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Artists score major win in copyright case against AI art generators

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Re: Artists score major win in copyright case against AI art generators

#71

Post by Workaccount2 »

p1necone wrote: post #42
reactor wrote: post #38

Humans acquire a significant amount of knowledge (or get trained on) by learning from the work of others. If companies can face legal repercussions for training models on materials from elsewhere, a similar argument could be made for individuals.

This argument seems ridiculous to me but it's hard to explain exactly why. People are people, LLMs are... not people - it seems pretty obvious to me that humans learning from seeing things is a basic fact of nature, and that someone feeding petabytes of copyrighted material into an AI model to fully automate generation of art is obviously copyright infringement. I can see the argument making more sense if we actually…

>and that someone feeding petabytes of copyrighted material into an AI model to fully automate generation of art is obviously copyright infringement.

It becomes a little less obvious when you learn that the models which had petabytes of images "go into it" are You have 5 million artists on one hand saying "My art is in there being used" and you have a 10GB file full of matrix vectors saying "There are no image files in here" on the other. Both are kind of right. ish. sort of.

Re: Artists score major win in copyright case against AI art generators

#72

Post by doctorpangloss »

davexunit wrote: post #59

It's so obvious to me that machine learning models are derivative works of their training set. If they weren't, then why would these companies fight so hard to say otherwise? They need that training data to make their product, so they should pay the licensing fees for it! 10 years ago, when I worked on a machine learning model for my employer, it was unthinkable to train on data we did not have the rights to use. But…

> It's so obvious to me that machine learning models are derivative works of their training set.

Okay, but narrative creators watch movies and listen to music and read books too. Many do indeed "file the serial numbers off" other people's work and publish something else, that makes them money and not the original creators. Does one instance of "filing the serial numbers off" by one author mean that no authors anywhere are allowed to write any books as soon as they've read "a bunch" of other books? I get what you are saying, but it's not so obvious what the right policy is. It is very hard to make it consistent when "AI" is substituted with "human," and it's not so obvious if "AI" is a distinct class from human, because it is after all, something that only exists because a programmer somewhere wrote and operated it.

Re: Artists score major win in copyright case against AI art generators

#73

Post by archontes »

aabajian wrote: post #48

IANAL. Is it legal to create derivatives of copyright work and then post them on public online forums? For example, I can certainly write , "Mickey Mouse got food poisoning from his Big Mac." But, if I ask an AI generator to "Make a picture of Mickey Mouse getting food poison at McDonald's", could I post the resulting picture?

I am also not a lawyer; I have some background and training in IP law as it pertains to engineering.

As far as I can tell, the image you describe and your example sentence are closer than you might think to each other. Mickey Mouse is a copyrighted character, and Disney could certainly claim infringement for both. Whether you have a fair use claim is down to the tenets of fair use, and whether they sue you is down to their estimation of how likely it is it'd be profitable for them to do so.

So what is fair use? https://www.law.cornell.edu/uscode/text/17/107

Put simply, you have to argue about it in court and decide on a case by case basis, but the factors are:

The nature of use, such as for profit vs. non-profit.

The nature of the copyrighted work. Your art might be considere literary criticism. How central to that message is Mickey Mouse?

The amount and substantiality of the copyrighted work appearing in your work. Mickey Mouse is the sole feature, so large.

How likely is it that your Mickey Mouse creation will serve as a substitute for people consuming normal Mickey Mouse content?

Re: Artists score major win in copyright case against AI art generators

#74

Post by epoxia »

slavik81 wrote: post #55
coffeecloud wrote: post #40

Earlier quoted context omitted.

To me it sounds like this argument is claiming that "training models" is legally equivalent to "training humans". So are there other examples of a human being allowed to do something where a machine made by a human is not allowed to do that thing? I am allowed to go to a movie and remember every detail and tell it to my friends, but my camcorder is not allowed to do that.

If you redrew The Lion King frame by frame from memory, it would still be copyright infringement if you redistributed it to your friends. The difference is how similar your recreation is to the original, not whether it was done by a human or by a machine.

Funnily enough, The Lion King is a property that has its own controversy of plagiarism of a different animation, Kimba The White Lion. But, I guess if Disney does it it's okay...

Re: Artists score major win in copyright case against AI art generators

#75

Post by 6gvONxR4sf7o »

doctorpangloss wrote: post #2

There are no clean image models. Zero. Using today's model architectures, the problem of using non-expressly-permitted data for training is insurmountable. I welcome anyone more knowledgeable on the matter to go ahead and comment about a counterexample before downvoting. So if the artists prevail, image generators are donezo. Open source, proprietary, whatever. People saying otherwise just don't know enough about how…

> Using today's model architectures, the problem of using non-expressly-permitted data for training is insurmountable… So if the artists prevail, image generators are donezo.

This doesn’t follow. Using 2014’s model architectures, image generators were also impossible, but that didn’t prevent progress. The field is moving absurdly rapidly. Suggesting that because we can’t do it one way today, therefore we can’t to it that way tomorrow is like saying that because we couldn’t do it one way yesterday, therefore we can’t do it that way today.

It’s wild to trample people’s livelihoods because researchers haven’t figured out how not to yet, especially when that kind of research is making such quick progress. I’d rather wait a few years and have the best of both worlds.

Re: Artists score major win in copyright case against AI art generators

#76

Post by paulddraper »

davexunit wrote: post #59

It's so obvious to me that machine learning models are derivative works of their training set. If they weren't, then why would these companies fight so hard to say otherwise? They need that training data to make their product, so they should pay the licensing fees for it! 10 years ago, when I worked on a machine learning model for my employer, it was unthinkable to train on data we did not have the rights to use. But…

Of course they are derivative.

The question is whether they are transformative.

Right or wrong, the bar for transformative use is probably lower than you think.

Artists are the beneficiaries of this, as they can riff on popular works for inspiration, recognizability, social commentary.

Given the existing case law, I don't see a ruling against AI companies as likely.

Re: Artists score major win in copyright case against AI art generators

#77

Post by archontes »

Workaccount2 wrote: post #61
radley wrote: post #54

Earlier quoted context omitted.

The context is generating images based explicitly on intellectual property. The problem is that most AI image generators allow IP as terms and/or they consumed IP to build their model, so they will return IP-based artworks. If you're a business using the image and used IP terms in your prompt, then you'd need permissions from both parties (Disney, McDonald's) before you post it. If you're writing about AI rights, or…

>At least, that's where this is all going. Not really, because that would still be a loss for artists. Where they are trying to steer the ship is to "training on IP is copyright violation". Artists are looking to stop AI from taking their jobs. An AI generator with an IP filter on it's output will still very much be a threat to their work.

I agree that interested parties are trying to steer the ship there. I just don't see the legal arguments that will get them there.

Given the fact that images are transmitted to a person in a manner that doesn't violate copyright (and even if they are, the transmitter, not receiver is guilty of infringement), training an AI is not something that copyright law limits.

The AI weights that result are about the farthest thing from a derivative work, as the weights as a separate object, don't seem to contain the slightest remnant of the original work.

Re: Artists score major win in copyright case against AI art generators

#78

Post by Retric »

doctorpangloss wrote: post #72
davexunit wrote: post #59

It's so obvious to me that machine learning models are derivative works of their training set. If they weren't, then why would these companies fight so hard to say otherwise? They need that training data to make their product, so they should pay the licensing fees for it! 10 years ago, when I worked on a machine learning model for my employer, it was unthinkable to train on data we did not have the rights to use. But…

> It's so obvious to me that machine learning models are derivative works of their training set. Okay, but narrative creators watch movies and listen to music and read books too. Many do indeed "file the serial numbers off" other people's work and publish something else, that makes them money and not the original creators. Does one instance of "filing the serial numbers off" by one author mean that no authors anywher…

The issue here is that the AI model itself is a derivative work.

Further, they will very much recreate things the’ve seen many examples of. Recreating “Mona Lisa” isn’t a problem, but recreating “Iron Man” is. Individual artists may not know how to prompt the system to recreate their work, but looking at the training sets is going to help quite a bit.

Re: Artists score major win in copyright case against AI art generators

#79

Post by [deleted] »

slavik81 wrote: post #55
coffeecloud wrote: post #40

Earlier quoted context omitted.

To me it sounds like this argument is claiming that "training models" is legally equivalent to "training humans". So are there other examples of a human being allowed to do something where a machine made by a human is not allowed to do that thing? I am allowed to go to a movie and remember every detail and tell it to my friends, but my camcorder is not allowed to do that.

If you redrew The Lion King frame by frame from memory, it would still be copyright infringement if you redistributed it to your friends. The difference is how similar your recreation is to the original, not whether it was done by a human or by a machine.

[deleted]

Re: Artists score major win in copyright case against AI art generators

#80

Post by doctorpangloss »

ijk wrote: post #37
doctorpangloss wrote: post #2

There are no clean image models. Zero. Using today's model architectures, the problem of using non-expressly-permitted data for training is insurmountable. I welcome anyone more knowledgeable on the matter to go ahead and comment about a counterexample before downvoting. So if the artists prevail, image generators are donezo. Open source, proprietary, whatever. People saying otherwise just don't know enough about how…

Where are you getting 2 billion from? The original CLIP paper says: > We demonstrate that the simple pre-training task of predicting which caption goes with which image is an efficient and scalable way to learn SOTA image representations from scratch on a dataset of 400 million (image, text) pairs collected from the internet. [1] OpenCLIP was trained on more images, but the datasets like LAION-2B are kind of low-qual…

The 400m images in the paper yield the ~40% zero shot ImageNet accuracy in the chart they publish.

That level of performance is generally not good enough for text conditioning of DDIMs.

The published CLIP checkpoints, and later in the paper, they talk about performance that is almost twice as good at 76.2%. That data point, notably, does not appear in the chart. So the published checkpoints, and the performance they talk about later in the paper, are clearly trained on way more data.

How much data? Let's take a guess. I got the data points from the chart they have, and I went and fit y=a log_⁡b (c+dx) + K to the points in the paper:

    a≈12.31
    b≈0.18
    c≈24.16
    d≈0.81
    K≈−10.47
Then I got 7.55b images to get a performance of 76%. The fit is R^2 = 0.993, I don't have any good intuitions for why this is so high, it could very well be real, and there's no reason to anchor on "7.55b is a lot higher than LAION-4b", although they could just concatenate a social media image dataset of 3b images with LAION-4b, and boom, there's 7b.

OpenCLIP reproduced this work after all with 2b images and got 79.5%. But e.g. Flux and SD3 do not use OpenCLIP's checkpoints. So that one performance figure isn't representative of how bad OpenCLIP's checkpoints are versus how good OpenAI's checkpoints are. It's not straightforward to fit, it's way more than 400m.

Another observation is that there are plenty of Hugging Face spaces with crappy ResNet and crappy small-dataset trained-from-scratch CLIP conditioning to try. Sometimes it actually looks as crappy as Adobe's outputs do, there's a little bit of a chance that Adobe tried and failed to create its own CLIP checkpoint on the crappy amount of data they had.

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