is likely to leave Tokyo (that is, the rest of us, creators and consumers alike) in ruin. But we’re already in squalor, anyway.
We don’t know exactly how they source their data (and that is definitely shady), but if I can gain access to a movie in a legal way, I don’t see why I would not be able to gather statistics from said movie, including running a speech to text model to caption it, then make statistics of how many times a few words were used, and followed by which ones. This is an oversimplified explanation of what a LLM does, but it’s the fairest I can come up, and it would be legal to do so. The models are always orders of magnitude smaller than the data they are trained on.
That said, I don’t imply that I’m happy with the state of high tech companies, the AI hype, the energy consumption, or the impact on the humble people. But I’ve put a lot of thought into this (and learning about machine learning for real), and I think this is not a ML problem, but a problem in the economic, legal and political system. AI hype is just a symptom.