7 ms·

There are really significant, novel copyright issues implicated by these large generative models trained on other people’s IP. If you take a step back, you can

There are really significant, novel copyright issues implicated by these large generative models trained on other people’s IP. If you take a step back, you can see that there are different ways to frame what is happening. One frame is: “Defendant built an algorithm that memorized features of Plaintiff’s IP. Defendant’s algorithm recombines parts of those features in order to produce works in the same domain that compete with Plaintiff’s work, all without Plaintiff’s consent.” Bear in mind that copyright holders are among the most litigious out there. If generative art becomes as big a deal as some people expect, they will have every incentive to use their huge litigation budgets to claim a piece of the action. Because the law develops very slowly, the legal process has not yet had the occasion to really evaluate what transformative use means in this novel context. I’m personally interested in seeing where things go, but it’s going to be a while before we know where the law is headed.

klipt 4y ago
> “Defendant built an algorithm that memorized features of Plaintiff’s IP. Defendant’s algorithm recombines parts of those features in order to produce works in the same domain that compete with Plaintiff’s work, all without Plaintiff’s consent.” The fun part is, this is how human artists learn too.
- throwaway1851 4y ago
  They absolutely do. What they don’t do is mechanistically clone compressed mathematical representations of input data. The human part of the creative process could very well be a distinguishing feature, legally.
  - nilsbunger 4y ago
    It will be hard to tell whether an image was created by a “human creative process” or AI. Will the same image be legal if a human made it but not if it was created by Stable Diffusion? How will someone even know, short of a legal discovery process?
    - ipaddr 4y ago
      The watermark.
      - LewisVerstappen 4y ago
        It's extremely trivial to remove the watermark.
      - simonw 4y ago
        What watermark? The model is open source and free for people to make their own modifications. I don't see how any watermark can survive in those conditions.
        jyrkesh 4y ago
        https://news.ycombinator.com/item?id=32573523 https://news.ycombinator.com/item?id=32573523 All this is super, super interesting to me. I don't think anybody really knows how it will play out, there's a lot of good arguments floating around.
        ipaddr 4y ago
        All images from stable diffusion have an invisible watermark unless you modify the source to remove it.
    - throwaway1851 4y ago
      I wouldn’t be too surprised if tools are created to quantify the amount of a source image that’s gone into an output image.
    - tommos0 4y ago
      Someone will create some AI that detects if the image contains stuff from their copyrighted portfolio
    - PeterisP 4y ago
      A legal discovery process is a perfectly reasonable (and common) way to determine if something is legal, and yes, it's completely unsurprising that the exact same outcome might be legal or illegal depending on how it was obtained (or even with what intent the actions were done), legality takes these things into account.
  - t-3 4y ago
    Tracing and collage both mechanistically clone elements of the input. Trendfollowing, mimicry, and copying others is standard in any creative area. I don't think computer-generated works will be easily distinguishable from human unless they're desired to be or shipped with metadata. It's already hard enough to distinguish human artists from other human artists without having names attached up front.
    - mellavora 4y ago
      > Tracing and collage both mechanistically clone elements of the input. Yes, and tracing counts as art fraud. Collage is a bit different, because you are mixing many clones of many other objects such that you create a new object; additionally the way you assemble the clones may transform them (a photo of the mona lisa has different surface texture than a painted version, even more different if it is clipped from newsprint), but while the borders of this are not clear, it is clear when people are far enough over the border. Think of hip-hop, sampling, and remixing music, and some of the legal battles which have come out of that.
      - throwaway6977 4y ago
        > Yes, and tracing counts as art fraud. I just spit out my coffee, turns out I'm not a bad artist, I'm actually a fraudster!
  - kergonath 4y ago
    They can (and do) clone compressed electrical representations of everything they see. Everything is just stored in memories in their brains instead of memory on the cloud. In the case of these complex AI, you cannot really extract the initial works, right? They have all been atomised, mashed together, and very imperfectly encoded as weights and parameters. Yeah I am sure a lot of lawyers are going to have a lot of fun arguing every way imaginable.
    - throwaway1851 4y ago
      I see this type of reduction again and again to advocate for one position or another relating to ML. Human consciousness and thought processes aren’t “just” anything (math, electrical impulses, etc.) — the fact is, we don’t know what the brain really does and how it’s connected to our conscious experience, or even what that is! Deep learning is very powerful and impressive in its applications to date. However, it’s so saturated with hype (and humans are so prone to anthropomorphizing things) that it’s often viewed as something much more profound than it actually is. Neural networks, despite their name, don’t model the brain. And they lack a whole array of “intelligence” features that humans possess and use constantly. All of this is to say that there are very significant differences between computer algorithms and human cognition, and I tend to think the legal system will be unpersuaded by arguments that ignore those differences. Also, this is to say nothing of the public policy interests that shape the law. Regardless of what’s “under the hood,” the law can simply treat human and machine output differently. I’m not a copyright lawyer, of course, so I can’t speak to the norms or technicalities of copyright law itself.
      - kergonath 4y ago
        > Human consciousness and thought processes aren’t “just” anything (math, electrical impulses, etc.) — the fact is, we don’t know what the brain really does and how it’s connected to our conscious experience, or even what that is! There are a lot of things we don’t know, but it is not magic. There is no discussion that artificial neurones don’t have much in common with the real ones, which are very non-linear and much more connected. But in the end it’s all electrochemistry. > Neural networks, despite their name, don’t model the brain. But that’s not directly related to my point. My point that even in the case of a ML model, you cannot get an exact reproduction any more than you can get from a human’s memory. In one case it’s scrambled somewhere in someone’s brain, in the other on a hard drive but the difference is not really relevant. Subjecting an AI’s production to the copyrights of all the things it’s been exposed to is very similar to subjecting a painter’s production to the copyrights of all the painting they have seen.
  - solumunus 4y ago
    I fail to see how the brain isn't doing a very similar thing?
    - noobermin 4y ago
      Is my brain's floating point calculations subject to round off error? In the (actual) neurons, is there a representation of real numbers? Where are the numbers in the brain stored? I feel like people who assert this neither understand what neural networks are and how brains work.
      - selestify 4y ago
        > Is my brain's floating point calculations subject to round off error? > > In the (actual) neurons, is there a representation of real numbers? Where are the numbers in the brain stored? None of these details are relevant to the bigger picture similarities of non-hardcoded learning from training data. None of these details change the ethics of what's being discussed here. > I feel like people who assert this neither understand what neural networks are and how brains work. That's just your bias showing.
  - taneq 4y ago
    > What they don’t do is mechanistically clone compressed mathematical representations of input data. Don’t they, though? What else do you think is behind the curtain if not mathematics?
- peoplefromibiza 4y ago
  > The fun part is, this is how human artists learn too. We don't actually know exactly how human artists learn, and human artists are capable of innovation, nobody knew pointillism or Bauhaus before they were invented. A little know fact is that for humans it takes a long long time to learn, while they learn, they develop a style, if they don't they are not "real" artists, but merely executors, artists evolve, sometimes dramatically, in unexpected ways [1] [2]. So for us humans learning is an experience, not just recombining parts of features of other things. We are also highly influenced by feelings, unfortunately, so sometimes we do things a certain way because we felt that way, not because we wanted to paint that thing that way, or because we are not good enough to do exactly what we wanted to do. Is Mona Lisa happy? Who can tell? Was Leonardo happy when he painted it? What was Leonardo thinking when he painted it? What was happening in his life? Is that the best smile Leonardo could paint or it's an enigma he put there for future generations? These questions are more important for an artist than the mere features of the painting. The philosophical question is: is art discovered or invented? If it's discovered, then SD can generate art, if it's invented, than SD it's not even generative work, because to invent something from something else, you need inventiveness. [1] Picasso 1896 https://mymodernmet.com/wp/wp-content/uploads/2018/01/pablo-picasso-periods-3.jpg https://mymodernmet.com/wp/wp-content/uploads/2018/01/pablo-... [2] Picasso 1946 https://www.photo.rmn.fr/CorexDoc/RMN/Media/TR1/MS4GY/16-515528.jpg https://www.photo.rmn.fr/CorexDoc/RMN/Media/TR1/MS4GY/16-515...
thewanderer1983 4y ago
Artist today use the exact same method of learning from other peoples artwork to generate new artwork and styles. These models are learning just like any artist learns and then producing new content.
- trention 4y ago
  Even if that's true (which it isn't), it doesn't matter. It's absolutely logically consistent to allow humans to do it while forbidding AI to do it.
  - astrange 4y ago
    The problem is forbidding it won’t do much. - It appears people can train AIs from scratch or at least fine-tune them at home. - Even if your art isn’t in “the training set”, that does not prevent the AI from learning its style. (Someone can decode it to CLIP embeddings. It could have a really good text model trained on vivid art museum descriptions of your art.) - The ability of an image model to generate your art means it could also be trained in reverse to recognize it, producing a caption model, which would give vision to the blind. And surely you’d feel bad about that.
    - trention 4y ago
      If you forbid it, the investment in developing those models disappears. They will be stuck at ~what we have now at best. You can also require cloud providers to enforce a ban on training (and deploying) such models, it's doable. Good luck training it in your basement, it will probably take you a decade. If this is banned, it will become a lot like piracy - yes, it's available, no, most people (at least in the West) don't do it, practically no businesses do it.
      - astrange 4y ago
        Training these models is much much cheaper than you think it is, and there’s good data for it already. Either use a CC0 set like Wikimedia/Flickr and throw in some dead artists like Brueghel, or train on data from a country we don’t respect the IP of. Lots of Taobao product photos out there. It’s enough.
mellavora 4y ago
How about if I use Stable Diffusion, running 24/7 on a massive set of parallel clusters, and file for IP protection on all of the resulting images? What potentially human-creatable images have I just taken ownership of? Let's extend: what if I claim IP ownership of every image which StableDiffusion could produce?
- dodobirdlord 4y ago
  The main reason is that you can’t, because only a work produced by a human is eligible for copyright. For example, it has previously been litigated that nobody has IP ownership of an image taken with a camera by an animal.

klipt 4y ago

> “Defendant built an algorithm that memorized features of Plaintiff’s IP. Defendant’s algorithm recombines parts of those features in order to produce works in the same domain that compete with Plaintiff’s work, all without Plaintiff’s consent.” The fun part is, this is how human artists learn too.

throwaway1851 4y ago
They absolutely do. What they don’t do is mechanistically clone compressed mathematical representations of input data. The human part of the creative process could very well be a distinguishing feature, legally.
- nilsbunger 4y ago
  It will be hard to tell whether an image was created by a “human creative process” or AI. Will the same image be legal if a human made it but not if it was created by Stable Diffusion? How will someone even know, short of a legal discovery process?
  - ipaddr 4y ago
    The watermark.
    - LewisVerstappen 4y ago
      It's extremely trivial to remove the watermark.
    - simonw 4y ago
      What watermark? The model is open source and free for people to make their own modifications. I don't see how any watermark can survive in those conditions.
      - jyrkesh 4y ago
        https://news.ycombinator.com/item?id=32573523 https://news.ycombinator.com/item?id=32573523 All this is super, super interesting to me. I don't think anybody really knows how it will play out, there's a lot of good arguments floating around.
      - ipaddr 4y ago
        All images from stable diffusion have an invisible watermark unless you modify the source to remove it.
  - throwaway1851 4y ago
    I wouldn’t be too surprised if tools are created to quantify the amount of a source image that’s gone into an output image.
  - tommos0 4y ago
    Someone will create some AI that detects if the image contains stuff from their copyrighted portfolio
  - PeterisP 4y ago
    A legal discovery process is a perfectly reasonable (and common) way to determine if something is legal, and yes, it's completely unsurprising that the exact same outcome might be legal or illegal depending on how it was obtained (or even with what intent the actions were done), legality takes these things into account.
- t-3 4y ago
  Tracing and collage both mechanistically clone elements of the input. Trendfollowing, mimicry, and copying others is standard in any creative area. I don't think computer-generated works will be easily distinguishable from human unless they're desired to be or shipped with metadata. It's already hard enough to distinguish human artists from other human artists without having names attached up front.
  - mellavora 4y ago
    > Tracing and collage both mechanistically clone elements of the input. Yes, and tracing counts as art fraud. Collage is a bit different, because you are mixing many clones of many other objects such that you create a new object; additionally the way you assemble the clones may transform them (a photo of the mona lisa has different surface texture than a painted version, even more different if it is clipped from newsprint), but while the borders of this are not clear, it is clear when people are far enough over the border. Think of hip-hop, sampling, and remixing music, and some of the legal battles which have come out of that.
    - throwaway6977 4y ago
      > Yes, and tracing counts as art fraud. I just spit out my coffee, turns out I'm not a bad artist, I'm actually a fraudster!
- kergonath 4y ago
  They can (and do) clone compressed electrical representations of everything they see. Everything is just stored in memories in their brains instead of memory on the cloud. In the case of these complex AI, you cannot really extract the initial works, right? They have all been atomised, mashed together, and very imperfectly encoded as weights and parameters. Yeah I am sure a lot of lawyers are going to have a lot of fun arguing every way imaginable.
  - throwaway1851 4y ago
    I see this type of reduction again and again to advocate for one position or another relating to ML. Human consciousness and thought processes aren’t “just” anything (math, electrical impulses, etc.) — the fact is, we don’t know what the brain really does and how it’s connected to our conscious experience, or even what that is! Deep learning is very powerful and impressive in its applications to date. However, it’s so saturated with hype (and humans are so prone to anthropomorphizing things) that it’s often viewed as something much more profound than it actually is. Neural networks, despite their name, don’t model the brain. And they lack a whole array of “intelligence” features that humans possess and use constantly. All of this is to say that there are very significant differences between computer algorithms and human cognition, and I tend to think the legal system will be unpersuaded by arguments that ignore those differences. Also, this is to say nothing of the public policy interests that shape the law. Regardless of what’s “under the hood,” the law can simply treat human and machine output differently. I’m not a copyright lawyer, of course, so I can’t speak to the norms or technicalities of copyright law itself.
    - kergonath 4y ago
      > Human consciousness and thought processes aren’t “just” anything (math, electrical impulses, etc.) — the fact is, we don’t know what the brain really does and how it’s connected to our conscious experience, or even what that is! There are a lot of things we don’t know, but it is not magic. There is no discussion that artificial neurones don’t have much in common with the real ones, which are very non-linear and much more connected. But in the end it’s all electrochemistry. > Neural networks, despite their name, don’t model the brain. But that’s not directly related to my point. My point that even in the case of a ML model, you cannot get an exact reproduction any more than you can get from a human’s memory. In one case it’s scrambled somewhere in someone’s brain, in the other on a hard drive but the difference is not really relevant. Subjecting an AI’s production to the copyrights of all the things it’s been exposed to is very similar to subjecting a painter’s production to the copyrights of all the painting they have seen.
- solumunus 4y ago
  I fail to see how the brain isn't doing a very similar thing?
  - noobermin 4y ago
    Is my brain's floating point calculations subject to round off error? In the (actual) neurons, is there a representation of real numbers? Where are the numbers in the brain stored? I feel like people who assert this neither understand what neural networks are and how brains work.
    - selestify 4y ago
      > Is my brain's floating point calculations subject to round off error? > > In the (actual) neurons, is there a representation of real numbers? Where are the numbers in the brain stored? None of these details are relevant to the bigger picture similarities of non-hardcoded learning from training data. None of these details change the ethics of what's being discussed here. > I feel like people who assert this neither understand what neural networks are and how brains work. That's just your bias showing.
- taneq 4y ago
  > What they don’t do is mechanistically clone compressed mathematical representations of input data. Don’t they, though? What else do you think is behind the curtain if not mathematics?
peoplefromibiza 4y ago
> The fun part is, this is how human artists learn too. We don't actually know exactly how human artists learn, and human artists are capable of innovation, nobody knew pointillism or Bauhaus before they were invented. A little know fact is that for humans it takes a long long time to learn, while they learn, they develop a style, if they don't they are not "real" artists, but merely executors, artists evolve, sometimes dramatically, in unexpected ways [1] [2]. So for us humans learning is an experience, not just recombining parts of features of other things. We are also highly influenced by feelings, unfortunately, so sometimes we do things a certain way because we felt that way, not because we wanted to paint that thing that way, or because we are not good enough to do exactly what we wanted to do. Is Mona Lisa happy? Who can tell? Was Leonardo happy when he painted it? What was Leonardo thinking when he painted it? What was happening in his life? Is that the best smile Leonardo could paint or it's an enigma he put there for future generations? These questions are more important for an artist than the mere features of the painting. The philosophical question is: is art discovered or invented? If it's discovered, then SD can generate art, if it's invented, than SD it's not even generative work, because to invent something from something else, you need inventiveness. [1] Picasso 1896 https://mymodernmet.com/wp/wp-content/uploads/2018/01/pablo-picasso-periods-3.jpg https://mymodernmet.com/wp/wp-content/uploads/2018/01/pablo-... [2] Picasso 1946 https://www.photo.rmn.fr/CorexDoc/RMN/Media/TR1/MS4GY/16-515528.jpg https://www.photo.rmn.fr/CorexDoc/RMN/Media/TR1/MS4GY/16-515...

thewanderer1983 4y ago

Artist today use the exact same method of learning from other peoples artwork to generate new artwork and styles. These models are learning just like any artist learns and then producing new content.

trention 4y ago
Even if that's true (which it isn't), it doesn't matter. It's absolutely logically consistent to allow humans to do it while forbidding AI to do it.
- astrange 4y ago
  The problem is forbidding it won’t do much. - It appears people can train AIs from scratch or at least fine-tune them at home. - Even if your art isn’t in “the training set”, that does not prevent the AI from learning its style. (Someone can decode it to CLIP embeddings. It could have a really good text model trained on vivid art museum descriptions of your art.) - The ability of an image model to generate your art means it could also be trained in reverse to recognize it, producing a caption model, which would give vision to the blind. And surely you’d feel bad about that.
  - trention 4y ago
    If you forbid it, the investment in developing those models disappears. They will be stuck at ~what we have now at best. You can also require cloud providers to enforce a ban on training (and deploying) such models, it's doable. Good luck training it in your basement, it will probably take you a decade. If this is banned, it will become a lot like piracy - yes, it's available, no, most people (at least in the West) don't do it, practically no businesses do it.
    - astrange 4y ago
      Training these models is much much cheaper than you think it is, and there’s good data for it already. Either use a CC0 set like Wikimedia/Flickr and throw in some dead artists like Brueghel, or train on data from a country we don’t respect the IP of. Lots of Taobao product photos out there. It’s enough.

mellavora 4y ago

How about if I use Stable Diffusion, running 24/7 on a massive set of parallel clusters, and file for IP protection on all of the resulting images? What potentially human-creatable images have I just taken ownership of? Let's extend: what if I claim IP ownership of every image which StableDiffusion could produce?

dodobirdlord 4y ago
The main reason is that you can’t, because only a work produced by a human is eligible for copyright. For example, it has previously been litigated that nobody has IP ownership of an image taken with a camera by an animal.