How is that any different from “stealing” art in a collage, though? While courts have disagreed on the subject (in particular there’s a big difference between visual collage and music sampling with the latter being very restricted) there is a clear argument to be made that collage is a fair use of the original works, because the result is completely different.
Sidestepping the debate about whether AI art is actually fair use, I do find the fair use doctrine an interesting lens to look at the wider issue — in particular, how deciding whether something is fair use is more complex than comparing a case to a straightforward checklist, but a fairly dynamic spectrum.
It’s possible that something could be:
Highly transformative
Takes from a published work that is primarily of a factual nature (such as a biography)
Distributed to a different market than the original work
but still not be considered fair use, if it had used the entirety of the base work without modification (in this case, the “highly transformative” would pertain to how the chunks of the base work are presented)
I’m no lawyer, but I find the theory behind fair use pretty interesting. In practice, it leaves a lot to be desired (the way that YouTube’s contentID infringes on what would almost certainly be fair use, because Google wants to avoid being taken to court by rights holders, so preempts the problem by being overly harsh to potential infringement). However, my broad point is that whether a court decides something is fair use relies on a holistic assessment that considers all four of pillars of fair use, including how strongly each apply.
AI trained off of artist’s works is different to making collage of art because of the scale of the scraping — a huge amount of copyrighted work has been used, and entire works of art were used, even if the processing of them were considered to be transformative (let’s say for the sake of argument that we are saying that training an AI is highly transformative). The pillar that AI runs up against the most though is “the effect of the use upon the potential market”. AI has already had a huge impact on the market for artistic works, and it is having a hugely negative impact on people’s ability to make a living through their art (or other creative endeavours, like writing). What’s more, the companies who are pushing AI are making inordinate amounts of revenue, which makes the whole thing feel especially egregious.
We can draw on the ideas of fair use to understand why so many people feel that AI training is “stealing” art whilst being okay with collage. In particular, it’s useful to ask what the point of fair use is? Why have a fair use exemption to copyright at all? The reason is because one of the purposes of copyright is meant to be to encourage people to make more creative works — if you’re unable to make any money from your efforts because you’re competing with people selling your own work faster than you can, then you’re pretty strongly disincentivised to make anything at all. Fair use is a pragmatic exemption carved out because of the recognition that if copyright is overly restrictive, then it will end up making it disproportionately hard to make new stuff. Fair use is as nebulously defined as it is because it is, in theory, guided by the principle of upholding the spirit of copyright.
Now, I’m not arguing that training an AI (or generating AI art) isn’t fair use — I don’t feel equipped to answer that particular question. As a layperson, it seems like current copyright laws aren’t really working in this digital age we find ourselves in, even before we consider AI. Though perhaps it’s silly to blame computers for this, when copyright wasn’t really helping individual artists much even before computers became commonplace. Some argue that we need new copyright laws to protect against AI, but Cory Doctorow makes a compelling argument about how this will just end up biting artists in the ass even worse than the AI. Copyright probably isn’t the right lever to pull to solve this particular problem, but it’s still a useful thing to consider if we want to understand the shape of the whole problem.
As I see it, copyright exists because we, as a society, said we wanted to encourage people to make stuff, because that enriches society. However, that goal was in tension with the realities of living under capitalism, so we tried to resolve that through copyright laws. Copyright presented new problems, which led to the fair use doctrine, which comes with problems of its own, with or without AI. The reason people consider AI training to be stealing is because they understand AI as a dire threat to the production of creative works, and they attempt to articulate this through the familiar language of copyright. However, that’s a poor framework for addressing the problem that AI art poses though. We would be better to strip this down to the ethical core of it so we can see the actual tension that people are responding to.
Maybe we need a more radical approach to this problem. One interesting suggestion that I’ve seen is that we should scrap copyright entirely and implement a generous universal basic income (UBI) (and other social safety nets). If creatives were free to make things without worrying about fulfilling basic living needs, it would make the problem of AI scraping far lower stakes for individual creatives. One problem with this is that most people would prefer to earn more than what even a generous UBI would provide, so would probably still feel cheated by Generative AI. However, the argument is that GenerativeAI cannot compare to human artists when it comes to producing novel or distinctive art, so the most reliable wa**y to obtain meaningful art would be to give financial support to the artists (especially if an individual is after something of a particular style). I’m not sure how viable this approach would be in practice, but I think that discussing more radical ideas like this is useful in figuring what the heck to do.
I completely agree on pretty much the whole sweep of this. AI just exposes another way in which copyright law is insufficient for the digital age.
On a personal note, a couple of years ago I tried to use chatgpt to write a story. It was shit so I wrote my own. I’ve taken up drawing again and want to properly learn digital painting.
In my mind, AI doesn’t threaten any of this because the enjoyment I get from these things doesn’t depend on selling what I do. Artists have been stereotypically starving for a long time because the innate human desire to create exceeds the desire of people to pay.
Allowing people to satisfy that desire without literally starving should be a societal goal.
Collage art retains the original components of the art, adding layers the viewer can explore and seek the source of, if desired.
VLMs on the other hand intentionally obscure the original works by sending them through filters and computer vision transformations to make the original work difficult to backtrace. This is no accident, its designed obfuscation.
The difference is intent - VLMs literally steal copies of art to generate their work for cynical tech bros. Classical collages take existing art and show it in a new light, with no intent to pass off the original source materials as their own creations.
The original developers of Stable Diffusion and similar models made absolutely no secret about the source data they used. Where are you getting this idea that they “intentionally obscure the original works… to make [them] difficult to backtrace.”? How would an image generation model even work in a way that made the original works obvious?
Literally steal
Copying digital art wasn’t “literally stealing” when the MPAA was suing Napster and it isn’t today.
For cynical tech bros
Stable Diffusion was originally developed by academics working at a University.
Your whole reply is pretending to know intent where none exists, so if that’s the only difference you can find between collage and AI art, it’s not good enough.
Stable Diffusion? The same Stable Diffusion sued by Getty Images which claims they used 12 million of their images without permission? Ah yes very non-secretive very moral. And what of industry titans DALL-E and Midjourney? Both have had multiple examples of artists original art being spat out by their models, simply by finessing the prompts - proving they used particular artists copyright art without those artists permission or knowledge.
Stable Diffusion also was from its inception in the hands of tech bros, funded and built with the help of a $3 billion dollar AI company (Runway AI), and itself owned by Stability AI, a made for profit company presently valued at $1 billion and now has James Cameron on its board. The students who worked on a prior model (Latent Diffusion) were hired for the Stable Diffusion project, that is all.
If they’re taking CC BY-SA and failing to attribute it, then they are also breaking licencing and abusing content for their profit. An VLM could easily add attributes to images to assign source data used in the output - weird none of them want to.
In other words, I’ll continue to treat AI art as the amoral slop it is. You are of course welcome to have a different opinion, I don’t really care if mine is ‘good enough’ for you.
Stable Diffusion? The same Stable Diffusion sued by Getty Images which claims they used 12 million of their images without permission? Ah yes very non-secretive very moral. And what of industry titans DALL-E and Midjourney? Both have had multiple examples of artists original art being spat out by their models, simply by finessing the prompts - proving they used particular artists copyright art without those artists permission or knowledge.
Getting sued means Getty images disagrees that the use of the images was legal, not that it was secret, nor that it was moral. Getty images are included in the LAION-5b dataset that Stability AI publicly stated they used to create Stable Diffusion. So it’s not “intentionally obscuring” as you claimed.
Copying is not theft, no matter how many words you want to write about it. You can steal a painting by taking it off the wall. You can’t steal a JPG by right-clicking it and selecting “Copy Image”. That’s fundamentally different.
An VLM could easily add attributes to images to assign source data used in the output
Oh yeah? Easily? What attribution should a model trained purely on LAION-5b add to an output image if prompted with “photograph of a cat”?
In other words, I’ll continue to treat AI art as the amoral slop it is. You are of course welcome to have a different opinion, I don’t really care if mine is ‘good enough’ for you.
You can do whatever you want (within usual rules) in your personal life, but you chose to enter into a discussion.
From that discussion it’s clear that your position is rooted in bias not knowledge. That’s why you can’t point out substantial differences between AI-generated images and other techniques which re-use existing imagery, why you make up intentions and can’t back them up, and why you prefer to dismiss academics as “tech bros” instead of engaging on facts.
How is that any different from “stealing” art in a collage, though? While courts have disagreed on the subject (in particular there’s a big difference between visual collage and music sampling with the latter being very restricted) there is a clear argument to be made that collage is a fair use of the original works, because the result is completely different.
Sidestepping the debate about whether AI art is actually fair use, I do find the fair use doctrine an interesting lens to look at the wider issue — in particular, how deciding whether something is fair use is more complex than comparing a case to a straightforward checklist, but a fairly dynamic spectrum.
It’s possible that something could be:
I’m no lawyer, but I find the theory behind fair use pretty interesting. In practice, it leaves a lot to be desired (the way that YouTube’s contentID infringes on what would almost certainly be fair use, because Google wants to avoid being taken to court by rights holders, so preempts the problem by being overly harsh to potential infringement). However, my broad point is that whether a court decides something is fair use relies on a holistic assessment that considers all four of pillars of fair use, including how strongly each apply.
AI trained off of artist’s works is different to making collage of art because of the scale of the scraping — a huge amount of copyrighted work has been used, and entire works of art were used, even if the processing of them were considered to be transformative (let’s say for the sake of argument that we are saying that training an AI is highly transformative). The pillar that AI runs up against the most though is “the effect of the use upon the potential market”. AI has already had a huge impact on the market for artistic works, and it is having a hugely negative impact on people’s ability to make a living through their art (or other creative endeavours, like writing). What’s more, the companies who are pushing AI are making inordinate amounts of revenue, which makes the whole thing feel especially egregious.
We can draw on the ideas of fair use to understand why so many people feel that AI training is “stealing” art whilst being okay with collage. In particular, it’s useful to ask what the point of fair use is? Why have a fair use exemption to copyright at all? The reason is because one of the purposes of copyright is meant to be to encourage people to make more creative works — if you’re unable to make any money from your efforts because you’re competing with people selling your own work faster than you can, then you’re pretty strongly disincentivised to make anything at all. Fair use is a pragmatic exemption carved out because of the recognition that if copyright is overly restrictive, then it will end up making it disproportionately hard to make new stuff. Fair use is as nebulously defined as it is because it is, in theory, guided by the principle of upholding the spirit of copyright.
Now, I’m not arguing that training an AI (or generating AI art) isn’t fair use — I don’t feel equipped to answer that particular question. As a layperson, it seems like current copyright laws aren’t really working in this digital age we find ourselves in, even before we consider AI. Though perhaps it’s silly to blame computers for this, when copyright wasn’t really helping individual artists much even before computers became commonplace. Some argue that we need new copyright laws to protect against AI, but Cory Doctorow makes a compelling argument about how this will just end up biting artists in the ass even worse than the AI. Copyright probably isn’t the right lever to pull to solve this particular problem, but it’s still a useful thing to consider if we want to understand the shape of the whole problem.
As I see it, copyright exists because we, as a society, said we wanted to encourage people to make stuff, because that enriches society. However, that goal was in tension with the realities of living under capitalism, so we tried to resolve that through copyright laws. Copyright presented new problems, which led to the fair use doctrine, which comes with problems of its own, with or without AI. The reason people consider AI training to be stealing is because they understand AI as a dire threat to the production of creative works, and they attempt to articulate this through the familiar language of copyright. However, that’s a poor framework for addressing the problem that AI art poses though. We would be better to strip this down to the ethical core of it so we can see the actual tension that people are responding to.
Maybe we need a more radical approach to this problem. One interesting suggestion that I’ve seen is that we should scrap copyright entirely and implement a generous universal basic income (UBI) (and other social safety nets). If creatives were free to make things without worrying about fulfilling basic living needs, it would make the problem of AI scraping far lower stakes for individual creatives. One problem with this is that most people would prefer to earn more than what even a generous UBI would provide, so would probably still feel cheated by Generative AI. However, the argument is that GenerativeAI cannot compare to human artists when it comes to producing novel or distinctive art, so the most reliable wa**y to obtain meaningful art would be to give financial support to the artists (especially if an individual is after something of a particular style). I’m not sure how viable this approach would be in practice, but I think that discussing more radical ideas like this is useful in figuring what the heck to do.
I completely agree on pretty much the whole sweep of this. AI just exposes another way in which copyright law is insufficient for the digital age.
On a personal note, a couple of years ago I tried to use chatgpt to write a story. It was shit so I wrote my own. I’ve taken up drawing again and want to properly learn digital painting.
In my mind, AI doesn’t threaten any of this because the enjoyment I get from these things doesn’t depend on selling what I do. Artists have been stereotypically starving for a long time because the innate human desire to create exceeds the desire of people to pay.
Allowing people to satisfy that desire without literally starving should be a societal goal.
Collage art retains the original components of the art, adding layers the viewer can explore and seek the source of, if desired.
VLMs on the other hand intentionally obscure the original works by sending them through filters and computer vision transformations to make the original work difficult to backtrace. This is no accident, its designed obfuscation.
The difference is intent - VLMs literally steal copies of art to generate their work for cynical tech bros. Classical collages take existing art and show it in a new light, with no intent to pass off the original source materials as their own creations.
The original developers of Stable Diffusion and similar models made absolutely no secret about the source data they used. Where are you getting this idea that they “intentionally obscure the original works… to make [them] difficult to backtrace.”? How would an image generation model even work in a way that made the original works obvious?
Copying digital art wasn’t “literally stealing” when the MPAA was suing Napster and it isn’t today.
Stable Diffusion was originally developed by academics working at a University.
Your whole reply is pretending to know intent where none exists, so if that’s the only difference you can find between collage and AI art, it’s not good enough.
Stable Diffusion? The same Stable Diffusion sued by Getty Images which claims they used 12 million of their images without permission? Ah yes very non-secretive very moral. And what of industry titans DALL-E and Midjourney? Both have had multiple examples of artists original art being spat out by their models, simply by finessing the prompts - proving they used particular artists copyright art without those artists permission or knowledge.
Stable Diffusion also was from its inception in the hands of tech bros, funded and built with the help of a $3 billion dollar AI company (Runway AI), and itself owned by Stability AI, a made for profit company presently valued at $1 billion and now has James Cameron on its board. The students who worked on a prior model (Latent Diffusion) were hired for the Stable Diffusion project, that is all.
I don’t care to drag the discussion into your opinion of whether artists have any ownership of their art the second after they post it on the internet - for me it’s good enough that artists themselves assign licences for their work (CC, CC BY-SA, ©, etc) - and if a billion dollar company is taking their work without permission (as in the © example) to profit off it - that’s stealing according to the artists intent by their own statement.
If they’re taking CC BY-SA and failing to attribute it, then they are also breaking licencing and abusing content for their profit. An VLM could easily add attributes to images to assign source data used in the output - weird none of them want to.
In other words, I’ll continue to treat AI art as the amoral slop it is. You are of course welcome to have a different opinion, I don’t really care if mine is ‘good enough’ for you.
Getting sued means Getty images disagrees that the use of the images was legal, not that it was secret, nor that it was moral. Getty images are included in the LAION-5b dataset that Stability AI publicly stated they used to create Stable Diffusion. So it’s not “intentionally obscuring” as you claimed.
Copying is not theft, no matter how many words you want to write about it. You can steal a painting by taking it off the wall. You can’t steal a JPG by right-clicking it and selecting “Copy Image”. That’s fundamentally different.
Oh yeah? Easily? What attribution should a model trained purely on LAION-5b add to an output image if prompted with “photograph of a cat”?
You can do whatever you want (within usual rules) in your personal life, but you chose to enter into a discussion.
From that discussion it’s clear that your position is rooted in bias not knowledge. That’s why you can’t point out substantial differences between AI-generated images and other techniques which re-use existing imagery, why you make up intentions and can’t back them up, and why you prefer to dismiss academics as “tech bros” instead of engaging on facts.