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"All photos included a Creative Commons licenses, but most were not licensed for commercial use." I wonder what the implications are for Stable Diffusion, DALL

"All photos included a Creative Commons licenses, but most were not licensed for commercial use." I wonder what the implications are for Stable Diffusion, DALLE and Midjourney since that art images on the internet are copyrighted by default. Even with a fair use argument, there are examples in cases where AI was generating art that included the signatures of artists. https://nwn.blogs.com/nwn/2022/12/lensa-ai-art-images-without-consent.html https://nwn.blogs.com/nwn/2022/12/lensa-ai-art-images-withou...

ilikehurdles 4y ago
> Stability AI is happy to follow copyright laws for their music model, because they know that music labels will hold them accountable. So this seems like a good time to point out to larger companies like @WaltDisneyCo that their copyrighted material is being stolen and used too I mean this is a pretty good point. If they're so sure this is legal, then train on copyrighted audio+video media as they already do with copyrighted visual media.
- zarzavat 4y ago
  Avoiding doing something because you don't want to get sued and subjected to a lengthy court battle is completely rational and it doesn't mean that doing that thing is illegal. For example, for decades many TV shows came up with their own lyrics for Happy Birthday song, even though it was well known that the song wasn't copyrighted, because nobody wanted to get sued and fight that battle. Easier to just change a few words in the script.
  - int_19h 4y ago
    It's not just legal issues that'll lead to self-regulation. It's also stuff like this: https://imgur.com/a/vAqCUP7 https://imgur.com/a/vAqCUP7
- devalidating 4y ago
  Simply put, there is less information in music. Copyright infringement cases have been won on as little as a handful of notes. So the likelihood of a copyrightable element from the underlying showing up in the model's output is that much higher. A single melody represents a similar portion of all possible melodies as does a color all possible colors and certainly less than the fraction represented by a single color palette. Yet you cannot copyright a color palette but you can a melody. Copyright law regarding audio media is entire different beast than visual media; the case law and fair use technicalities do not always line up as simply as "if its legal on visual media it must also be legal on audio."
gwern 4y ago
This is apples and oranges. SD et al are defended on the grounds of being transformative use (https://en.wikipedia.org/wiki/Transformative_use https://en.wikipedia.org/wiki/Transformative_use): they do not distribute (ie copy) the original training images, and they are not a derivative work due to transformativeness, so the license of the original images is completely irrelevant. (Details like 'signatures' are also irrelevant: if I write a style parody of William Shakespeare and add a '--Willy Shakespeare' at the end to round it off, have I revealed that I have secretly copied his work? Of course not. It's just plausible that there would be a name there, so I came up with a name.) The criticism here is that distributing (copying) the original image violates the non-commercial clause of the original images because someone, somewhere, might somehow have made money in some way because the dataset exists; but as they somewhat lamely acknowledge later, what counts as 'commercial' has never been clearly defined, and it probably can't be defined (because for most people 'commercial' seems to be defined by 'ewww'), and this is why CC-NC licenses are heavily discouraged by WMF and other FLOSS groups and weren't part of FLOSS from the beginning even though Stallman was in large part attacking commercial exploitation.
- schemescape 4y ago
  Does anyone know if attempts have been made to trick these ML models into reproducing original copyrighted inputs verbatim (edit: or close enough)? Edit: Asking about verbatim copies wasn't really a great question. I should have asked about producing things that are "close enough to cause legal trouble" (whether that be due to copyright, trademark, or something else).
  - Scaevolus 4y ago
    That's a known failure mode called "overfitting" or "memorization", where a specific input text is very accurately reproduced. I'm not aware of it occurring for any copyrighted inputs, but it occurs for many famous artworks-- it's nearly impossible to convince Stable Diffusion to style "Mona Lisa" at all.
  - sdenton4 4y ago
    That's not really how memorization in neutral networks works. For classifiers, memorization is more like learning a hash function and a lookup table; no need to store the full image at all. Even for very large models, the weights are a tiny fraction of the size of the original data. It's probably helpful to think of embeddings for generative models in a similar way; it's a very specific embedding function, like a locality sensitive hash, which doesn't require actually storing the data.
polygamous_bat 4y ago
> Even with a fair use argument, there are examples in cases where AI was generating art that included the signatures of artists. I went through the post, and I am not sure whether I agree with the analysis of the examples. Diffusion models are conceptual parrots, and it is possible that "25% images contain a scribble in the bottom right corner, so the model will make a scribble in the corner" is what is being construed as a signature in this post. I think a large part of outrage from the artists about diffusion model "stealing" art comes from a place of disbelief that machines can be this good without "stealing", and it's perfectly natural. In fact, it's unnatural to me how good machines have gotten in image generation, and it is a field I've been following for five years now. However, because I understand the model and can implement it myself, I can convince myself it doesn't need to steal, just needs to be able to model correlations at some ungodly level.
- zowie_vd 4y ago
  >I think a large part of outrage from the artists about diffusion model "stealing" art comes from a place of disbelief that machines can be this good without "stealing" I think when you make machines that automate away some people's passion and purpose in life, of course they're going to be upset. When, on top of that, the machine automating their work is a "conceptual parrot" that is parroting the concepts they invented without their permission, of course they're going to be pissed off. Besides, whilst AI image generators don't steal exact elements from the training data, they do basically steal the artstyles and subject matter of illustrators, which takes them many years to foster. Imagine an illustrator of fantasy book covers hardly being able to find work anymore because some publishers figured out that, instead of hiring him, they could cheaply hire an unskilled person from a third world country to type the illustrator's name into an AI image generator so that it imitates his works, along with a few keywords for the book in question, until eventually something good pops out. That is currently considered fair use in US copyright law, but in my opinion it is nonetheless so unjust that it justifies calling it "stealing".

ilikehurdles 4y ago

> Stability AI is happy to follow copyright laws for their music model, because they know that music labels will hold them accountable. So this seems like a good time to point out to larger companies like @WaltDisneyCo that their copyrighted material is being stolen and used too I mean this is a pretty good point. If they're so sure this is legal, then train on copyrighted audio+video media as they already do with copyrighted visual media.

zarzavat 4y ago
Avoiding doing something because you don't want to get sued and subjected to a lengthy court battle is completely rational and it doesn't mean that doing that thing is illegal. For example, for decades many TV shows came up with their own lyrics for Happy Birthday song, even though it was well known that the song wasn't copyrighted, because nobody wanted to get sued and fight that battle. Easier to just change a few words in the script.
- int_19h 4y ago
  It's not just legal issues that'll lead to self-regulation. It's also stuff like this: https://imgur.com/a/vAqCUP7 https://imgur.com/a/vAqCUP7
devalidating 4y ago
Simply put, there is less information in music. Copyright infringement cases have been won on as little as a handful of notes. So the likelihood of a copyrightable element from the underlying showing up in the model's output is that much higher. A single melody represents a similar portion of all possible melodies as does a color all possible colors and certainly less than the fraction represented by a single color palette. Yet you cannot copyright a color palette but you can a melody. Copyright law regarding audio media is entire different beast than visual media; the case law and fair use technicalities do not always line up as simply as "if its legal on visual media it must also be legal on audio."

gwern 4y ago

This is apples and oranges. SD et al are defended on the grounds of being transformative use (https://en.wikipedia.org/wiki/Transformative_use https://en.wikipedia.org/wiki/Transformative_use): they do not distribute (ie copy) the original training images, and they are not a derivative work due to transformativeness, so the license of the original images is completely irrelevant. (Details like 'signatures' are also irrelevant: if I write a style parody of William Shakespeare and add a '--Willy Shakespeare' at the end to round it off, have I revealed that I have secretly copied his work? Of course not. It's just plausible that there would be a name there, so I came up with a name.) The criticism here is that distributing (copying) the original image violates the non-commercial clause of the original images because someone, somewhere, might somehow have made money in some way because the dataset exists; but as they somewhat lamely acknowledge later, what counts as 'commercial' has never been clearly defined, and it probably can't be defined (because for most people 'commercial' seems to be defined by 'ewww'), and this is why CC-NC licenses are heavily discouraged by WMF and other FLOSS groups and weren't part of FLOSS from the beginning even though Stallman was in large part attacking commercial exploitation.

schemescape 4y ago
Does anyone know if attempts have been made to trick these ML models into reproducing original copyrighted inputs verbatim (edit: or close enough)? Edit: Asking about verbatim copies wasn't really a great question. I should have asked about producing things that are "close enough to cause legal trouble" (whether that be due to copyright, trademark, or something else).
- Scaevolus 4y ago
  That's a known failure mode called "overfitting" or "memorization", where a specific input text is very accurately reproduced. I'm not aware of it occurring for any copyrighted inputs, but it occurs for many famous artworks-- it's nearly impossible to convince Stable Diffusion to style "Mona Lisa" at all.
- sdenton4 4y ago
  That's not really how memorization in neutral networks works. For classifiers, memorization is more like learning a hash function and a lookup table; no need to store the full image at all. Even for very large models, the weights are a tiny fraction of the size of the original data. It's probably helpful to think of embeddings for generative models in a similar way; it's a very specific embedding function, like a locality sensitive hash, which doesn't require actually storing the data.

polygamous_bat 4y ago

> Even with a fair use argument, there are examples in cases where AI was generating art that included the signatures of artists. I went through the post, and I am not sure whether I agree with the analysis of the examples. Diffusion models are conceptual parrots, and it is possible that "25% images contain a scribble in the bottom right corner, so the model will make a scribble in the corner" is what is being construed as a signature in this post. I think a large part of outrage from the artists about diffusion model "stealing" art comes from a place of disbelief that machines can be this good without "stealing", and it's perfectly natural. In fact, it's unnatural to me how good machines have gotten in image generation, and it is a field I've been following for five years now. However, because I understand the model and can implement it myself, I can convince myself it doesn't need to steal, just needs to be able to model correlations at some ungodly level.

zowie_vd 4y ago
>I think a large part of outrage from the artists about diffusion model "stealing" art comes from a place of disbelief that machines can be this good without "stealing" I think when you make machines that automate away some people's passion and purpose in life, of course they're going to be upset. When, on top of that, the machine automating their work is a "conceptual parrot" that is parroting the concepts they invented without their permission, of course they're going to be pissed off. Besides, whilst AI image generators don't steal exact elements from the training data, they do basically steal the artstyles and subject matter of illustrators, which takes them many years to foster. Imagine an illustrator of fantasy book covers hardly being able to find work anymore because some publishers figured out that, instead of hiring him, they could cheaply hire an unskilled person from a third world country to type the illustrator's name into an AI image generator so that it imitates his works, along with a few keywords for the book in question, until eventually something good pops out. That is currently considered fair use in US copyright law, but in my opinion it is nonetheless so unjust that it justifies calling it "stealing".