GitHub Copilot is not infringing your copyright (2021)
felixreda.eu
felixreda.eu
It is truly amazing how many people will shill for these massive corporations that claim they love open source or that their AI is open while they profit off of the violation of licenses and contribute very little back.
edit wording about the shill
What about BSL, SSPL, or other source available (for your eyes only) licenses? Copilot harvests all public repos, regardless of its license.
To simplify:
- imagine all code Copilot trained on is GPL licensed. - we have a universal function `isInfringing(code)` that has access to all GPL code, and returns `true` if it is infringing some GPL code.
for a given prompt; if `isInfringing(copilot(prompt))==false` we cannot claim copilot infringing on GPL code, even it is trained on GPLed code.
so the problem starts here; does the piece of code copilot emits, if written by yourself also would be infringing ?
why everyone on discussions tries to bring "if a human made it"? a generative AI operates way faster than anyone ever existed and ever will and probably a person aware of the license & acting respectful towards it, will create something more sensible/plausible to avoid plagiarism
now having dozen/hundreds/thousands of humans substituted by a machine that makes money for some for-profit company is really fair? even if they were a non-profit, as someone pointed up, people who create the content that feeds the weights aren't recieving a penny! they already made money with it, they will make more & that is/will upgrading/e the state of gen. AI
for sure legal battles on people copying code from permissive licenses should exist but it's feels a different discussion
At what measure is one sufficiently inspired for it to be a derivate work? That is up to courts to decide.
Technically when you get a piece from each, there is no infringement legally. ( as they have all different copyright holders )
If CoPilot indeed derives a function (or a functional block) from a single source, it might plainly violate the license of the repository where it derives the code from.
There are many questions, and nothing is clear cut. The only thing I know is, I will never use that thing.
EDIT: I remembered that people were able to make CoPilot emit their code almost as-is with the correct prompts: https://x.com/docsparse/status/1581461734665367554
So it's not we're taking a bit from n different sources, and generate something with that.
False in ex-Commonwealth countries and Japan.
And for which jurisdictions has this been established? What is the legal argument that "weights" are derivative but output is not?
I'm surprised it's so clear cut as you say, but I haven't really been following the whole kerfuffle.
If you can get a decent facsimile of licensed code out the other end, how is it really any different from lossy compression? I doubt the courts would consider a lossy re-encode of a disney movie as free from copyright.
That's not really Microsoft's problem as long as people aren't afraid of using Copilot to generate (potentially GPL'd) code. And from what I've generally seen from genAI discussions at work, people think very little about any legal implications.
However, copyright isn’t cooties. If the output is not similar, then it is not infringing regardless of how much GPL’d training data was used to generate it.
>"How much change is enough" has always been a gray area for courts and humans to decide.
But copilot has been shown to generate chunks of sufficient size and specificity that as a layman it very much feels like "copied GPL code". And my boss agrees too - we have a blanket ban on generative AI tools in our work because it's not considered worth the risk.
Only when given chinks of copyrighted code as input. I don't think anyone has demonstrated big chunks of copyrighted code in the output when copyrighted code isn't present in the query/context.
In fact, I suspect microsoft specifically filters the output for that.
No, of course not. We should probably revisit copyright law, given that it was written at a time when no-one foresaw modern AI tools, its capabilities, and its effects on creators and societies.
Free Software already views all proprietary software as inherently immoral. So there is no need to take a detour of what went into making the software to reach that conclusion from that angle.
Transformers predict the most likely next token, the most likely next token is usually related to the surrounding context.
So yes it can create code similar to GPL code but it can only do that consistently when the GPL code is included in the context. So don’t do that.
Even the license itself states it's optional, and you don't have to agree it (if you don't, you get the copyright law's default).
Author of the article is a former member of the Pirate Party and EU parliament, so they have expertise in the copyright law.
So the same persons that supported Napster and the Pirate Bay now want to circumvent copyright for open source software.
An unholy alliance, but the recent comments from some Microsoft brass about everything on the Web being freeware seems to indicate that these are the talking points that Microsoft and its new allies will put out.
I expect that people professionally dedicated to a copyright reform are very familiar with it, regardless of which way they want to reform it.
The copyright laws were written before generative AI existed, so they may not be adequate or fair in the new reality, but that's the current state anyway. As Reda notes, the law is not specific enough to draw the difference between collecting and processing data for search engines (that may be using ML for retrieval) and using the same data with LLMs.
EU courts disagree:
> Under European copyright law, scraping GPL-licensed code, or any other copyrighted work, is legal, regardless of the licence used.
This is not immediately obvious to me.
A small though experiment: the Harry Potter books are clearly copyrighted works. If I generate a frequency list of all words in these books, i.e. a list of all words and how often they appear, that frequency list is derived from the original work, in the normal way we would use the word "derived". But is it a "derivative work", under the strict legal definition of this term?
However, the broader issue that Microsoft has infiltrated OSS and its organizations successfully by hiring and donating remains. It would not surprise me at all if they now hire people with an ostensibly "freedom fighter" background for credibility.
Look at how many people here cite his (former?) membership in the Pirate Party for credibility! Party membership means nothing. Politicians (in general!) change their minds, can be bought, etc. The Green Party in Germany started out as a peace party and has been used repeatedly to lend credibility to the Kossovo and other wars.
https://blog.okfn.org/2022/03/03/microsoft-to-support-open-d...
Today, we are pleased to announce that Microsoft will once again be supporting Open Data Day by providing mini-grants to organisations to help them run events, the call will launch on Open Data Day 2022.
They also supported "Open Data Day 2021". Sounds like a nice trojan horse to influence EU legislation through purported activists.
Frequency signal data over an image are not the image, but no one argues a JPEG encoded copy of a PNG isn't the same image. I think the weights vs code are similar in that regard.
As for releasing weights, probably more if we're talking about AGPL code.
There's existing analogies like encyclopedias and dictionaries.
One interesting aspect to those sorts of consolidation works is that they may contain errors and other artifacts, specifically to identify duplications of their work vs new from-scratch work.
It also feels similar to the recent article posted about photography and how during its early days pictures were used for advertising without the consent of those photographed. [0]
[0] https://www.truthdig.com/articles/the-troubled-development-o...
There are other problems with releasing model weights under the GPL. It just doesn't fit, in the same way as releasing non-software under the GPL doesn't make sense.
Calling the output of generative AI copyrightable violates the spirit of copyright, as it is neither creative nor labor-intensive. We could quibble about that, but I think we can at least agree that the point is that this generative AI stuff requires very little skill to use in most cases and can't operate without prior art to train on. Other lame stuff has been copyrighted before, like paint splatters and stuff, but even that type of art appears to involve more skill than entering a few words into a generative AI.
That should not be astonishing. The Free Software community has made it clear from day 1 that the GPL can only achieve its goals through enforcement of copyright. If the authors wanted their code to be made use of in non-Free software, they would have used a BSD or MIT license.
We should mention when we say this, although I think it is self-evident, that the preferable alternative is reducing the scope of copyright across the board -- be it with shorter time frames (I'd argue even twenty years total is too long!) or some other means.
To programmers and developers, remember the core of free software is NOT the commercial developer / programmer and it NEVER has been. The core is always the user and what they need. This is so important that it needs to be repeated every time someone talks about free software because free software is NOT about open source. Open source code is a necessary part of free software but it is NOT sufficient.
Would reducing copyright duration actually help with that?
Which is why gnu/linux without a terminal is totally usable and therefore accesible to the non programmer. /s
I agree that user centric developement should be the goal, but I hardly see it implemented. Free software programmers almost allways solved their own needs first, which is alright, because usually no one paid them to serve other peoples needs, but I seldom see this goal met.
The primary consideration is freedom for the user. Ease-of-use for the user is a different consideration.
I was referring to this and the main thing users need, is software they can use to solve their problems. If they have to study IT to do so, or hire programmers first, then this would be primarily a new (and big) problem to them, before they even can start working on their problem.
You know, simple examples of common use cases right on top? Not my experience. I experienced it as a system written by and for hackers. And everything else an afterthought at best. I remember my first real life linux hardcore enthusiasts: "I have to free myself from the GUI"
Well, I did, but the common people won't.
Using the terminal is not "programming". Non-programmers can use the terminal for many non-programming tasks. Imagemagick and netpbm-progs require no knowledge of programming to use, although it may require knowledge manipulating files and some graphical theory. The only difference from GIMP or Photoshop is that the UI/UX has a different efficiency metric (mainly because interactive image manipulation is more efficient when you are interacting visually). But the operations are just as discoverable: reading and navigating help text/man pages in the former (the man pages for Imagemagick and netpbm-progs are relatively decent), and reading and navigating menus and dialog boxes in the latter.
I know. Which is why the year of the linux desktop was such a success.
"Why does it matter to the person who makes their solution available that the common people won't?"
They have all the right not to care, but it still is not helping the goal of being useful for normal people.
That isn't the goal. I don't know why you keep saying that.
Maybe, but your goal is irrelevant to the authors of the GPL.
> The question here is, how is it for GNU in general.
The goal for the FSF and their GPL is, and always was, freedom for the user of the software.
Ease-of-use was never an important consideration, much less a goal. This whole discussion from you in this thread is bizarre, TBH. You are projecting your goals onto the FSF's GPL, and judging it to be a failure based on your goals.
Your goals are irrelevant to them, just as their goals appear to be irrelevant to you.
Have you used modern Fedora? I have an old Thinkpad at home that I put Fedora on last year as our "sofa" laptop for web shopping etc. I took careful note of what I needed to do to set it up and that involved nothing on the command line to get to something good that my wife could happily use (not a techie, never used Linux).
And just because you can use something for internet, does not mean it satisfies user need in general. It satisfies some users needs. Those who need a little - those who understand the system. But the mainstreamusers in the middle .. continue to stay away for a reason. But hopefully more will invest in the change, with the forced win 11 change.
If they win this fight - GPL code will be usable by all of Artifical Humanity. GPL Singularity.
Take vi(m). It's not intuitive to your suggested target user and has a learning curve shaped like a cliff. So it fails to provide for what you consider a "user". However it serves it's actual target users very well.
Arch doesn't position itself towards what you have presented as a user, Mint might however as they have very different target audiences. Not everything has to be designed to the lowest common denominator.
Yeah, a code editor is by definition for developers.
The question here was about the OS in general. And it is a pretty established fact, that linux is popular with developers, but not with mainstream normal people. Unless linux comes in the shape of android, where everything linux is hidden and locked down.
These situations might trigger a lot of issues, but none related to copyright. If you work for MS, then move to another company, there is no copyright infringement if you simply generate new code based on whatever you read at MS. There might be some rule regarding non-competitive, etc, but these are not related to copyright.
The very basic question is how the LLM got trained and how it got access to the source. If MS source code would leak, you cannot sue people for reading it.
Having read MS code and starting to generate new code that is heavily inspired - sure, that's not copyright infringement. But, if you had memorized a bunch of code (and this is within human capability; people can recite many works of literature of varying length with total accuracy, given sufficient study) - that would be copyright infringement once the code was a non-trivial amount. The test in copyright is whether the copying is literal, not how the copying was done/did it pass through a human brain.
This scenario rarely comes up because humans are, generally, an awful medium for accurate repetition. However, it's not really been shown than LLMs are not: in fact, CoPilot claims (at least in its Enterprise agreements) to check its output _does not_ parrot existing code identically. The specific commitment they made in their blog post is/was, "We have incorporated filters and other technologies that are designed to reduce the likelihood that Copilots return infringing content". To be clear, they only propose to reduce the possibility, not remove it.
LLMs rely on a form of lossy compression which can sometimes give back verbatim content. I think it's pretty clear and unarguable that this is a copyright infringement.
Give credit where credit is due, including paying the creators when the licensing is violated.
... and has since joined the board of GitHub.
I am reading this right… ? If this argument is generally true, does this mean that the output of a compiler might also be sent into the public domain? Or the live recording and broadcast of an event which involves automated machines on all levels?
Can you expand on this? From my academic studies (which are indeed growing a bit stale) a Language Model (Large, Medium, Small doesn't matter) is a deterministic machine. Give the same x input n times it will produce the same output y, n times. Some implementations of LM:s might introduce noise to randomise output, but that is not intrinsic to all LM:s.
A language model has no volition, no intent, it does not start without the intervention of a human (or another machine if it is a part of an automated chain).
How is this different compared to a compiler?
With a compiler I craft something in a specific language, often a programming language, I commit it, then a long chain of automated actions happen:
1. The code gets automatically pushed to a repository by my machine
2. The second machine automatically runs tests and fuzzes
3. The second machine automatically compiles binaries
4. The second machine packages the binaries
5. The second machine publishes the binaries to a third machine
How is the above workflow any different from someone using a Language Model to craft something in a specific language and send it through a deterministic LM?
edit re-reading my own question, I think I need to clarify a bit: How can an LLM be said to create anything, and if yes, how is that really any different from a run-of-the-mill developer workflow?
AI is trying to avoid paying for training data since the amount of data required is so vast anything reasonable to content creators as payment would result in billions of expenses.
Additionally there have been copyright exemptions around scrapping and reproducing the scrapped contents but typically those exemptions have been explicitly granted as part of a copyright case and have been narrowly defined.
For instance Google Images only provides thumbnails and your browser gets the full size image from the original source.
The biggest problem for AI is that most previous copyright cases that were similar have all been partially avoided by not being the same thing. Google scrapping isn't trying to do the same thing your content is doing.
However training data output is trying to do the same thing as the original so falls under stricter scrutiny.
Although as this post eludes to the problem is going after the AI is untested territory and going after violators tends to be complex at best. After all in my first hypothetical how would anyone know? I will say that historically the courts haven't been very positive about shell games like this.
Furthermore, copyright is key to ensuring attribution, and attribution is an important enabler and motivator of creativity (copyleft does not at all imply non-attribution, in fact copyleft licenses may require it).
Not a "person". Not a "human". An "animal".
I hope AI observes all the code and complexity in Nature and drops the human facade. I hope AI understands the intelegence of the Trees and Birds and Fish.
I hope AI wins.
So we know for sure the LLM can spit out exact code with exact same names and comments, or exact paragraphs from books, so there is no question that it memorizes stuff and my explanation is that popular book quotes and popular code snippets will appear more then once in the training data so the training will cause to memorize this text.
Also how the F** can the AI spit facts about a metal band if it has no memory.
If corporations are allowed to do this to the community then we should allow to do the same, train open models on proprietary code and copyrighted images,music and videos.
And you are correct; if the current lawsuits against these corporations result in a legal precedence that training on copyrighted material is not an infringement of copyright, then yes, anyone will be able to train models in that way. (Within reason; copyright/fair use is very much handled on a case-by-case basis)
I suppose you are aware of the case with ChatGPT and Dune’s Litany Against Fear memorization and the lengths OpenAI went to try and prevent the people to reproduce the issue to prove it is happening. If not google it, do you disagree that is not memorization ? That somehow the model manages to create the exact same text each time because it memorized some abstract concepts that are not in fact the exact representation fo this text ?
Yes they _can_ and _do_ sometimes memorize. But they do not _only_ memorize which is what you implied with the statement I've quoted.
When people talk about AI and memory, they're not talking about the training phase or training data. When they talk about AI and memorization, they _are_ talking about the training phase and training data.
To answer your question: I _do_ think LLMs can memorize large-ish chunks of text. But: because in normal real world usage they do not output large chunks of their training data verbatim, I don't think there's a sufficient risk of plagiarism to be concerned.
I perfectly understand that the LLM developers do not want the LLM to store large chunk of text but the fact that the LLM can pull the text out exactly was proven , so even if we pretend the text was not "memorized" and we use some ridiculous verb like "it was quantum probabilistic ally vectorized" the issue is not fixed. If your LLM can reproduce my poem then it memorized it, AI bullshiters can use other word to cope but I do not give a shit, you need a mathematical proven training algorithm or even better good data to train your LLM to not reproduce copyrighted material. Renaming concepts is bullshit.
I'm not sure this is applicable to licensed programs because a book is sold, not licensed.
> The output of a machine simply does not qualify for copyright protection – it is in the public domain.
As far as I know, the output of a compiler that builds executables from copyrighted source code is still subject to copyright protection. Is software like an LLM fundamentally different from a compiler in this regard?
In my opinion, the author's argument has several flaws, but perhaps a more important question is whether society would benefit from making an exception for LLM technologies.
I think it depends on how this technology will be used. If it is intended for purely educational purposes and is free of charge for end users, maybe it's not that bad. After all, we have Wikipedia.
However, if the technology is intended for commercial use, it might be reasonable to establish common rules for paying royalties to the original authors of the training data whenever authorship can be clearly determined. From this perspective, it could further benefit authors of open-source and possibly free software too.
Felix was elected to the board of the Open Knowledge Foundation Germany in 2020. Felix is an expert in copyright law and has been Director of Developer Policy at GitHub since March 2024. He previously headed the “control ©” project at the Gesellschaft für Freiheitsrechte. From 2014 to 2019, Felix was a Member of the European Parliament within the Greens/EFA group. Felix is an Affiliate of the Berkman Klein Center for Internet and Society at Harvard University and a member of the Advisory Board of D64 - Center for Digital Progress.
There is definitely arguments to be made that Copilot contravenes this:
> they can be applied only in certain special cases that do not conflict with the normal exploitation of the works or other subject matter and do not unreasonably prejudice the legitimate interests of the rightholders.
and the only other exception is:
> ... (a lawful use) ... of a work or other subject-matter to be made, and which have no independent economic significance, shall be exempted from the reproduction right provided for in Article 2.
By laundering licensing restrictions copilot definitely has the ability to conflict with the normal exploitation of works and also doesn't have independent economic significance because it competes with programmers.
"Copyright law has only ever applied to intellectual creations – where there is no creator, there is no work."
This is the sort of thing that may be technically true but these kinds of rules were made under the assumption that most valued intellectual creations are indeed made by people, if you're going to argue that gigantic companies can use machines to basically launder intellectual artifacts, and that this doesn't compete with the interests of actual creators because technically ChatGPT isn't a legal person I think you're getting lost in legalese and missing the point
A US corporation is slurping up as much open source code as they possibly can and spending bucketloads of money to build a product that they are going to sell for (possibly) more bucketloads of money. The people who worked hard on writing the open source code are getting nothing, except maybe a tighter job market. IMHO, it's hard not to take it personally and it's difficult to get away from the feeling that there is a real injustice taking place.
Most of the time it is probably irrelevant, as Copilot doesn't suggest entire files yet, and nobody is going to care about expanding a loop or finishing a line or the likes, but I have seen as much as 14 lines in my tests. Eventually you are going to get to the point where it becomes truly relevant.
> Director of Developer Policy at GitHub since March 2024
so this should be understood the same way you understand an editorial in the New York Times entitled Why Babies Can Learn To Like Bombs, by Joe Blow (Raytheon).
That's a false analogy. It is more like going to the bookshop and taking a photo of every page of the book.
Even so, if you use this content in any shape or form the source should be cited regardless of book ownership.
LLMs seem to - with the right prompt- be able to reproduce copyrighted work. So it is “in there” in some abstract baked in sense.
We really need some sort of legal middle ground to reflect reality on the ground. It’s not quite straight stealing but it’s also not entirely not copied.
Even when the source is available, it is looked at by people, who write requirements based on what they observed in the code. After that, they are considered compromised, and are banned from ever touching the code of the re-implementation.
People would start releasing works of Art under GPL! Not just Computer Code!
Some discussion then: https://news.ycombinator.com/item?id=27736650
Microsoft will assume liability for legal copyright risks of Copilot
https://news.ycombinator.com/item?id=37420885
This week:
Judge dismisses DMCA copyright claim in GitHub Copilot suit
Do pro-generative AI people have absolutely no argument besides this? If I had a dollar for every time I've heard it, I'd be rich by now. And it's not even close to being a good argument.
They say it even though the standard response is: "When I buy a joint[1], I am breaking no laws. Does that make it legal for a corporation to purchase 200m tons of marijuana for profit?"
As far as legal concepts go, scale matters! Just because you are legally allowed to do something individually, does not automatically make it legal to do it for profit 200m times a month.
FCOL, before you even get to the scale argument, some things that are legal to do for free are not legal to do for profit.
[1] In my jurisdiction, anyway. Many others too.
" If you had so many dollars you would change your motto/ to say your account is 7 digits like you won the lotto/ buy vanilla ice and lick it like there's no tomorrow "
In hip-hop culture these lyrics could jog someone's memory of some Nas lyrics, some 8 mile battle songs maybe.
Could an AI come up with those awful lyrics? It sure could if it knew the specific Nas lyrics, 8 mile battle lyrics, knew about the lotto and twist the rules, what a motto is and so on.
Would it infringe any copyright by knowing the lyrics to Nas songs, 8 mile battle songs? According to you, yes. But I disagree.
Why hypocrites? Because I think artists (and coders) are always inspired by someone else's work and add their own experience, context, personality on top to create new work. Yes, generative AI is doing it a massive scale and democratizing most of the creative process, but to me it's the same thing even if, technically, it may be very crude and basic.
What absolute nonsense.
Dude got ripped into in his own comment section... apparently he conveniently ignored the fact that copilot spits out verbatim code blocks, which is the main problem everyone talks about.
I don't want to shit on the Pirate Party he is a member of, but most of his blogposts seems like the typical anti-EU bashing to me. But YMMV.
>The judge disagreed, however, on the grounds that the code suggested by Copilot was not identical enough to the developers' own copyright-protected work, and thus section 1202(b) did not apply.[...] >Judge Tigar earlier ruled the plaintiffs hadn't actually demonstrated instances of this happening, which prompted a dismissal of the claim with a chance to amend it.
[1] https://www.theregister.com/2024/07/08/github_copilot_dmca/
The machine, such as it is, is generally not acting on its own. A person operates the machine, and presumably is on the hook for infringement on some level.
Consider: what if one directs the machine to reproduce a specific body of code and it ostensibly does so. Was there copying?
What if I have a person read out that body of code and I type exactly what I hear? I used a machine to produce the resultant text file, but it's pretty clear that copying has occurred then.
FWIW, I'm not a copyright maximalist, but I don't think you can win a conflict by abstaining from playing the game the other team is playing. That is: the companies producing, and drawing incredible and exclusive economic value from, industrial scale plagiarism machinery are hardly going to stop ruthlessly enforcing copyright on their own proprietary software. It would seem best, if it's the goal, to get laws changed in advance of simply declaring, lopsidedly, that this is all fine.
Obviously LLMs are much more advanced than this, but in the basis it's still a machine that takes its input data and applies specified transformations with randomness.
Obviously, it seems impossible for an LLM user to verify the legality of the output, so it seems like the only conclusion is not to use it, or to only release your works under copyleft.
I guess an alternate interpretation is treating them like gun manufacturers. They aren't the ones pulling the trigger, but one could argue their business and marketing practices are done negligently enough for them to carry a portion of the responsibility. I guess then one must show that the LLM creators are sufficiently negligent in preventing misuse of their product at the same scale.
I.i.r.c. they even "give you a license" to use LLM output, implying that they own the copyright. Too lazy to look this up so I might be wrong there though.
The input to my algorithms is a single number, and the goal is to create something new and distinctive that is clearly different from anything that existed before, and that wouldn't exist without the ingenuity of my algorithms.
There's a reason why compression comparisons tend to include the size of the decompressor in their comparisons - my "magic algorithm can compress wikipedia down to a single bye!" is less impressive with the "decompressor" contains a copy of wikipedia.
The output of those algorithms isn't a creative work (as you're running a creative work to generate them, not applying any kind of creativity once the program is finished), so it's not protected. Same with generated code.
The lines get a bit blurry when you start applying a creative process onto the generated work. The edits you do on generated images in Photoshop may be considered creative work, as may the edits you do to generated code.
Protections only apply as far as copyright/trademark law can apply. In the case of generative AI and LLMs, it seems that copyright/trademark law doesn't consider the generated output to be a derivate work of the data model, or the model is not a derivative work of the input dataset. As a result, the output of generative AI doesn't seem to be restricted by the license of the training material.
In theory, a sufficiently powerful generative AI may be able to generate entire Disney movies, which would not be considered derivative works under the current laws, as far as I can tell. I'm sure the moment Disney gets threatened, AI copyright law will be updated, though.
So when (if) I release that game, anyone can just rip the assets, not even apply any transformation, and put them in their own product. I would have to let them do it with no legal recourse. That doesn't seem right.