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
We are human beings. The comparison is false on it's face because what you all are calling AI isn't in any conceivable way comparable to the complexity and versatility of a human mind, yet you continue to spit this lie out, over and over again, trying to play it up like it's Data from Star Trek.
This model isn't "learning" anything in any way that is even remotely like how humans learn. You are deliberately simplifying the complexity of the human brain to make that comparison.
Moreover, human beings make their own choices, they aren't actual tools.
They pointed a tool at copyrighted works and told it to copy, do some math, and regurgitate it. What the AI "does" is not relevant, what the people that programmed it told it to do with that copyrighted information is what matters.
There is no intelligence here except theirs. There is no intent here except theirs.
I do think the complexity of artificial neural networks is overstated. A real neuron is a lot more complex than an artificial one, and real neurons are not simply feed forward like ANNs (which have to be because they are trained using back-propagation), but instead have their own spontaneous activity (which kinda implies that real neural networks don't learn using stochastic gradient descent with back-propagation). But to say that there's nothing at all comparable between the way humans learn and the way ANNs learn is wrong IMO.
If you read books such as V.S. Ramachandran and Sandra Blakeslee's Phantoms in the Brain or Oliver Sacks' The Man Who Mistook His Wife For a Hat you will see lots of descriptions of patients with anosognosia brought on by brain injury. These are people who, for example, are unable to see but also incapable of recognizing this inability. If you ask them to describe what they see in front of them they will make something up on the spot (in a process called confabulation) and not realize they've done it. They'll tell you what they've made up while believing that they're telling the truth. (Vision is just one example, anosognosia can manifest in many different cognitive domains).
It is V.S Ramachandran's belief that there are two processes that occur in the Brain, a confabulator (or "yes man" so to speak) and an anomaly detector (or "critic"). The yes-man's job is to offer up explanations for sensory input that fit within the existing mental model of the world, whereas the critic's job is to advocate for changing the world-model to fit the sensory input. In patients with anosognosia something has gone wrong in the connection between the critic and the yes man in a particular cognitive domain, and as a result the yes-man is the only one doing any work. Even in a healthy brain you can see the effects of the interplay between these two processes, such as with the placebo effect and in hallucinations brought on by sensory deprivation.
I think ANNs in general and LLMs in particular are similar to the yes-man process, but lack a critic to go along with it.
What implications does that have on copyright law? I don't know. Real neurons in a petri dish have already been trained to play games like DOOM and control the yoke of a simulated airplane. If they were trained instead to somehow draw pictures what would the legal implications of that be?
There's a belief that laws and political systems are derived from some sort of deep philosophical insight, but I think most of the time they're really just whatever works in practice. So, what I'm trying to say is that we can just agree that what OpenAI does is bad and should be illegal without having to come up with a moral imperative that forces us to ban it.
If you fundamentally do not think that artificial intelligences can be created, the onus is on yo uto explain why it's impossible to replicate the circuitry of our brains. Everything in science we've seen this far has shown that we are merely physical beings that can be recreated physically.
Otherwise, I asked you to examine a thought experiment where you are trying to build an artificial intelligence, not necessarily an LLM.
Or you are over complicating yourself to seem more important and special. Definitely no way that most people would be biased towards that, is there?
Oh please do go ahead and show us your proof that free will exists! Thank god you finally solved that one! I heard people were really stressing about it for a while!
"I don't know how this works but it's math and that scares me so I'll minimize it!"
If we have an AI that's equivalent to humanity in capability of learning and creative output/transformation, it would be immoral to just use it as a tool. At least that's how I see it.
I think that's a huge risk, but we've only ever seen a single, very specific type of intelligence, our own / that of animals that are pretty closely related to us.
Movies like Ex Machina and Her do a good job of pointing out that there is nothing that inherently means that an AI will be anything like us, even if they can appear that way or pass at tasks.
It's entirely possible that we could develop an AI that was so specifically trained that it would provide the best script editing notes but be incapable of anything else for instance, including self reflection or feeling loss.