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Every time the argument about how Stable Diffusion models haven't copied anything but have instead “learned” by “seeing”, and generated work is “inspired by” th

Every time the argument about how Stable Diffusion models haven't copied anything but have instead “learned” by “seeing”, and generated work is “inspired by” that learning, I can’t help but feel that proponents of that argument are falling into an anthropomorphization trap. These words all provide a reference point to help humans understand the technology, but regardless of any apparent similarities, SD does not “see” the way humans see, or become “inspired” the way humans are inspired. I suspect that if humans had the ability to operate on billions of images to systematically gain “inspiration”, the state of copyright law and rules around fair use would not look the way they do today. The fact that artists are all on a relatively level playing field, innate talents notwithstanding, seems at the core of the historical precedents set by artists drawing inspiration from each other. I’d argue that generative AI isn’t adding a new player to that game, but altering that game entirely. All of the more simplistic analogies seem similar to claiming that automobiles are really the same as bicycles, just faster. Except automobiles resulted in major shifts in both behavior and policy, and there’s a reason people don’t ride bicycles on the autobahn. Generative AI is transformative and exciting tech, but we need to stop pretending it’s human, if only because it’s important that policy makers don’t see this technology as human-like intelligence. That argument may benefit ethically questionable models in the short term, but seems legitimately dangerous when considering other emerging AI use cases and the possibility that AIs will be handling decision making for critical systems in the near future.

lern_too_spel 4y ago
They're arguing that Stable Diffusion doesn't violate copyright law, so Getty doesn't have a case. You seem to be saying that existing copyright law is no longer sufficient. You're talking past each other.
stuckinhell 4y ago
You are right. Also corporations don't care about "fairness" or people. My megacorp sees our AI has an upcoming "secret sauce"/"edge" for our platform. They have sued companies in the past just to stall them, while we work on competing features and I expect them to do the same again. AI is going to be a major competitive edge for corporations, and lawfare between Winners and Losers will be intense. I say corporations because I don't think normal people will have the capital to train AI's or even run them. The difference between midjourney and stable diffusion is great example to look at these days. Midjourney is making waves things like 80's movie shrek and skyrim.
ImprobableTruth 4y ago
Are you saying that these systems are just copying? Do you think the avocado chair is a copy and that nothing learning-esque occurred? >claiming that automobiles are really the same as bicycles, just faster. Except automobiles resulted in major shifts in both behavior and policy, and there’s a reason people don’t ride bicycles on the autobahn. But speed (and weight) is the key difference. If cars were just really fast and heavy bikes, would anything change? I don't think so. It's purely quantitative, rather than qualitative. It might be that the quantitative differences make generative systems harmful (though I'm not convinced), but that's not substantiated by claims about it not actually being learning.
- haswell 4y ago
  > Are you saying that these systems are just copying? Do you think the avocado chair is a copy and that nothing learning-esque occurred? No, I think it’s neither copying nor learning in the traditional sense, but something fundamentally new, and that’s the crux of the issue. My argument is that we need to treat this as what it is: a transformative piece of software, but software nonetheless. Not some entity that should be afforded human-like status when examining the ethical questions that naturally arise. > But speed (and weight) is the key difference. If cars were just really fast and heavy bikes, would anything change? I don't think so. It's purely quantitative, rather than qualitative. Those are two key differences, but there are a myriad more, each with implications that highlight the difference, e.g. theoretical range, fuel, safety, capacity, etc. The point there is less about drawing a perfect parallel with AIs and more to point out that the category of automobile introduces a whole slew of considerations that must be accounted for to ensure safe operation alongside bicycles, horse drawn carriages and pedestrians. As a thought experiment, I think it’s interesting to consider how one might justify photographing or photocopying original works using a similar line of thinking. “This new scanner/copier sees a piece of artwork and re-draws it on your behalf, and is just a more efficient form of tracing.” Most people would find this description problematic, but seem to accept a similar form of this when examining AI primarily because the AI software is also able to generate new output. I’m not claiming that AI is similar to a photo copier, but I am advocating for a more honest conversation about what it is/is not. I think that looking at past advancements that shattered all established norms at the time is an interesting way to test how one feels about such massive advances. Nuclear energy, firearms, radio, photography, etc. have all had similarly seismic impact.
Auracle 4y ago
I understand what you're saying, but I have to say that Stable Diffusion (and other competitors) struggles with hands, feet, and to a lesser extent faces. Those are the same things that human artists struggle with. It's not a technological brain, but IMO it's the closest we've come. While the models themselves don't become inspired, you tell it what to take inspiration from in the same way that you'd decide "I want to make a drawing/photograph like ____ but different by doing ____."
- haswell 4y ago
  Is there any evidence that the reasons Stable Diffusion struggles with these things resembles the reasons humans struggle with these things? It seems like another case of recognizing an apparent pattern and anthropomorphizing it. Would it not be just as likely that such technical gaps are just a reflection of human limitations, not some inherent property? > It's not a technological brain, but IMO it's the closest we've come. This may be the case, but “the closest we’ve come” seems like a weak argument for anthropomorphizing that progress, especially when you look at how far the gap still is to human-like consciousness.
  - Auracle 4y ago
    Faces are probably because they're full of detail and humans are great at telling if there's something 'wrong' with a face. Hands and feet are probably due to intricacy, which to me seems more like the same issue that humans would have. Again, I'm not arguing that it's intelligent, just that it's...close. I'm not so sure that the gap to human-like consciousness is all that far anymore. If you were to somehow make one of these models more general instead of just text or images and instead "train" it the same way a human child gets trained I'm not entirely sure we'd be able to tell the difference. Obviously we aren't there yet, but the rapid advances these past few years makes it feel like it might at least happen in my lifetime.
- renox 4y ago
  I think you're mistaken: often AI don't get the numbers of hand or digits right.. I don't think humans have any difficulties coming with the correct number of hand or digits, drawing them yes but not the number.
fdye 4y ago
So I think you are likely correct on it being something new. However, I still think its fair use. A thought experiment. Lets say I have an idea for a picture I want. I would like a teddy bear that is in the style of H.R. Giger. I a human write the prompt "style: h.r. giger, a teddy bear" and plug it into Stable Diffusion. I then generate 1000 images, it takes say an hour, and then I pick the one I like. Now the counter example for our experiment. I have the same idea. I go to my community college and learn to draw (lets say I'm decently talented). I goto a book store, buy a book of H.R. Giger's art. Study that book and try to replicate it, eventually can do a passable copy. I then find a teddy bear, possibly also copyrighted. Then finally draw my teddy bear in the style of H.R. Giger. Now I dont think most people would say the second example violates any laws and is fair use. You cannot copyright a style (although some lawsuits are moving forward for rap flow) to my knowledge. Yes I would be ridiculed by the art community as derivative. Its unlikely to end up in the Louvre, but could probably be put on a shirt and sold or whatever with minimal legal risk. So why does the first example feel different then the second? I think it comes back to the process. I would describe them both as the same process but everything after the 'idea' and writing the prompt is just 'steps'. Yes they are steps we attach value to, such as learning to draw, and talent. But ultimately, the real creative thing was the 'idea'. Another parallel we've experienced has kind of shown us the way. When the first spreadsheet came out it was very much a similar process. However, we don't see it as so as numbers generally aren't seen as creative expression. Never the less there was a desire to calculate someones net profits or whatever. Previously, there was large amounts of accountants, I'm sure with tribal knowledge about how to get this done using a bunch of chalkboards and double checking their work. Most trained on this and knew how to do this fastidiously. Then spreadsheets were invented and it saved them a ton of time. The tribal knowledge was not needed. Even a lay person who had a need to calculate 'net profits' could do that with a fraction of the work prior. Final thought, if producing derivative works based on previous art becomes trivial. Then wont the artists who can actually create original works be far more valuable, if immediately copied? Perhaps a lot of the concern of this moment is artists seeing how much of what they produce, and actually sells, is really derivative to begin with...
- anonymouskimmer 4y ago
  Copyrights exist as an incentive for humans to bring new works into being. They are not incentives to use any particular tools to bring those new works into being. In my opinion, under this rubric, the extent a computer-generated work can be copyrighted (or be seen as transformational enough to be fair use) would depend on the amount of effort a human put into iterating that specific piece of work. And even then whether or not Andy Warhol's paintings are copyrightable, or are unauthorized copies of copyrighted work, is still going through the courts. > When the first spreadsheet came out it was very much a similar process. Processes have never been copyrightable. A particular implementation can be patented, but copyright is an entirely different form of intellectual property.

lern_too_spel 4y ago

They're arguing that Stable Diffusion doesn't violate copyright law, so Getty doesn't have a case. You seem to be saying that existing copyright law is no longer sufficient. You're talking past each other.

stuckinhell 4y ago

You are right. Also corporations don't care about "fairness" or people. My megacorp sees our AI has an upcoming "secret sauce"/"edge" for our platform. They have sued companies in the past just to stall them, while we work on competing features and I expect them to do the same again. AI is going to be a major competitive edge for corporations, and lawfare between Winners and Losers will be intense. I say corporations because I don't think normal people will have the capital to train AI's or even run them. The difference between midjourney and stable diffusion is great example to look at these days. Midjourney is making waves things like 80's movie shrek and skyrim.

ImprobableTruth 4y ago

Are you saying that these systems are just copying? Do you think the avocado chair is a copy and that nothing learning-esque occurred? >claiming that automobiles are really the same as bicycles, just faster. Except automobiles resulted in major shifts in both behavior and policy, and there’s a reason people don’t ride bicycles on the autobahn. But speed (and weight) is the key difference. If cars were just really fast and heavy bikes, would anything change? I don't think so. It's purely quantitative, rather than qualitative. It might be that the quantitative differences make generative systems harmful (though I'm not convinced), but that's not substantiated by claims about it not actually being learning.

haswell 4y ago
> Are you saying that these systems are just copying? Do you think the avocado chair is a copy and that nothing learning-esque occurred? No, I think it’s neither copying nor learning in the traditional sense, but something fundamentally new, and that’s the crux of the issue. My argument is that we need to treat this as what it is: a transformative piece of software, but software nonetheless. Not some entity that should be afforded human-like status when examining the ethical questions that naturally arise. > But speed (and weight) is the key difference. If cars were just really fast and heavy bikes, would anything change? I don't think so. It's purely quantitative, rather than qualitative. Those are two key differences, but there are a myriad more, each with implications that highlight the difference, e.g. theoretical range, fuel, safety, capacity, etc. The point there is less about drawing a perfect parallel with AIs and more to point out that the category of automobile introduces a whole slew of considerations that must be accounted for to ensure safe operation alongside bicycles, horse drawn carriages and pedestrians. As a thought experiment, I think it’s interesting to consider how one might justify photographing or photocopying original works using a similar line of thinking. “This new scanner/copier sees a piece of artwork and re-draws it on your behalf, and is just a more efficient form of tracing.” Most people would find this description problematic, but seem to accept a similar form of this when examining AI primarily because the AI software is also able to generate new output. I’m not claiming that AI is similar to a photo copier, but I am advocating for a more honest conversation about what it is/is not. I think that looking at past advancements that shattered all established norms at the time is an interesting way to test how one feels about such massive advances. Nuclear energy, firearms, radio, photography, etc. have all had similarly seismic impact.

Auracle 4y ago

I understand what you're saying, but I have to say that Stable Diffusion (and other competitors) struggles with hands, feet, and to a lesser extent faces. Those are the same things that human artists struggle with. It's not a technological brain, but IMO it's the closest we've come. While the models themselves don't become inspired, you tell it what to take inspiration from in the same way that you'd decide "I want to make a drawing/photograph like ____ but different by doing ____."

haswell 4y ago
Is there any evidence that the reasons Stable Diffusion struggles with these things resembles the reasons humans struggle with these things? It seems like another case of recognizing an apparent pattern and anthropomorphizing it. Would it not be just as likely that such technical gaps are just a reflection of human limitations, not some inherent property? > It's not a technological brain, but IMO it's the closest we've come. This may be the case, but “the closest we’ve come” seems like a weak argument for anthropomorphizing that progress, especially when you look at how far the gap still is to human-like consciousness.
- Auracle 4y ago
  Faces are probably because they're full of detail and humans are great at telling if there's something 'wrong' with a face. Hands and feet are probably due to intricacy, which to me seems more like the same issue that humans would have. Again, I'm not arguing that it's intelligent, just that it's...close. I'm not so sure that the gap to human-like consciousness is all that far anymore. If you were to somehow make one of these models more general instead of just text or images and instead "train" it the same way a human child gets trained I'm not entirely sure we'd be able to tell the difference. Obviously we aren't there yet, but the rapid advances these past few years makes it feel like it might at least happen in my lifetime.
renox 4y ago
I think you're mistaken: often AI don't get the numbers of hand or digits right.. I don't think humans have any difficulties coming with the correct number of hand or digits, drawing them yes but not the number.

fdye 4y ago

So I think you are likely correct on it being something new. However, I still think its fair use. A thought experiment. Lets say I have an idea for a picture I want. I would like a teddy bear that is in the style of H.R. Giger. I a human write the prompt "style: h.r. giger, a teddy bear" and plug it into Stable Diffusion. I then generate 1000 images, it takes say an hour, and then I pick the one I like. Now the counter example for our experiment. I have the same idea. I go to my community college and learn to draw (lets say I'm decently talented). I goto a book store, buy a book of H.R. Giger's art. Study that book and try to replicate it, eventually can do a passable copy. I then find a teddy bear, possibly also copyrighted. Then finally draw my teddy bear in the style of H.R. Giger. Now I dont think most people would say the second example violates any laws and is fair use. You cannot copyright a style (although some lawsuits are moving forward for rap flow) to my knowledge. Yes I would be ridiculed by the art community as derivative. Its unlikely to end up in the Louvre, but could probably be put on a shirt and sold or whatever with minimal legal risk. So why does the first example feel different then the second? I think it comes back to the process. I would describe them both as the same process but everything after the 'idea' and writing the prompt is just 'steps'. Yes they are steps we attach value to, such as learning to draw, and talent. But ultimately, the real creative thing was the 'idea'. Another parallel we've experienced has kind of shown us the way. When the first spreadsheet came out it was very much a similar process. However, we don't see it as so as numbers generally aren't seen as creative expression. Never the less there was a desire to calculate someones net profits or whatever. Previously, there was large amounts of accountants, I'm sure with tribal knowledge about how to get this done using a bunch of chalkboards and double checking their work. Most trained on this and knew how to do this fastidiously. Then spreadsheets were invented and it saved them a ton of time. The tribal knowledge was not needed. Even a lay person who had a need to calculate 'net profits' could do that with a fraction of the work prior. Final thought, if producing derivative works based on previous art becomes trivial. Then wont the artists who can actually create original works be far more valuable, if immediately copied? Perhaps a lot of the concern of this moment is artists seeing how much of what they produce, and actually sells, is really derivative to begin with...

anonymouskimmer 4y ago
Copyrights exist as an incentive for humans to bring new works into being. They are not incentives to use any particular tools to bring those new works into being. In my opinion, under this rubric, the extent a computer-generated work can be copyrighted (or be seen as transformational enough to be fair use) would depend on the amount of effort a human put into iterating that specific piece of work. And even then whether or not Andy Warhol's paintings are copyrightable, or are unauthorized copies of copyrighted work, is still going through the courts. > When the first spreadsheet came out it was very much a similar process. Processes have never been copyrightable. A particular implementation can be patented, but copyright is an entirely different form of intellectual property.