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I know this website is not a hivemind, but it's interesting every time an article like this gets posted the majority opinion seems to be that training diffusion

by cmovq 4y ago

I know this website is not a hivemind, but it's interesting every time an article like this gets posted the majority opinion seems to be that training diffusion models on copyrighted work is totally fine. In contrast when talking about training code generation models there are multiple comments mentioning this is not ok if licenses weren't respected. For anyone who holds both of these opinions, why do you think it's ok to train diffusion models on copyrighted work, but not co-pilot on GPL code?

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benlivengood 4y ago
Humans used to learn to code from copyrighted works (textbooks) without much reference to OSS or Free Software. Similarly, teaching ML models to code from copyrighted works isn't going to violate copyright more frequently than a human might; and detecting exact copies should be pretty easy by comparing with the corpus used to train it. Software houses already have to worry about infringement of snippets, and things like Codex are just one more potential source.
- ipaddr 4y ago
  Those books were purchased and a license granted for such use.
  - lmm 4y ago
    > Those books were purchased Sometimes. People also borrowed them, read them in libraries, or in later years looked at free textbooks online. > and a license granted for such use I never heard of such a thing, and it was never seen as necessary. No student checked the licenses on their textbooks before deciding whether they could read them.
firefoxkekw 4y ago
Cognitive dissonance, different persons, hypocrisy.
pjonesdotca 4y ago
Because the models are not creating a 1:1 replacement of the original work. As mentioned before "style" is not something subject to copyright and the model creates a model of that style. The process of finetuning a model generally means that one would not want to recreate the original images as that would overfit it and render it, essentially useless. When it comes to code, there is a higher chance of getting a one-to-one clone of the input as the options used in creating an algorithm, or even a simple function are dramatically reduced imo.
- mensetmanusman 4y ago
  Code is hundreds to many thousands of lines. A line of code is analogous to one color pixel in digital art.
  - com2kid 4y ago
    Depends on which lines of code. I have written projects where I'd consider a handful of lines of code to be the core central tenant of the entire project that everything else is built up around. Copy those lines and everything else is scaffolding that falls out naturally from the development process.
  - melagonster 4y ago
    but one line similar code is easier to find. this is because copilot work in one line/small function level.
- leereeves 4y ago
  > when it comes to code, there is a higher chance of getting a one-to-one clone of the input. I'm not so sure. There's a generated image in the article that I think looks enough like Wonder Woman to cause a lawsuit. That's just one of a handful of images in the article, and doesn't seem to have been chosen for its similarity to Wonder Woman.
- dwringer 4y ago
  I think when it comes to art, less than one-to-one clones are often still functionally equivalent in the mind of many viewers. Stylistic and thematic content is often just as, if not more, important than the exact composition. But currently the law does agree that this is not copyrightable. And sometimes independent artists profit and make a name for themselves copping other styles, and I think that's great. But could it be considered an intellectual and sociological denial-of-service attack when it's scaled to the point where a machine can crank out dozens of derivative works per minute? I'm not sure this is a situation at all comparable to human artists making derivative works. Those involve long periods of concentration, focus, and reflection by a conscious human agent to pull off, thus in some sense furthering to the intellectual development of humanity and fostering a deeper appreciation for the source work. The machine does none of that; it's sort of just a photocopier one step removed in hyperspace, copying some of the artists' abstractions instead of their brush strokes.
bombcar 4y ago
If I were to steel man both sides it'd be something like this: 1. Training an AI model on code (so far) makes it regurgitate code line-for-line (with comments!). This is like "learning to code" by just cut and pasting working code from other codebases, you have to follow the license. The AI doesn't "understand the algorithm" at all (or it hasn't been told "don't export the input you fool"). Obviously a bog-simple AI could make all licenses moot by dumping out what it input, and the courts wouldn't permit that. 2. Training an AI model on illustrations so far produces "style parodies" which may look similar to an untrained eye (the artist here is annoyed because she'd not art like that, even though to us it looks similar enough). Drawing a picture that looks like Mickey Mouse is a trademark violation, but tracing a picture of the Mouse is both a trademark and a copyright violation. The first violates some pretty clear legal concepts; the second is closer to violating moral concepts but those are more flexible - if an artist spends years learning to paint in the style of Michelangelo is that immoral?
- deleted 4y ago
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- shadowgovt 4y ago
  And perhaps more importantly regarding (1) than simple regurgitation: code does things. There's a real risk that if you just let Copilot emit output without understanding what that output does, it'll do the wrong thing. Art is in the eye of the beholder. If the output looks correct as per what you're looking for, it is correct. There's no additional layer of "Is it saying what I meant it to say" that is relevant to anyone who isn't an art critic.
  - Xelynega 4y ago
    Art is in the eye of the beholder, but it still needs a creator. That creator had a vision in mind that's unique to them because of their experiences, and I think it's wrong to say that this image can be quantified as a location in a abstract feature space. So to say "there is no additional layer [to judge goodness] that is relevant to [most people]" assumes there is an algorithmic measure of "goodness" that can be applied to art, which is an assumption you need to make to believe that there's any similarities with AI generated art and human generated other than "they look kinda similar".
mensetmanusman 4y ago
People often hold conflicting views, they done like to think about it though, because it can lead to cognitive dissonance. That’s one reason why it is probably better to have a derived world view than a contrived world view.
aliqot 4y ago
Your argument is tantamount to expecting Michael Bay to have never seen a Scorcese or deriving influence from it.
- pessimizer 4y ago
  Pretending it's not clearly more complicated than that will not convince anyone, it will make them feel condescended to. While Scorcese is Scorcese, a deep learning model is not Michael Bay.
  - aliqot 4y ago
    I used that comparison on purpose. Michael Bay leans on a lot of computer driven technology to shoot movies inspired by other more traditional directors. The comparison is direct, if you feel condescended to, I did not intend that.
- pvaldes 4y ago
  Is Michael Bay cloning and copyrighting entire scenes of the Scorsese films as entirely yours?
com2kid 4y ago
> In contrast when talking about training code generation models there are multiple comments mentioning this is not ok if licenses weren't respected. I think one of the differences is that people are seeing non-trivial amounts of copyrighted code being output by AI models. If a 262,144 pixel image has a few 2x2 squares copied directly, you can't tell. If a 300 line source file has 20 lines copied directly from a copyrighted source, well, that is more blatant.
- andybak 4y ago
  I personally feel the bar for copyrighting code should be considerably higher than 20 lines.
  - com2kid 4y ago
    > I personally feel the bar for copyrighting code should be considerably higher than 20 lines. That highly depends on the lines of code. One of my (now abandoned) open source react components essentially does some smarter-than-it-probably-should state management in just a handful of LOCs. At least a few hundred people found the clever solution I came up with useful enough to integrate into their own projects. I've seen talented a graphics programmer hand optimize routines to gain significant speed boosts, speed boosts that helped save non-trivial amounts of system resources. And where do you draw the line? That same gfx programmer optimized maybe a dozen functions, each less than 20 lines, but all quite independent of each other. The sum total of his work gave us a huge performance boost over everyone else in the field at the time. And of course you also have super terse languages like APL, where non-trivial algorithms can easily be implemented in 20 LOC. But let's move to another medium, the written word, also one of the less controversial aspects of copyright (ignoring the USA's penchant for indefinite extension of copyright) Start with poems, plenty of artistically significant poems that come in under 20 lines, deserving of copyright for sure. https://tinhouse.com/miracles-by-lucy-corin/ https://tinhouse.com/miracles-by-lucy-corin/ There is a short story, around 22 lines. The problem is, it is complicated, which is why these are the types of things that get litigated all the time. Heck as a profession we cannot even agree on what a line of code is. A LOC in Java is, IMHO, worse less than a LOC in JavaScript, and if you jump to embedded C, wow that is super terse, unless you count the thousands of lines of #defines describing pinouts and such, but domain knowledge is needed to know that those aren't "real" lines of code.
nico 4y ago
Yup. There’s also this, FTA: > the original images themselves aren’t stored in the Stable Diffusion model, with over 100 terabytes of images used to create a tiny 4 GB model Is jpeg compression transformative then? Should a compressed image of something not be copyrightable because “it doesn’t store” the “real image”? How about compressed video? Where do we draw the line?
- friend_and_foe 4y ago
  If you can't reproduce a quantitatively (not qualitatively) similar likeness of an image then it is not just a compressed image.
- marmada 4y ago
  By that case all art should be copyrighted since our brain stores a highly compressed version of everything we've seen. I wager 100 TB => 4GB is different from JPEG compression and more similar to what happens in our brains. "Neural compression" so to speak
  - notamy 4y ago
    > By that case all art should be copyrighted since our brain stores a highly compressed version of everything we've seen. Good thing this is already the case! https://en.wikipedia.org/wiki/Berne_Convention https://en.wikipedia.org/wiki/Berne_Convention > The Berne Convention formally mandated several aspects of modern copyright law; it introduced the concept that a copyright exists the moment a work is "fixed", rather than requiring registration. It also enforces a requirement that countries recognize copyrights held by the citizens of all other parties to the convention.
    - marmada 4y ago
      This doesn't make any sense in this context and I think you know it bud. I was making the point that stable diffusion != JPEG compression
  - wnkrshm 4y ago
narcraft 4y ago
It's actually fine in both cases
- deleted 4y ago
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deleted 4y ago
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charcircuit 4y ago
Code generation models tend to much more often regurgitate code from the training data compared to one of these image based models regurgitating images from the training data. Code generation models need to have special handling for checking if the generated code falls under copyright.
friend_and_foe 4y ago
It's not the training of the models that's the problem, it's when the AI spits out "substantial portions of code", an important term in the GPL and with regard to fair use law, that are exact, sometimes even including exact comments from specific codebases. This does violate the licenses. There's something quantitative in code that you don't get in drawings, drawings the unique quality is purely qualitative, so it is hard to demonstrate what exactly it was that was ripped off. When you find your exact words being returned by a code helper AI it's hard to pretend that it's not directly and plainly just copy pasting code snippets.
- oneoff786 4y ago
  It’s a dumb hill to die on. Doomed to fall to a layer of minor refactoring. If you say that’s the problem, you’ll have nothing to stand on later.
  - andybak 4y ago
    On the contrary - the part that is problemmatic is the verbatim reproduction of copyrighted code. If that's fixed by a "minor refactoring" then there's no hill to die on. It's not AI code generation per se that's problemmatic - it's when it does things that are break current IP law. If you want to debate expanding IP law - that's a different discussion and one I would be rather sceptical about. I'd prefer the that IP law in general was rolled back - not forward.
    - oneoff786 4y ago
      Which is a fine point of view. But it’s not the one that many (most?) detractors actually hold. It would imply that you cannot offend open source licenses by doing something as simple as recreating a codebase in another language, thus eliminating the exact matches.
  - robocat 4y ago
    > Doomed to fall to a layer of minor refactoring Not quite - there is a reason why https://wikipedia.org/wiki/Clean_room_design https://wikipedia.org/wiki/Clean_room_design exists as a concept to workaround copyright, and the same concept could hold for ML models.
Waterluvian 4y ago
Because when I go to a live performance, watch a movie, browse an art gallery, etc., I am training my brain on copyrighted work. Every artist has done the same. No artist has developed their style in a vaccuum. (See my other comment though, I am not sold on any of this being right).
- peoplefromibiza 4y ago
  > Because when I go to a live performance, watch a movie, browse an art gallery, etc., I am training my brain on copyrighted work you paid for it and enjoyed it in the way the artist intended. > I am training my brain on copyrighted work. too bad your brain alone is useless. You need good hands to replicate much of the copyrighted works you "trained" your brain on. > No artist has developed their style in a vacuum. some absolutely did, indeed. Just look at the school of film and animation that artists in USSR developed while separated from the rest of the World. They are unique and completely different from what the west was used to (Disney) https://www.youtube.com/watch?v=2qWBZattl8s https://www.youtube.com/watch?v=2qWBZattl8s https://www.youtube.com/watch?v=1qrWnS3ULPk https://www.youtube.com/watch?v=1qrWnS3ULPk
  - UncleEntity 4y ago
    > Just look at the school of film and animation that artists in USSR developed while separated from the rest of the World. So they were developed in a complete vacuum including traditional things like theater, poetry and story telling?
    - peoplefromibiza 4y ago
      they pioneered new techniques in a vacuum, because they were segregated. complete vacuum is a silly argument, we owe dinosaurs the oil we used to build up our modern societies, would you say that AI would be impossible without dinosaurs? Do we owe the big bang a debt of gratitude?
  - systemicdanna 4y ago
    Both links contain great examples of late 1960s Polish animation. Poland was never a part of USSR. Moreover, just like Czechoslovakia, Poland did not develop its animation style in a vacuum. They had strong artistic connections with many other European countries, especially France. > They are unique and completely different from what the west was used to (Disney) Not sure if you are an American... but Europe has a very old and very rich animation tradition. Growing up in Europe I was only vaguely familiar with Disney. The vast majority of animation I watched as a child was European.
joshcryer 4y ago
I always held the opinion that GPL etc was a copy-left license that was intended to make sure the code was free (free as in freedom not as in beer). That in an ideal world you wouldn't need the GPL or any licenses at all. At this point I really don't care what co-pilot or any of its derivatives result in and I think in the not too distant future we will have machine code to readable code translation which will enable more freedom. That is, it really won't matter if the code is compiled or not, when you can "AI decompile" it into human readable code, do your modifications, and then do with it what you will. From that view let the data be free.
- ipaddr 4y ago
  Some languages need to compile but others don't
- drran 4y ago
  GPL folks are completely OK with something like Copylot when GPL license is obeyed, so all emitted code, generated by AI trained on GPL code, is licensed under GPL again. It's not OK to call our code as «public code» and ignore our license.
  - Siira 4y ago
    But by repeating this argument you are strengthening copyright, which is the fundamental evil GPL was made to fight. There surely will be FOSS clones of Copilot in the near future. There is no need to feed the copyright lobby.
- pessimizer 4y ago
  As long as this copyright violation laundering isn't reserved for the big guys, I'm happy for anything that confuses and delegitimizes the concept of copyright. But it is reserved for the big guys, you're going to get sued to death if you copy any of their work.
michaelmrose 4y ago
I think both are inevitable and I'm ok with both. I think a sticking point is that its considered normal to make your own art in the style of another but abnormal to copy code verbatim. Art seems to be clearly the former while there are instances that probably stick in people's minds where copilot has produced verbatim examples. Indeed it seems like code will be vastly more prone to this problem compared to art because changing a single pixel is merely a question of aesthetics whereas code is constrained tightly by the syntax of the language. With a much smaller space of correct results duplication is likely inevitable.
- somethingor 4y ago
  This is my thinking too. A maximally useful code AI would include verbatim reproduction (since presumably the code it was trained on was written that way for a reason relevant to its function). A maximally useful art AI has comparatively little reason to ever want to output verbatim training inputs.
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mirekrusin 4y ago
Can humans learn from copyrighted work? ps. I'm surprised music has not yet been yet leveled by AI, can't wait for "dimmu borgir christmas carols" prompts.
- itronitron 4y ago
  I don't think the law will get hammered down until the AI models generate 'major recording artist' inspired songs. Anyone claiming that artists can't claim 'style' as a defense of AI generated works is in for a rude awakening.
- CuriouslyC 4y ago
  Music is somewhat more challenging because you have a few other problems that have to be solved in the pipeline, and source separation is still not a 100% solved problem. Beyond that, audio tagging beyond track level artist/genre is a lot harder than image tagging. Once you have separated sources for a training data set, it's like text generation, except that instead of a single function of sequence position, you have multiple correlated functions of time. Text generation models can barely maintain self consistency from paragraph to paragraph, which is a sequence difference of maybe 200 tokens, now consider moving from token position to a time variable, and adding the requirement that multiple sequences retain coherency both with each other, and with themselves over much larger distances. There are generative music models, but it's mostly stuff that's been trained on midi files for a specific genre or artist, and the output isn't that impressive. I am also eagerly awaiting "hark the bloodied angel screams" with blastbeats, shrieks and blistering tremolo guitar, though.
marcosdumay 4y ago
> the majority opinion seems to be that training diffusion models on copyrighted work is totally fine Well, maybe they were all just downvoted into invisibility. But up to your post, I have seen none.
melagonster 4y ago
maybe we can have a GPL code generator model, all generated code are under GPL license?
an1sotropy 4y ago
I think this is a great question, but I think answers should rest on a slightly more detailed understanding of how actually copyright works. IANAL, but to a first-order approximation: everything is "copyrighted" [1]. The copyright is owned by someone/something. The owner gets to set the terms of the licensing. The rare things not under copyright may have been put explicitly into the public domain (which actually takes some effort), or have had their copyright expire (which takes quite a while; thanks Disney). So: this is really a question about fair use [2], and about when the terms of licensing kick in, and it should be understood and discussed as such. I don't think anyone who has really thought about this is claiming that the models can't be trained on (copyrighted) material; the consumption of the material is not the problem, is it? The problem is that the models: (1) sometimes recreate particular inputs or identifiable parts of them (like the Getty watermark), or recreate some essential characteristics of their inputs (like possibly trademark-able stylistic elements), AND ALSO, (2) have no way of attributing the output to the input. Without being able to identify anything specific about the input, it is impossible know with certainty that the output falls within fair use (e.g. because it was sufficiently transformative), and it is impossible to know how to implement the terms of licensing for things that don't fall within fair use. There's just no getting around that with the current crop of models. The legal minefield is not from (1) or (2), but from (1)+(2), at the moment of redistribution, monetized or not. Even if Copilot was only trained on non-reciprocal licenses (BSD, MIT), there are very likely still licensing terms of use, which may include identifying the original copyright owner. Reciprocal licenses like GPL have more involved licensing terms, but that is not the problem: the problem is failure to identify the original licensing terms. We should not use these models as an opportunity to make an issue about GPL or its authors, or about the business model of companies like Getty; both rest on copyright, and come to our attention because of licensing. Sorry about the rant. As for your question: I think it may be as simple as: to what extent are readers here the producers of inputs to the ML models, versus consumers of outputs. It gets personal for coders when models violate licensing terms of FOSS code, but it feels fun/empowering to wield the models to make images that we'd otherwise be unable to access. From my rant above you can tell that whether its for code or images, I think the whole thing is an IP disaster. [1] https://en.wikipedia.org/wiki/Berne_Convention https://en.wikipedia.org/wiki/Berne_Convention [2] https://en.wikipedia.org/wiki/Fair_use https://en.wikipedia.org/wiki/Fair_use
kelseyfrog 4y ago
The vast majority of HN's patronage is tech aligned. Try asking a community of artists the same question and see what their responses are. The results might surprise you.
- dQw4w9WgXcQ 4y ago
  What's funny is HN was majority OK with AirBNB "disrupting" hotels and Uber/Lyft "disrupting" taxi services by bending the rules and exploiting legal loopholes, but when AI starts "disrupting" their artwork and code by bending the rules suddenly disruption becomes a personal problem. Disrupt onward I say. Humans learn and remix from prior copyrighted work all the time using their brains (consciously chosen or not). So long as the new work is distinguishable enough to be unique there's nothing wrong with these new AI creations.
Adverblessly 4y ago
With the caveat of "Strong opinions, weakly held", my personal take is that creating artificial scarcity is inherently immoral and thus copyright itself is immoral. Training AI on someone's non-private work is then completely fine IMO. Copyleft is a license that weakens copyright (and thus inherently good :)), so using machine learning to weaken copyleft by allowing you to copyright "clones" of copyleft code is bad. If I try to generalize here, the problem in both cases is only if you produce copyrighted works, especially if you trained on copyleft works. If instead both models would stipulate that all produced works are copyleft I would be much more fine with it (and I feel it would respect the license of the copyleft works it was trained on, even if that may be legally shaky).
- egypturnash 4y ago
  How do you propose to keep artists able to pay their bills and live a decent life if you're completely cool with training AIs on them? Bonus points if you have any actionable scheme beyond waving your hands and talking vaguely about "basic income". Keep in mind that the life of a professional artist is currently very perilous, anyone working freelance is constantly battling against the social media giants' desire to keep everyone scrolling their site forever. Words like "patreon" and "commission" and links off-site to places an artist can exchange their works for money are poison to The Algorithm and will be hidden. And also if I am reading this right, you have absolutely no problem with an image generator that's been trained on copyrighted work producing work that's either copyrighted or copylefted? You are utterly fine with disregarding the copyrights of the original artist and/or whoever they may have assigned the copyright to as part of their contract?
  - sinity 4y ago
    > How do you propose to keep artists able to pay their bills and live a decent life if you're completely cool with training AIs on them? Why isn't it a concern for any other automation? How do we progress, exactly, if we randomly decide that nothing can disrupt any of the current ways of earning income? What about, IDK, coal miners? > And also if I am reading this right, you have absolutely no problem with an image generator that's been trained on copyrighted work producing work that's either copyrighted or copylefted? You are utterly fine with disregarding the copyrights of the original artist and/or whoever they may have assigned the copyright to as part of their contract? Copyright maximalism is bad. It also doesn't make any sense. Someone learning to reproduce your capabilities by looking at your stuff isn't violating copyright. If we allowed copyright to somehow mean that someone's skills can't be reproduced...
fnordpiglet 4y ago
Because there’s more programmers than artists in this hive mind.
lolinder 4y ago
Possibly controversial opinion: I think the biggest reason why so many people hold conflicting views on this is because of who the victim is in each case. The loudest voices complaining they were directly hurt by Copilot's training are open source maintainers. These are exactly the kind of people who we love to root for on here. They're the little guy involved in a labor of love, giving away their work for free (with terms). On the other hand, the highest-profile victims of Stable Diffusion and DALL-E are Getty Images and company. They're in most respects the opposite of open source maintainers: big companies worth millions of dollars for doing comparatively little work (primarily distributing photos other people took). Because in the case of images the victim is most prominently faceless corporations, I think our collective bias towards "information wants to be free" shows through more clearly when regarding DALL-E than it does with Copilot.
- makeitdouble 4y ago
  > On the other hand, the highest-profile victims of Stable Diffusion and DALL-E are Getty Images and company. They're in most respects the opposite of open source maintainers: big companies worth millions of dollars for doing comparatively little work (primarily distributing photos other people took). It's puzzling to me you acknowledge people are taking these photos and getting a cut from their use through the marketplace, yet still see Getty as the biggest victim. If Getty could AI-generate their whole portofolio and keep 100% of the sales to themselves they'd do it in heartbeat (and I'd expect them to partially go that route). The most screwed people are the photographs ("the little guy" in your comparison)
  - lolinder 4y ago
    I said Getty is the highest profile victim, not the only victim. They're the ones making waves.
- wnkrshm 4y ago
  If you're in the freelance art-sphere, the victims are also small artists who have been hustling hard to be able to live from their art.
not2b 4y ago
I've been thinking of a possible resolution to this. For Copilot and similar systems: keep the training data, and in addition to the text generation, add a search function. Find generated sequences that Copilot puts out, and send pointers to the source for close matches in strings over a threshold length. Example: if Copilot produces the Quake fast inverse square root routine, you'd get a pointer to the source AND to the license. This would allow credit for the author for permissive free licenses, and would allow the user to dump that code if it's GPL and they aren't willing to distribute under those terms. For art, train on contributed images whose authors agree to use them for that purpose. There could be some organization, perhaps a nonprofit, that would own the images and users of the model could credit that organization, and perhaps contribute back their own generated work. That way a legally clean commons could be built and could grow.
- noobermin 4y ago
  Of course people today are training on copyrighted images, chanting fair use because people on the internet tell them it's okay, instead of finding groups of artists who consent to having their art be trained on.
ativzzz 4y ago
I think any code that's posted in public should be considered free to use by anyone for anything and its corresponding license be ignored and invalid. If you want restrictions on how people use your code, don't post it publicly, or have a proprietary portion that's required for compilation
noobermin 4y ago
To be honest, the majority opinion on this just demonstrates how narrow minded and uncritical many people here are that the clear and obvious juxtaposition doesn't get their minds churning. It's hard not to notice half of them merely use AI tools and don't really understand how they work, hence why the silly and incorrect phrase of "your mind is a NN!" keeps occurring here.
angusturner 4y ago
I feel like a broken record on this topic lately, but I strongly believe that training ML models on copyrighted works should be legal. It is clear to anyone that understands this tech that it is not simply "memorizing" or "copying" the training data, even if they can be coaxed into doing this for certain inputs (in the current iteration of the tools). Ultimately, I think the problem of reproducing certain popular works or code snippets will be solved. One interesting direction here are the tools of information theory and differential privacy. e.g) proving that certain training inputs cannot be recovered from the weights, or that there is a threshold of how much information can be gleaned from a single input. It is easy to imagine (because its nearly there already) a future version of StableDiffusion (or CoPilot) which provably compresses all training data beyond any possibility of recovery, and yet still produces extremely convincing results which disrupt the creative professions of art and programming. Until we get to that point, it feels like the only consistent and sensible place to apply regulations is with the model end user. When I use CoPilot, I accept the small (honestly overblown) risk that _maybe_ I won't have the license to use some small snippet of code it spits out. But I'm happy to wear that responsibility, because the boost to productivity is so great that I dread a return to pre-CoPilot world. That is, a world where everyone keeps reinventing the same solution to simple problems over and over and over again.
- kmeisthax 4y ago
  Training being fair use is something I can buy into. As for actually using the model... personally I still find that unacceptable. Even if the risks are low, we have lots of works in the model, so the risk can still add up. The idea you have in your head of training without regurgitation is likely not possible. The underlying technology treats the training set as gospel: the system is trained to regurgitate first, and generalization is a happy accident. Likewise, we can't look into a model to check and see what it's memorized, nor can we trace back an output to a particular training example. Which has ethical implications with the way that AI companies crawl the web to get training data; such models almost certainly hold someone's personal information and there's no way to get it out of there aside from curating your training set to begin with.
  - 4y ago
im3w1l 4y ago
Stealing stuff so you can get rich selling it is worse than stealing for private use. Stealing from idealist volunteers is worse than stealing from a random person.
datacruncher01 4y ago
Style is not protected by copyright. You can create your own art in the style of any living artist and this is allowed. AI is automating that process. Some works that the models produce may be too close to an original work and probably be guilty of copyright violation if that ever goes to court. It'll be up to a judge to look at the original and the AI output to weigh in on if it's different enough or if it's an elaborate copy. Code is different, there isn't a style to it other than perhaps indention and variable naming conventions. Entire sections (that are protected by GPL) are copied. This by itself isn't the issue, it's contaminating your codebase that is the problem. If your work ends up with the same license as the code sources and those are properly documented per those license agreements you're fine. But if you end up violating the GPL and someone knows their code is in use, you are in a tough situation. Again, it'll end up in an expensive court room session where a judge is going to have to determine if enough code was copied to be construed as a license violation. That's the one scenario you would want to avoid in the first place because for a lot of businesses that kind of lawsuit is too expensive to fight.
matheusmoreira 4y ago
It's the hypocrisy of it all. Multi-billion dollar corporations whose empires were built on copyright, violating the licenses of other people's code. Why do they get a pass for that while simultaneously shoving DRM and trusted computing down our throats? I hope they get sued for ridiculous sums.
samatman 4y ago
I hold neither of those opinions. My take is that agricultural civilization is being digested by technocapital and we're all along for the ride. That said, the application of copyright to text, vs, code, vs images, has salient differences. The concept of plagiarism in visual artwork exists by analogy, but it's hard to call it coherent. Music is somewhere in the middle, people have sued successfully over melody and hooks. There are things like characters in animation, it's not unheard of, but the balance is more on the side of "great artists steal".
mr_toad 4y ago
> why do you think it's ok to train diffusion models on copyrighted work, but not co-pilot on GPL code? Probably worth pointing out that GitHub has a license to the code on its site (read the fine print) that is independent of other licenses that the code may available under. Whether that license applies to training ML models is legally uncharted waters. Whether it’s right to train those models is another matter.
FeepingCreature 4y ago
I do open source on Github and I believe both are totally fine.
smeagull 4y ago
I don't think copyrighting things is fine.
SergeAx 4y ago
It is totally okay to train Copilot on GPL code, but the resulting generated code should also be released under GPL license, clearly being a derivative work. I don't even know why it is being discussed.

by cmovq 4y ago

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benlivengood 4y ago

Humans used to learn to code from copyrighted works (textbooks) without much reference to OSS or Free Software. Similarly, teaching ML models to code from copyrighted works isn't going to violate copyright more frequently than a human might; and detecting exact copies should be pretty easy by comparing with the corpus used to train it. Software houses already have to worry about infringement of snippets, and things like Codex are just one more potential source.

ipaddr 4y ago
Those books were purchased and a license granted for such use.
- lmm 4y ago
  > Those books were purchased Sometimes. People also borrowed them, read them in libraries, or in later years looked at free textbooks online. > and a license granted for such use I never heard of such a thing, and it was never seen as necessary. No student checked the licenses on their textbooks before deciding whether they could read them.

firefoxkekw 4y ago

Cognitive dissonance, different persons, hypocrisy.

pjonesdotca 4y ago

Because the models are not creating a 1:1 replacement of the original work. As mentioned before "style" is not something subject to copyright and the model creates a model of that style. The process of finetuning a model generally means that one would not want to recreate the original images as that would overfit it and render it, essentially useless. When it comes to code, there is a higher chance of getting a one-to-one clone of the input as the options used in creating an algorithm, or even a simple function are dramatically reduced imo.

mensetmanusman 4y ago
Code is hundreds to many thousands of lines. A line of code is analogous to one color pixel in digital art.
- com2kid 4y ago
  Depends on which lines of code. I have written projects where I'd consider a handful of lines of code to be the core central tenant of the entire project that everything else is built up around. Copy those lines and everything else is scaffolding that falls out naturally from the development process.
- melagonster 4y ago
  but one line similar code is easier to find. this is because copilot work in one line/small function level.
leereeves 4y ago
> when it comes to code, there is a higher chance of getting a one-to-one clone of the input. I'm not so sure. There's a generated image in the article that I think looks enough like Wonder Woman to cause a lawsuit. That's just one of a handful of images in the article, and doesn't seem to have been chosen for its similarity to Wonder Woman.
dwringer 4y ago
I think when it comes to art, less than one-to-one clones are often still functionally equivalent in the mind of many viewers. Stylistic and thematic content is often just as, if not more, important than the exact composition. But currently the law does agree that this is not copyrightable. And sometimes independent artists profit and make a name for themselves copping other styles, and I think that's great. But could it be considered an intellectual and sociological denial-of-service attack when it's scaled to the point where a machine can crank out dozens of derivative works per minute? I'm not sure this is a situation at all comparable to human artists making derivative works. Those involve long periods of concentration, focus, and reflection by a conscious human agent to pull off, thus in some sense furthering to the intellectual development of humanity and fostering a deeper appreciation for the source work. The machine does none of that; it's sort of just a photocopier one step removed in hyperspace, copying some of the artists' abstractions instead of their brush strokes.

bombcar 4y ago

If I were to steel man both sides it'd be something like this: 1. Training an AI model on code (so far) makes it regurgitate code line-for-line (with comments!). This is like "learning to code" by just cut and pasting working code from other codebases, you have to follow the license. The AI doesn't "understand the algorithm" at all (or it hasn't been told "don't export the input you fool"). Obviously a bog-simple AI could make all licenses moot by dumping out what it input, and the courts wouldn't permit that. 2. Training an AI model on illustrations so far produces "style parodies" which may look similar to an untrained eye (the artist here is annoyed because she'd not art like that, even though to us it looks similar enough). Drawing a picture that looks like Mickey Mouse is a trademark violation, but tracing a picture of the Mouse is both a trademark and a copyright violation. The first violates some pretty clear legal concepts; the second is closer to violating moral concepts but those are more flexible - if an artist spends years learning to paint in the style of Michelangelo is that immoral?

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shadowgovt 4y ago
And perhaps more importantly regarding (1) than simple regurgitation: code does things. There's a real risk that if you just let Copilot emit output without understanding what that output does, it'll do the wrong thing. Art is in the eye of the beholder. If the output looks correct as per what you're looking for, it is correct. There's no additional layer of "Is it saying what I meant it to say" that is relevant to anyone who isn't an art critic.
- Xelynega 4y ago
  Art is in the eye of the beholder, but it still needs a creator. That creator had a vision in mind that's unique to them because of their experiences, and I think it's wrong to say that this image can be quantified as a location in a abstract feature space. So to say "there is no additional layer [to judge goodness] that is relevant to [most people]" assumes there is an algorithmic measure of "goodness" that can be applied to art, which is an assumption you need to make to believe that there's any similarities with AI generated art and human generated other than "they look kinda similar".

mensetmanusman 4y ago

People often hold conflicting views, they done like to think about it though, because it can lead to cognitive dissonance. That’s one reason why it is probably better to have a derived world view than a contrived world view.

aliqot 4y ago

Your argument is tantamount to expecting Michael Bay to have never seen a Scorcese or deriving influence from it.

pessimizer 4y ago
Pretending it's not clearly more complicated than that will not convince anyone, it will make them feel condescended to. While Scorcese is Scorcese, a deep learning model is not Michael Bay.
- aliqot 4y ago
  I used that comparison on purpose. Michael Bay leans on a lot of computer driven technology to shoot movies inspired by other more traditional directors. The comparison is direct, if you feel condescended to, I did not intend that.
pvaldes 4y ago
Is Michael Bay cloning and copyrighting entire scenes of the Scorsese films as entirely yours?

com2kid 4y ago

> In contrast when talking about training code generation models there are multiple comments mentioning this is not ok if licenses weren't respected. I think one of the differences is that people are seeing non-trivial amounts of copyrighted code being output by AI models. If a 262,144 pixel image has a few 2x2 squares copied directly, you can't tell. If a 300 line source file has 20 lines copied directly from a copyrighted source, well, that is more blatant.

andybak 4y ago
I personally feel the bar for copyrighting code should be considerably higher than 20 lines.
- com2kid 4y ago
  > I personally feel the bar for copyrighting code should be considerably higher than 20 lines. That highly depends on the lines of code. One of my (now abandoned) open source react components essentially does some smarter-than-it-probably-should state management in just a handful of LOCs. At least a few hundred people found the clever solution I came up with useful enough to integrate into their own projects. I've seen talented a graphics programmer hand optimize routines to gain significant speed boosts, speed boosts that helped save non-trivial amounts of system resources. And where do you draw the line? That same gfx programmer optimized maybe a dozen functions, each less than 20 lines, but all quite independent of each other. The sum total of his work gave us a huge performance boost over everyone else in the field at the time. And of course you also have super terse languages like APL, where non-trivial algorithms can easily be implemented in 20 LOC. But let's move to another medium, the written word, also one of the less controversial aspects of copyright (ignoring the USA's penchant for indefinite extension of copyright) Start with poems, plenty of artistically significant poems that come in under 20 lines, deserving of copyright for sure. https://tinhouse.com/miracles-by-lucy-corin/ https://tinhouse.com/miracles-by-lucy-corin/ There is a short story, around 22 lines. The problem is, it is complicated, which is why these are the types of things that get litigated all the time. Heck as a profession we cannot even agree on what a line of code is. A LOC in Java is, IMHO, worse less than a LOC in JavaScript, and if you jump to embedded C, wow that is super terse, unless you count the thousands of lines of #defines describing pinouts and such, but domain knowledge is needed to know that those aren't "real" lines of code.

nico 4y ago

Yup. There’s also this, FTA: > the original images themselves aren’t stored in the Stable Diffusion model, with over 100 terabytes of images used to create a tiny 4 GB model Is jpeg compression transformative then? Should a compressed image of something not be copyrightable because “it doesn’t store” the “real image”? How about compressed video? Where do we draw the line?

friend_and_foe 4y ago
If you can't reproduce a quantitatively (not qualitatively) similar likeness of an image then it is not just a compressed image.
marmada 4y ago
By that case all art should be copyrighted since our brain stores a highly compressed version of everything we've seen. I wager 100 TB => 4GB is different from JPEG compression and more similar to what happens in our brains. "Neural compression" so to speak
- notamy 4y ago
  > By that case all art should be copyrighted since our brain stores a highly compressed version of everything we've seen. Good thing this is already the case! https://en.wikipedia.org/wiki/Berne_Convention https://en.wikipedia.org/wiki/Berne_Convention > The Berne Convention formally mandated several aspects of modern copyright law; it introduced the concept that a copyright exists the moment a work is "fixed", rather than requiring registration. It also enforces a requirement that countries recognize copyrights held by the citizens of all other parties to the convention.
  - marmada 4y ago
    This doesn't make any sense in this context and I think you know it bud. I was making the point that stable diffusion != JPEG compression
- wnkrshm 4y ago

narcraft 4y ago

It's actually fine in both cases

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charcircuit 4y ago

Code generation models tend to much more often regurgitate code from the training data compared to one of these image based models regurgitating images from the training data. Code generation models need to have special handling for checking if the generated code falls under copyright.

friend_and_foe 4y ago

It's not the training of the models that's the problem, it's when the AI spits out "substantial portions of code", an important term in the GPL and with regard to fair use law, that are exact, sometimes even including exact comments from specific codebases. This does violate the licenses. There's something quantitative in code that you don't get in drawings, drawings the unique quality is purely qualitative, so it is hard to demonstrate what exactly it was that was ripped off. When you find your exact words being returned by a code helper AI it's hard to pretend that it's not directly and plainly just copy pasting code snippets.

oneoff786 4y ago
It’s a dumb hill to die on. Doomed to fall to a layer of minor refactoring. If you say that’s the problem, you’ll have nothing to stand on later.
- andybak 4y ago
  On the contrary - the part that is problemmatic is the verbatim reproduction of copyrighted code. If that's fixed by a "minor refactoring" then there's no hill to die on. It's not AI code generation per se that's problemmatic - it's when it does things that are break current IP law. If you want to debate expanding IP law - that's a different discussion and one I would be rather sceptical about. I'd prefer the that IP law in general was rolled back - not forward.
  - oneoff786 4y ago
    Which is a fine point of view. But it’s not the one that many (most?) detractors actually hold. It would imply that you cannot offend open source licenses by doing something as simple as recreating a codebase in another language, thus eliminating the exact matches.
- robocat 4y ago
  > Doomed to fall to a layer of minor refactoring Not quite - there is a reason why https://wikipedia.org/wiki/Clean_room_design https://wikipedia.org/wiki/Clean_room_design exists as a concept to workaround copyright, and the same concept could hold for ML models.

Waterluvian 4y ago

Because when I go to a live performance, watch a movie, browse an art gallery, etc., I am training my brain on copyrighted work. Every artist has done the same. No artist has developed their style in a vaccuum. (See my other comment though, I am not sold on any of this being right).

peoplefromibiza 4y ago
> Because when I go to a live performance, watch a movie, browse an art gallery, etc., I am training my brain on copyrighted work you paid for it and enjoyed it in the way the artist intended. > I am training my brain on copyrighted work. too bad your brain alone is useless. You need good hands to replicate much of the copyrighted works you "trained" your brain on. > No artist has developed their style in a vacuum. some absolutely did, indeed. Just look at the school of film and animation that artists in USSR developed while separated from the rest of the World. They are unique and completely different from what the west was used to (Disney) https://www.youtube.com/watch?v=2qWBZattl8s https://www.youtube.com/watch?v=2qWBZattl8s https://www.youtube.com/watch?v=1qrWnS3ULPk https://www.youtube.com/watch?v=1qrWnS3ULPk
- UncleEntity 4y ago
  > Just look at the school of film and animation that artists in USSR developed while separated from the rest of the World. So they were developed in a complete vacuum including traditional things like theater, poetry and story telling?
  - peoplefromibiza 4y ago
    they pioneered new techniques in a vacuum, because they were segregated. complete vacuum is a silly argument, we owe dinosaurs the oil we used to build up our modern societies, would you say that AI would be impossible without dinosaurs? Do we owe the big bang a debt of gratitude?
- systemicdanna 4y ago
  Both links contain great examples of late 1960s Polish animation. Poland was never a part of USSR. Moreover, just like Czechoslovakia, Poland did not develop its animation style in a vacuum. They had strong artistic connections with many other European countries, especially France. > They are unique and completely different from what the west was used to (Disney) Not sure if you are an American... but Europe has a very old and very rich animation tradition. Growing up in Europe I was only vaguely familiar with Disney. The vast majority of animation I watched as a child was European.

joshcryer 4y ago

I always held the opinion that GPL etc was a copy-left license that was intended to make sure the code was free (free as in freedom not as in beer). That in an ideal world you wouldn't need the GPL or any licenses at all. At this point I really don't care what co-pilot or any of its derivatives result in and I think in the not too distant future we will have machine code to readable code translation which will enable more freedom. That is, it really won't matter if the code is compiled or not, when you can "AI decompile" it into human readable code, do your modifications, and then do with it what you will. From that view let the data be free.

ipaddr 4y ago
Some languages need to compile but others don't
drran 4y ago
GPL folks are completely OK with something like Copylot when GPL license is obeyed, so all emitted code, generated by AI trained on GPL code, is licensed under GPL again. It's not OK to call our code as «public code» and ignore our license.
- Siira 4y ago
  But by repeating this argument you are strengthening copyright, which is the fundamental evil GPL was made to fight. There surely will be FOSS clones of Copilot in the near future. There is no need to feed the copyright lobby.
pessimizer 4y ago
As long as this copyright violation laundering isn't reserved for the big guys, I'm happy for anything that confuses and delegitimizes the concept of copyright. But it is reserved for the big guys, you're going to get sued to death if you copy any of their work.

michaelmrose 4y ago

I think both are inevitable and I'm ok with both. I think a sticking point is that its considered normal to make your own art in the style of another but abnormal to copy code verbatim. Art seems to be clearly the former while there are instances that probably stick in people's minds where copilot has produced verbatim examples. Indeed it seems like code will be vastly more prone to this problem compared to art because changing a single pixel is merely a question of aesthetics whereas code is constrained tightly by the syntax of the language. With a much smaller space of correct results duplication is likely inevitable.

somethingor 4y ago
This is my thinking too. A maximally useful code AI would include verbatim reproduction (since presumably the code it was trained on was written that way for a reason relevant to its function). A maximally useful art AI has comparatively little reason to ever want to output verbatim training inputs.

deleted 4y ago

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mirekrusin 4y ago

Can humans learn from copyrighted work? ps. I'm surprised music has not yet been yet leveled by AI, can't wait for "dimmu borgir christmas carols" prompts.

itronitron 4y ago
I don't think the law will get hammered down until the AI models generate 'major recording artist' inspired songs. Anyone claiming that artists can't claim 'style' as a defense of AI generated works is in for a rude awakening.
CuriouslyC 4y ago
Music is somewhat more challenging because you have a few other problems that have to be solved in the pipeline, and source separation is still not a 100% solved problem. Beyond that, audio tagging beyond track level artist/genre is a lot harder than image tagging. Once you have separated sources for a training data set, it's like text generation, except that instead of a single function of sequence position, you have multiple correlated functions of time. Text generation models can barely maintain self consistency from paragraph to paragraph, which is a sequence difference of maybe 200 tokens, now consider moving from token position to a time variable, and adding the requirement that multiple sequences retain coherency both with each other, and with themselves over much larger distances. There are generative music models, but it's mostly stuff that's been trained on midi files for a specific genre or artist, and the output isn't that impressive. I am also eagerly awaiting "hark the bloodied angel screams" with blastbeats, shrieks and blistering tremolo guitar, though.

marcosdumay 4y ago

> the majority opinion seems to be that training diffusion models on copyrighted work is totally fine Well, maybe they were all just downvoted into invisibility. But up to your post, I have seen none.

melagonster 4y ago

maybe we can have a GPL code generator model, all generated code are under GPL license?

an1sotropy 4y ago

I think this is a great question, but I think answers should rest on a slightly more detailed understanding of how actually copyright works. IANAL, but to a first-order approximation: everything is "copyrighted" [1]. The copyright is owned by someone/something. The owner gets to set the terms of the licensing. The rare things not under copyright may have been put explicitly into the public domain (which actually takes some effort), or have had their copyright expire (which takes quite a while; thanks Disney). So: this is really a question about fair use [2], and about when the terms of licensing kick in, and it should be understood and discussed as such. I don't think anyone who has really thought about this is claiming that the models can't be trained on (copyrighted) material; the consumption of the material is not the problem, is it? The problem is that the models: (1) sometimes recreate particular inputs or identifiable parts of them (like the Getty watermark), or recreate some essential characteristics of their inputs (like possibly trademark-able stylistic elements), AND ALSO, (2) have no way of attributing the output to the input. Without being able to identify anything specific about the input, it is impossible know with certainty that the output falls within fair use (e.g. because it was sufficiently transformative), and it is impossible to know how to implement the terms of licensing for things that don't fall within fair use. There's just no getting around that with the current crop of models. The legal minefield is not from (1) or (2), but from (1)+(2), at the moment of redistribution, monetized or not. Even if Copilot was only trained on non-reciprocal licenses (BSD, MIT), there are very likely still licensing terms of use, which may include identifying the original copyright owner. Reciprocal licenses like GPL have more involved licensing terms, but that is not the problem: the problem is failure to identify the original licensing terms. We should not use these models as an opportunity to make an issue about GPL or its authors, or about the business model of companies like Getty; both rest on copyright, and come to our attention because of licensing. Sorry about the rant. As for your question: I think it may be as simple as: to what extent are readers here the producers of inputs to the ML models, versus consumers of outputs. It gets personal for coders when models violate licensing terms of FOSS code, but it feels fun/empowering to wield the models to make images that we'd otherwise be unable to access. From my rant above you can tell that whether its for code or images, I think the whole thing is an IP disaster. [1] https://en.wikipedia.org/wiki/Berne_Convention https://en.wikipedia.org/wiki/Berne_Convention [2] https://en.wikipedia.org/wiki/Fair_use https://en.wikipedia.org/wiki/Fair_use

kelseyfrog 4y ago

The vast majority of HN's patronage is tech aligned. Try asking a community of artists the same question and see what their responses are. The results might surprise you.

dQw4w9WgXcQ 4y ago
What's funny is HN was majority OK with AirBNB "disrupting" hotels and Uber/Lyft "disrupting" taxi services by bending the rules and exploiting legal loopholes, but when AI starts "disrupting" their artwork and code by bending the rules suddenly disruption becomes a personal problem. Disrupt onward I say. Humans learn and remix from prior copyrighted work all the time using their brains (consciously chosen or not). So long as the new work is distinguishable enough to be unique there's nothing wrong with these new AI creations.

Adverblessly 4y ago

With the caveat of "Strong opinions, weakly held", my personal take is that creating artificial scarcity is inherently immoral and thus copyright itself is immoral. Training AI on someone's non-private work is then completely fine IMO. Copyleft is a license that weakens copyright (and thus inherently good :)), so using machine learning to weaken copyleft by allowing you to copyright "clones" of copyleft code is bad. If I try to generalize here, the problem in both cases is only if you produce copyrighted works, especially if you trained on copyleft works. If instead both models would stipulate that all produced works are copyleft I would be much more fine with it (and I feel it would respect the license of the copyleft works it was trained on, even if that may be legally shaky).

egypturnash 4y ago
How do you propose to keep artists able to pay their bills and live a decent life if you're completely cool with training AIs on them? Bonus points if you have any actionable scheme beyond waving your hands and talking vaguely about "basic income". Keep in mind that the life of a professional artist is currently very perilous, anyone working freelance is constantly battling against the social media giants' desire to keep everyone scrolling their site forever. Words like "patreon" and "commission" and links off-site to places an artist can exchange their works for money are poison to The Algorithm and will be hidden. And also if I am reading this right, you have absolutely no problem with an image generator that's been trained on copyrighted work producing work that's either copyrighted or copylefted? You are utterly fine with disregarding the copyrights of the original artist and/or whoever they may have assigned the copyright to as part of their contract?
- sinity 4y ago
  > How do you propose to keep artists able to pay their bills and live a decent life if you're completely cool with training AIs on them? Why isn't it a concern for any other automation? How do we progress, exactly, if we randomly decide that nothing can disrupt any of the current ways of earning income? What about, IDK, coal miners? > And also if I am reading this right, you have absolutely no problem with an image generator that's been trained on copyrighted work producing work that's either copyrighted or copylefted? You are utterly fine with disregarding the copyrights of the original artist and/or whoever they may have assigned the copyright to as part of their contract? Copyright maximalism is bad. It also doesn't make any sense. Someone learning to reproduce your capabilities by looking at your stuff isn't violating copyright. If we allowed copyright to somehow mean that someone's skills can't be reproduced...

fnordpiglet 4y ago

Because there’s more programmers than artists in this hive mind.

lolinder 4y ago

Possibly controversial opinion: I think the biggest reason why so many people hold conflicting views on this is because of who the victim is in each case. The loudest voices complaining they were directly hurt by Copilot's training are open source maintainers. These are exactly the kind of people who we love to root for on here. They're the little guy involved in a labor of love, giving away their work for free (with terms). On the other hand, the highest-profile victims of Stable Diffusion and DALL-E are Getty Images and company. They're in most respects the opposite of open source maintainers: big companies worth millions of dollars for doing comparatively little work (primarily distributing photos other people took). Because in the case of images the victim is most prominently faceless corporations, I think our collective bias towards "information wants to be free" shows through more clearly when regarding DALL-E than it does with Copilot.

makeitdouble 4y ago
> On the other hand, the highest-profile victims of Stable Diffusion and DALL-E are Getty Images and company. They're in most respects the opposite of open source maintainers: big companies worth millions of dollars for doing comparatively little work (primarily distributing photos other people took). It's puzzling to me you acknowledge people are taking these photos and getting a cut from their use through the marketplace, yet still see Getty as the biggest victim. If Getty could AI-generate their whole portofolio and keep 100% of the sales to themselves they'd do it in heartbeat (and I'd expect them to partially go that route). The most screwed people are the photographs ("the little guy" in your comparison)
- lolinder 4y ago
  I said Getty is the highest profile victim, not the only victim. They're the ones making waves.
wnkrshm 4y ago
If you're in the freelance art-sphere, the victims are also small artists who have been hustling hard to be able to live from their art.

not2b 4y ago

I've been thinking of a possible resolution to this. For Copilot and similar systems: keep the training data, and in addition to the text generation, add a search function. Find generated sequences that Copilot puts out, and send pointers to the source for close matches in strings over a threshold length. Example: if Copilot produces the Quake fast inverse square root routine, you'd get a pointer to the source AND to the license. This would allow credit for the author for permissive free licenses, and would allow the user to dump that code if it's GPL and they aren't willing to distribute under those terms. For art, train on contributed images whose authors agree to use them for that purpose. There could be some organization, perhaps a nonprofit, that would own the images and users of the model could credit that organization, and perhaps contribute back their own generated work. That way a legally clean commons could be built and could grow.

noobermin 4y ago
Of course people today are training on copyrighted images, chanting fair use because people on the internet tell them it's okay, instead of finding groups of artists who consent to having their art be trained on.

ativzzz 4y ago

I think any code that's posted in public should be considered free to use by anyone for anything and its corresponding license be ignored and invalid. If you want restrictions on how people use your code, don't post it publicly, or have a proprietary portion that's required for compilation

noobermin 4y ago

To be honest, the majority opinion on this just demonstrates how narrow minded and uncritical many people here are that the clear and obvious juxtaposition doesn't get their minds churning. It's hard not to notice half of them merely use AI tools and don't really understand how they work, hence why the silly and incorrect phrase of "your mind is a NN!" keeps occurring here.

angusturner 4y ago

I feel like a broken record on this topic lately, but I strongly believe that training ML models on copyrighted works should be legal. It is clear to anyone that understands this tech that it is not simply "memorizing" or "copying" the training data, even if they can be coaxed into doing this for certain inputs (in the current iteration of the tools). Ultimately, I think the problem of reproducing certain popular works or code snippets will be solved. One interesting direction here are the tools of information theory and differential privacy. e.g) proving that certain training inputs cannot be recovered from the weights, or that there is a threshold of how much information can be gleaned from a single input. It is easy to imagine (because its nearly there already) a future version of StableDiffusion (or CoPilot) which provably compresses all training data beyond any possibility of recovery, and yet still produces extremely convincing results which disrupt the creative professions of art and programming. Until we get to that point, it feels like the only consistent and sensible place to apply regulations is with the model end user. When I use CoPilot, I accept the small (honestly overblown) risk that _maybe_ I won't have the license to use some small snippet of code it spits out. But I'm happy to wear that responsibility, because the boost to productivity is so great that I dread a return to pre-CoPilot world. That is, a world where everyone keeps reinventing the same solution to simple problems over and over and over again.

kmeisthax 4y ago
Training being fair use is something I can buy into. As for actually using the model... personally I still find that unacceptable. Even if the risks are low, we have lots of works in the model, so the risk can still add up. The idea you have in your head of training without regurgitation is likely not possible. The underlying technology treats the training set as gospel: the system is trained to regurgitate first, and generalization is a happy accident. Likewise, we can't look into a model to check and see what it's memorized, nor can we trace back an output to a particular training example. Which has ethical implications with the way that AI companies crawl the web to get training data; such models almost certainly hold someone's personal information and there's no way to get it out of there aside from curating your training set to begin with.
- 4y ago

im3w1l 4y ago

Stealing stuff so you can get rich selling it is worse than stealing for private use. Stealing from idealist volunteers is worse than stealing from a random person.

datacruncher01 4y ago

Style is not protected by copyright. You can create your own art in the style of any living artist and this is allowed. AI is automating that process. Some works that the models produce may be too close to an original work and probably be guilty of copyright violation if that ever goes to court. It'll be up to a judge to look at the original and the AI output to weigh in on if it's different enough or if it's an elaborate copy. Code is different, there isn't a style to it other than perhaps indention and variable naming conventions. Entire sections (that are protected by GPL) are copied. This by itself isn't the issue, it's contaminating your codebase that is the problem. If your work ends up with the same license as the code sources and those are properly documented per those license agreements you're fine. But if you end up violating the GPL and someone knows their code is in use, you are in a tough situation. Again, it'll end up in an expensive court room session where a judge is going to have to determine if enough code was copied to be construed as a license violation. That's the one scenario you would want to avoid in the first place because for a lot of businesses that kind of lawsuit is too expensive to fight.

matheusmoreira 4y ago

It's the hypocrisy of it all. Multi-billion dollar corporations whose empires were built on copyright, violating the licenses of other people's code. Why do they get a pass for that while simultaneously shoving DRM and trusted computing down our throats? I hope they get sued for ridiculous sums.

samatman 4y ago

I hold neither of those opinions. My take is that agricultural civilization is being digested by technocapital and we're all along for the ride. That said, the application of copyright to text, vs, code, vs images, has salient differences. The concept of plagiarism in visual artwork exists by analogy, but it's hard to call it coherent. Music is somewhere in the middle, people have sued successfully over melody and hooks. There are things like characters in animation, it's not unheard of, but the balance is more on the side of "great artists steal".

mr_toad 4y ago

> why do you think it's ok to train diffusion models on copyrighted work, but not co-pilot on GPL code? Probably worth pointing out that GitHub has a license to the code on its site (read the fine print) that is independent of other licenses that the code may available under. Whether that license applies to training ML models is legally uncharted waters. Whether it’s right to train those models is another matter.

FeepingCreature 4y ago

I do open source on Github and I believe both are totally fine.

smeagull 4y ago

I don't think copyrighting things is fine.

SergeAx 4y ago

It is totally okay to train Copilot on GPL code, but the resulting generated code should also be released under GPL license, clearly being a derivative work. I don't even know why it is being discussed.