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
If ChatGPT was free I might see their point but it’s not so no. If you’re making money from someone’s work you should pay them.
You’re making an indie movie on your iPhone with friends. You sell one ticket. You now owe: Apple, Joseph Nicéphore Niépce’s estate (inventor of the camera), every cinematographer who first devised the type of shots you’re using, the writers since the beginning of time that created the types of story elements in the script, the mathematicians and scientists that developed lense technology, the car manufacturers that aided your ability to transport you to the set, the guy who’s YouTube tutorial you watched to figure out lighting, etc, etc, etc.
Your black and white framing appears to provide a clear ethical framework until you dig a millimeter into it. The reality is that society only exists because of the work that all of the individuals within it produce. Things like copyright are an adapter to our capitalistic economy to ensure people’s work that can be copied, are protected enough that they have the opportunity to make money off of it. It exists so somebody else can’t immediately turn around and sell the same book someone else wrote, or just change a few words and do as such. This protection was meant to last 15 to 20 years. Then enter the public domain for anyone to copy and rewrite as they please.
Current copyright is an utter bastardization of its intended use. Massive corporations are trying to act like they’re fighting for the little guy to own their IP forever. But they buy up all that IP for pennies compared to how they turn around and commoditize it. Then they own all of what society produces in perpetuity. They can sit on their dragon hoards and laugh as they gobble up any new creation that strays too close. And people wonder why everything is a sequel of a sequel of a sequel owned by massive corporations.
I was trying to keep it simple.
I would have paid them by purchasing the iphone and whatever software I used. I paid for the car that transported me. I would have paid for my education. People can also give their work away for free if they want, or be compensated by ads as in the case of Youtube or FOSS.
Current copyright is an utter bastardization of its intended use. Massive corporations are trying to act like they’re fighting for the little guy to own their IP forever. But they buy up all that IP for pennies compared to how they turn around and commoditize it. Then they own all of what society produces in perpetuity. They can sit on their dragon hoards and laugh as they gobble up any new creation that strays too close. And people wonder why everything is a sequel of a sequel of a sequel owned by massive corporations.
What do you think ChatGPT is trying to do? It’s already being used to churn out shitloads of garbage content. They’re not making things better.
By that rationalization, OpenAI is paying their Internet bill, and for a copy of Dune, so they’re free to use any content they acquired to make their product better. Your original argument wasn’t akin to, “Shouldn’t someone using an iPhone pay for one?” It was “Shouldn’t Apple get a cut of everything made with the iPhone?”
You could make the argument that people use ChatGPT to churn out garbage content, sure, but a lot of cinephiles would accuse your proverbial indie movie of being the same and blame Apple for creating the iPhone and enabling it. If you want to make that argument, go ahead. But don’t pretend it has anything to do with people getting paid fairly for what they made.
ChatGPT is enabling people to make more things, easier, to get paid. And people, as always, are relying on everything that was created before them as a basis for their work. Same as when I go to school and the professor shows me lots of different works to learn from. The thousands of students in that class didn’t pay for any of that stuff. The professor distilled it and presented it and I paid him to do it.
The problem is that they didn’t pay for the content they’ve acquired and they’re selling it to others. The creators are not being compensated and may not want to participate in AI development at all. If the creators agree to it then fine but most do not. Just look at what’s happening with art. People are scraping all of an artists work to create AI pictures in their style and impersonate them. That’s not okay.
Here’s an experiment for you to try at home. Ask an AI model a question, copy a sentence or two of what they give back, and paste it into a search engine. The results may surprise you.
And stop comparing AI to humans but then giving AI models more freedom. If I wrote a paper I’d need to cite my sources. Where the fuck are your sources ChatGPT? Oh right, we’re not allowed to see that but you can take whatever you want from us. Sounds fair.
Did the experiment.
Zero shock factor. It showed an empty google search result. I have screenshots for the deniers. I don’t know what you think will happen, but unless you’re asking it some super vague question, where the answer would be unanimous across the board, it’s not going to spit out some shock factor quote that you can google. What a waste of an ‘experiment’.
Can you just give us the TLDE?
AI Chat bots copy/paste much of their “training data” verbatim.
Not to fully argue against your point, but I do want to push back on the citations bit. Given the way an LLM is trained, it’s not really close to equivalent to me citing papers researched for a paper. That would be more akin to asking me to cite every piece of written or verbal media I’ve ever encountered as they all contributed in some small way to way that the words were formulated here.
Now, if specific data were injected into the prompt, or maybe if it was fine-tuned on a small subset of highly specific data, I would agree those should be cited as they are being accessed more verbatim. The whole “magic” of LLMs was that it needed to cross a threshold of data, combined with the attentional mechanism, and then the network was pretty suddenly able to maintain coherent sentences structure. It was only with loads of varied data from many different sources that this really emerged.
It’s not a breach of copyright or other IP law not to cite sources on your paper.
Getting your paper rejected for lacking sources is also not infringing in your freedom. Being forced to pay damages and delete your paper from any public space would be infringement of your freedom.
I mean, you’re not necessarily wrong. But that doesn’t change the fact that it’s still stealing, which was my point. Just because laws haven’t caught up to it yet doesn’t make it any less of a shitty thing to do.
Look… All I have to say is… Support the Internet Archive!
(please)
If they can base their business on stealing, then we can steal their AI services, right?
Pirating isn’t stealing but yes the collective works of humanity should belong to humanity, not some slimy cabal of venture capitalists.
Yes, that’s exactly the point. It should belong to humanity, which means that anyone can use it to improve themselves. Or to create something nice for themselves or others. That’s exactly what AI companies are doing. And because it is not stealing, it is all still there for anyone else. Unless, of course, the copyrightists get there way.
How do you feel about Meta and Microsoft who do the same thing but publish their models open source for anyone to use?
Well how long to you think that’s going to last? They are for-profit companies after all.
Those aren’t open source, neither by the OSI’s Open Source Definition nor by the OSI’s Open Source AI Definition.
The important part for the latter being a published listing of all the training data. (Trainers don’t have to provide the data, but they must provide at least a way to recreate the model given the same inputs).
Data information: Sufficiently detailed information about the data used to train the system, so that a skilled person can recreate a substantially equivalent system using the same or similar data. Data information shall be made available with licenses that comply with the Open Source Definition.
They are model-available if anything.
For the purposes of this conversation. That’s pretty much just a pedantic difference. They are paying to train those models and then providing them to the public to use completely freely in any way they want.
It would be like developing open source software and then not calling it open source because you didn’t publish the market research that guided your UX decisions.
You said open source. Open source is a type of licensure.
The entire point of licensure is legal pedantry.
And as far as your metaphor is concerned, pre-trained models are closer to pre-compiled binaries, which are expressly not considered Open Source according to the OSD.
You said open source. Open source is a type of licensure.
The entire point of licensure is legal pedantry.
No. Open source is a concept. That concept also has pedantic legal definitions, but the concept itself is not inherently pedantic.
And as far as your metaphor is concerned, pre-trained models are closer to pre-compiled binaries, which are expressly not considered Open Source according to the OSD.
No, they’re not. Which is why I didn’t use that metaphor.
A binary is explicitly a black box. There is nothing to learn from a binary, unless you explicitly decompile it back into source code.
In this case, literally all the source code is available. Any researcher can read through their model, learn from it, copy it, twist it, and build their own version of it wholesale. Not providing the training data, is more similar to saying that Yuzu or an emulator isn’t open source because it doesn’t provide copyrighted games. It is providing literally all of the parts of it that it can open source, and then letting the user feed it whatever training data they are allowed access to.
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{{labeling it “theft” is both legally and technically inaccurate.}} Well, my understanding is that humans have intelligence, humans teach and learn from previous/other people’s work and make progressive or create new work/idea using their own intelligence. AI/machine doesn’t have intelligence from the start, doesn’t have own intelligence to create/make things. It just copies, remixes, and applies the knowledge, and many personalities and all expressions have been teached. So “theft” is technically accurate.
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.
I absolutely would download a car.
I’ll train my AI on just the bee movie. Then I’m going to ask it “can you make me a movie about bees”? When it spits the whole movie, I can just watch it or sell it or whatever, it was a creation of my AI, which learned just like any human would! Of course I didn’t even pay for the original copy to train my AI, it’s for learning purposes, and learning should be a basic human right!
Ai has ideas? That’s a bit of a philosophical stretch.
The argument that these models learn in a way that’s similar to how humans do is absolutely false, and the idea that they discard their training data and produce new content is demonstrably incorrect. These models can and do regurgitate their training data, including copyrighted characters.
And these things don’t learn styles, techniques, or concepts. They effectively learn statistical averages and patterns and collage them together. I’ve gotten to the point where I can guess what model of image generator was used based on the same repeated mistakes that they make every time. Take a look at any generated image, and you won’t be able to identify where a light source is because the shadows come from all different directions. These things don’t understand the concept of a shadow or lighting, they just know that statistically lighter pixels are followed by darker pixels of the same hue and that some places have collections of lighter pixels. I recently heard about an ai that scientists had trained to identify pictures of wolves that was working with incredible accuracy. When they went in to figure out how it was identifying wolves from dogs like huskies so well, they found that it wasn’t even looking at the wolves at all. 100% of the images of wolves in its training data had snowy backgrounds, so it was simply searching for concentrations of white pixels (and therefore snow) in the image to determine whether or not a picture was of wolves or not.
Even if they learned exactly like humans do, like so fucking what, right!? Humans have to pay EXORBITANT fees for higher education in this country. Arguing that your bot gets socialized education before the people do is fucking absurd.
That seems more like an argument for free higher education rather than restricting what corpuses a deep learning model can train on
Tomato, tomato…
This process is akin to how humans learn by reading widely and absorbing styles and techniques, rather than memorizing and reproducing exact passages.
Like fuck it is. An LLM “learns” by memorization and by breaking down training data into their component tokens, then calculating the weight between these tokens. This allows it to produce an output that resembles (but may or may not perfectly replicate) its training dataset, but produces no actual understanding or meaning–in other words, there’s no actual intelligence, just really, really fancy fuzzy math.
Meanwhile, a human learns by memorizing training data, but also by parsing the underlying meaning and breaking it down into the underlying concepts, and then by applying and testing those concepts, and mastering them through practice and repetition. Where an LLM would learn “2+2 = 4” by ingesting tens or hundreds of thousands of instances of the string “2+2 = 4” and calculating a strong relationship between the tokens “2+2,” “=,” and “4,” a human child would learn 2+2 = 4 by being given two apple slices, putting them down to another pair of apple slices, and counting the total number of apple slices to see that they now have 4 slices. (And then being given a treat of delicious apple slices.)
Similarly, a human learns to draw by starting with basic shapes, then moving on to anatomy, studying light and shadow, shading, and color theory, all the while applying each new concept to their work, and developing muscle memory to allow them to more easily draw the lines and shapes that they combine to form a whole picture. A human may learn off other peoples’ drawings during the process, but at most they may process a few thousand images. Meanwhile, an LLM learns to “draw” by ingesting millions of images–without obtaining the permission of the person or organization that created those images–and then breaking those images down to their component tokens, and calculating weights between those tokens. There’s about as much similarity between how an LLM “learns” compared to human learning as there is between my cat and my refrigerator.
And YET FUCKING AGAIN, here’s the fucking Google Books argument. To repeat: Google Books used a minimal portion of the copyrighted works, and was not building a service to compete with book publishers. Generative AI is using the ENTIRE COPYRIGHTED WORK for its training set, and is building a service TO DIRECTLY COMPETE WITH THE ORGANIZATIONS WHOSE WORKS THEY ARE USING. They have zero fucking relevance to one another as far as claims of fair use. I am sick and fucking tired of hearing about Google Books.
EDIT: I want to make another point: I’ve commissioned artists for work multiple times, featuring characters that I designed myself. And pretty much every time I have, the art they make for me comes with multiple restrictions: for example, they grant me a license to post it on my own art gallery, and they grant me permission to use portions of the art for non-commercial uses (e.g. cropping a portion out to use as a profile pic or avatar). But they all explicitly forbid me from using the work I commissioned for commercial purposes–in other words, I cannot slap the art I commissioned on a T-shirt and sell it at a convention, or make a mug out of it. If I did so, that artist would be well within their rights to sue the crap out of me, and artists charge several times as much to grant a license for commercial use.
In other words, there is already well-established precedent that even if something is publicly available on the Internet and free to download, there are acceptable and unacceptable use cases, and it’s broadly accepted that using other peoples’ work for commercial use without compensating them is not permitted, even if I directly paid someone to create that work myself.
So, is the Internet caring about copyright now? Decades of Napster, Limewire, BitTorrent, Piratebay, bootleg ebooks, movies, music, etc, but we care now because it’s a big corporation doing it?
Just trying to get it straight.
Personally for me its about the double standard. When we perform small scale “theft” to experience things we’d be willing to pay for if we could afford it and the money funded the artists, they throw the book at us. When they build a giant machine that takes all of our work and turns it into an automated record scratcher that they will profit off of and replace our creative jobs with, that’s just good business. I don’t think it’s okay that they get to do things like implement DRM because IP theft is so terrible, but then when they do it systemically and against the specific licensing of the content that has been posted to the internet, that’s protected in the eyes of the law
What about companies who scrape public sites for training data but then publish their trained models open source for anyone to use?
That feels a lot more reasonable and fair to me personally.
If they still profit from it, no.
Open models made by nonprofit organisations, listing their sources, not including anything from anyone who requests it not to be included (with robots.txt, for instance), and burdened with a GPL-like viral license that prevents the models and their results from being used for profit… that’d probably be fine.
And also be useless for most practical applications.
We’re talking about LLMs. They’re useless for most practical applications by definition.
And when they’re not entirely useless (basically, autocomplete) they’re orders of magnitude less cost-effective than older almost equivalent alternatives, so they’re effectively useless at that, too.
They’re fancy extremely costly toys without any practical use, that thanks to the short-sighted greed of the scammers selling them will soon become even more useless due to model collapse.
The Internet is not a person
People on Lemmy. I personally didn’t realize everyone here was such big fans of copyright and artificial scarcity.
The reality is that people hate tech bros (deservedly) and then blindly hate on everything they like by association, which sometimes results in dumbassery like everyone now dick-riding the copyright system.
The reality is that people hate the corporations using creative peoples works to try and make their jobs basically obsolete and they grab onto anything to fight against it, even if it’s a bit of a stretch.
I’d hate a world lacking real human creativity.
I don’t think LLMs should be taken down, it would be impossible for that to happen. I do, however think it should be forced into open source.
This is the only way. These companies are essentially asking for a free license for themselves while everyone else must pay.
“Copyright for thee but not for me.”
Will your warez be legal after you wrap them in an AI model, or only if you are a big, greedy, invasive, tech company?
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There is an easy answer to this, but it’s not being pursued by AI companies because it’ll make them less money, albeit totally ethically.
Make all LLM models free to use, regardless of sophistication, and be collaborative with sharing the algorithms. They don’t have to be open to everyone, but they can look at requests and grant them on merit without charging for it.
So how do they make money? How goes Google search make money? Advertisements. If you have a good, free product, advertisement space will follow. If it’s impossible to make an AI product while also properly compensating people for training material, then don’t make it a sold product. Use copyright training material freely to offer a free product with no premiums.
I don’t currently have a computer powerful enough to host a top tier LLM like chatgpt4. If I can’t even run it, I sure as shit could never continue to train it with new data. I often use chatgpt with my phone and the thought of doing either one is ridiculous.
There are ways to make money on open source outside of the open source item itself. Redhat has done just that with Linux.
An LLM is just software. No matter what algorithm, tool, or fairy magic was used to amalgamate the data it consumed, they all sucked in open source code and just like any other software that includes open source software, it should be subject to the licensing on the open source software, which pretty much means they should be open source themselves. Companies that want to make money off of AI trained on public data can make their money on the value they add, just like redhat.
The biggest issue I see right now is how to deal with AIs tendency to output data untransformed. Trademark and all those types of licenses are negated as long as the idea within is transformed, but it is really hard to argue transformation when the stupid thing is pooping out word for word quotes, but acting as if it is “new” and transformed.
