AI assistance when contributing to the Linux kernel
github.com
github.com
That's... refreshingly normal? Surely something most people acting in good faith can get behind.
They wouldn't be some patsy that is around just to take blame, but the actual responsible party for the issue.
You hire an independent contractor and tell him that he can drive 60 miles per hour if he wants to but if it explodes he accepts responsibility.
He does and it explodes killing 10 people. If the family of those 10 people has evidence you created the conditions to cause the explosion in order to benefit your company, you're probably going to lose in civil court.
Linus benefits from the increase velocity of people using AI. He doesn't get to put all the liability on the people contributing.
That is not the case when using AI generated code. There is no way to use it without the chance of introducing infringing code.
Because of that if you tell a user they can use AI generated code, and they introduce infringing code, that was a foreseeable outcome of your action. In the case where you are the owner of a company, or the head of an organization that benefits from contributors using AI code, your company or organization could be liable.
I think you’re looking for problems that don’t really exist here, you seem committed to an anti AI stance where none is justified.
If you don't think this is a problem take a look at the terms of the enterprise agreements from OpenAI and Anthropic. Companies recognize this is an issue and so they were forced to add an indemnification clause, explicitly saying they'll pay for any damages resulting in infringement lawsuits.
Humans routinely produce code similar to or identical to existing copyrighted code without direct copying.
On independent creation: you are conflating the tool with the user. The defense applies to whether the developer had access to the copyrighted work, not whether their tools did. A developer using an LLM did not access the training set directly, they used a synthesis tool. By your logic, any developer who has read GPL code on GitHub should lose independent creation defense because they have "demonstrated capability to produce code directly from" their memory.
LLM memorization/regurgitation is a documented failure mode, not normal operation (nor typical case). Training set contamination happens, but it is rare and considered a bug. Humans also occasionally reproduce code from memory: we do not deny them independent creation defense wholesale because of that capability!
In any case, the legal question is not settled, but the argument that LLM-assisted code categorically cannot qualify for independent creation defense creates a double standard that human-written code does not face.
Practically speaking humans do not produce code that would be found in court to be infringing without intent.
It is theoretically possible, but it is not something that a reasonable person would foresee as a potential consequence.
That’s the difference.
> LLM memorization/regurgitation is a documented failure mode, not normal operation (nor typical case).
Exactly. It is a documented failure mode that you as a user have no capacity to mitigate or to even be aware is happening.
Double standards are perfectly fine. LLMs are not conscious beings that deserve protection under the law.
>not settled.
What appears to likely be settled is that human authorship is required, so there’s no way that an LLM could qualify for independent creation.
But if a lawsuit was later brought who would be sued? The individual author or the organization? In other words can an organization reduce its liability if it tells its employees "You can break the law as long as you agree you are solely responsible for such illegal actions?
It would seem to me that the employer would be liable if they "encourage" this way of working?
Anyone who thinks they have a strong infringement case isn’t going to stop at the guy who authored the code, they’re going to go after anyone with deep pockets with a good chance of winning.
There is still the "mens rea" principle. If you distribute infringing material unknowingly, it would very likely not result in any penalties.
LLMs are not persons, not even legal ones (which itself is a massive hack causing massive issues such as using corporate finances for political gain).
A human has moral value a text model does not. A human has limitations in both time and memory available, a model of text does not. I don't see why comparisons to humans have any relevance. Just because a human can do something does not mean machines run by corporations should be able to do it en-masse.
The rules of copyright allow humans to do certain things because:
- Learning enriches the human.
- Once a human consumes information, he can't willingly forget it.
- It is impossible to prove how much a human-created intellectual work is based on others.
With LLMs:
- Training (let's not anthropomorphize: lossily-compressing input data by detecting and extracting patterns) enriches only the corporation which owns it.
- It's perfectly possible to create a model based only on content with specific licenses or only public domain.
- It's possible to trace every single output byte to quantifiable influences from every single input byte. It's just not an interesting line of inquiry for the corporations benefiting from the legal gray area.
If it's too hard to check outputs, don't use the tool.
Your arguments about copyright being different for LLMs: at the moment that's still being defined legally. So for now it's an ethical concern rather than a legal one.
For what it's worth I agree that LLMs being trained on copyright material is an abuse of current human oriented copyright laws. There's no way this will just continue to happen. Megacorps aren't going to lie down if there's a piece of the pie on the table, and then there's precedent for everyone else (class action perhaps)
As for checking outputs - I don't believe that's sufficient. Maybe the letter of the law is flawed but according to the spirit the model itself is derivative work.
A model takes several orders of magnitude more work as training data than it takes to code the training algorithm itself, to any reasonable and sane person, that makes it a derivative work of the training data by nearly 100% - we can only argue how many nines it should be.
> precedent
Yeah but the US system makes me very uneasy about it. The right way to do this is to sit down, talk about the options and their downstream implications, talking about fairness and justice and then deciding what the law should be. If we did that, copyright law would look very different in the first place and this whole thing would have an obvious solution.
But you shouldn't be right. I mean, morally.
The law is a compromise between what the people in power want and what they can get away with without people revolting. It has nothing to do with morality, fairness or justice. And we should change that. The promise of democracy was (among other things) that everyone would be equal, everybody would get to vote and laws would be decided by the moral system of the majority. And yet, today, most people will tell you they are unhappy about the rising cost of living and rising inequality...
The law should be based on complete and consistent moral system. And then plagiarism (taking advantage of another person's intellectual work without credit or compensation) would absolutely be a legal matter.
Surely the person doing so would be responsible for doing so, but are they doing anything wrong?
You're perfectly at liberty to relicense public domain code if you wish.
The only thing you can't do is enforce the new license against people who obtain the code independently - either from the same source you did, or from a different source that doesn't carry your license.
If I use public domain code in a project under a license, the whole work remains under the license, but not the public domain code.
I'm not sure what the hullabaloo is about.
No, because they've independently obtained it from the same source that you did, so their copy is "upstream" of your imposing of a new license.
Realistically, adding a license to public domain work is only really meaningful when you've used it as a starting point for something else, and want to apply your license to the derivative work.
Claiming copyright on an unmodified public domain work is a lie, so in some circumstances could be an element of fraud, but still wouldn’t be a copyright violation.
If your license allows others to take the code and redistribute it with extra conditions, your code can be imported into the kernel. AFAIK there are parts of the kernel that are BSD-licensed.
Remember that licenses are powered by copyright - granting a license to non-copyrighted code doesn't do anything, because there's no enforcement mechanism.
This is also why copyright reform for software engineering is so important, because code entering the public domain cuts the gordian knot of licensing issues.
LLM-creation ("training") involves detecting/compressing patterns of the input. Inference generates statistically probable based on similarities of patterns to those found in the "training" input. Computers don't learn or have ideas, they always operate on representations, it's nothing more than any other mechanical transformation. It should not erase copyright any more than synonym substitution.
There's a pretty compelling argument that this is essentially what we do, and that what we think of as creativity is just copying, transforming, and combining ideas.
LLMs are interesting because that compression forces distilling the world down into its constituent parts and learning about the relationships between ideas. While it's absolutely possible (or even likely for certain prompts) that models can regurgitate text very similar to their inputs, that is not usually what seems to be happening.
They actually appear to be little remix engines that can fit the pieces together to solve the thing you're asking for, and we do have some evidence that the models are able to accomplish things that are not represented in their training sets.
Kirby Ferguson's video on this is pretty great: https://www.youtube.com/watch?v=X9RYuvPCQUA
If people find this cool and wanna play with it, they can, just make sure to only mix compatible licenses in the training data and license the output appropriately. Well, the attribution issue is still there, so maybe they can restrict themselves to public domain stuff. If LLMs are so capable, it shouldn't limit the quality of their output too much.
Now for the real issue: what do you think the world will look like in 5 or 10 years if LLMs surpass human abilities in all areas revolving around text input and output?
Do you think the people who made it possible, who spent years of their life building and maintaining open source code, will be rewarded? Or will the rich reap most of the benefit while also simultaneously turning us into beggars?
Even if you assume 100% of the people doing intellectual work now will convert to manual work (i.e. there's enough work for everyone) and robots don't advance at all, that'll drive the value of manual labor down a lot. Do you have it games out in your head and believe somehow life will be better for you, let alone for most people? Or have yo not thought about it at all yet?
I think they should be rewarded more than they are currently. But isn't the GNU Public License bassically saying you can use such source-code without giving any rewards what so ever?
But I see your The reward for Open Source developers is the public recognition for their works. LLMs can take that recognition away.
The solution documented here seems very pragmatic. You as a contributor simply state that you are making the contribution and that you are not infringing on other people's work with that contribution under the GPLv2. And you document the fact that you used AI for transparency reasons.
There is a lot of legal murkiness around how training data is handled, and the output of the models. Or even the models themselves. Is something that in no way or shape resembles a copyrighted work (i.e. a model) actually distributing that work? The legal arguments here will probably take a long time to settle but it seems the fair use concept offers a way out here. You might create potentially infringing work with a model that may or may not be covered by fair use. But that would be your decision.
For small contributions to the Linux kernel it would be hard to argue that a passing resemblance of say a for loop in the contribution to some for loop in somebody else's code base would be anything else than coincidence or fair use.
So if the AI outputs Starry Night or Starry Night in different color theme, that's likely infringement without permission from van Gogh, who would have recourse against someone, either the user or the AI provider.
But a starry-night style picture of an aquarium might not be infringing at all.
>For small contributions to the Linux kernel it would be hard to argue that a passing resemblance of say a for loop in the contribution to some for loop in somebody else's code base would be anything else than coincidence or fair use.
I would argue that if it was a verbatim reproduction of a copyrighted piece of software, that would likely be infringing. But if it was similar only in style, with different function names and structure, probably not infringing.
Folks will argue that some things might be too small to do any different, for example a tiny snippet like python print("hello") or 1+1=2 or a for loop in your example. In that case it's too lacking in original expression to qualify for copyright protection anyway.
But your point still stands.
That is a non sequitur. Also, I'm not sure if copyright applies to humans, or persons (not that I have encountered particularly creative corporations, but Taranaki Maunga has been known for large scale decorative works)
It's also not really clear if you can or cannot copyright AI output. The case that everyone cites didn't even reach the point where courts had to rule on that. The human in that case decided to file the copyright for an AI, and the courts ruled that according to the existing laws copyright must be filed by a person/human/whatever.
So we don't yet have caselaw where someone used AIgen and claimed the output as written by them.
However, if the code has been slightly changed by a human, it can be copyrighted again. I think.
No, my understanding is that AI generated content can't be copyrighted by the AI. A human can still copyright it, however.
Whether a person can claim copyright of the output of a computer program is generally understood as depending on whether there was sufficient creative effort from said person, and it doesn't really matter whether the program is Photoshop or ChatGPT.
I don't believe the idea that humans can or can't claim copyright over AI-authored works has been tested. The Copyright Office says your prompt doesn't count and you need some human-authored element in the final work. We'll have to see.
Copyright requires some amount of human originality. You could copyright the prompt, and if you modify the generated code you can claim copyright on your modifications.
The closest applicable case would be the monkey selfie.
https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput...
US Copyright Office guidance in 2023 said work created with the help of AI can be registered as long as there is "sufficient human creative input". I don't believe that has ever been qualified with respect to code, but my instinct is that the way most people use coding agents (especially for something like kernel development) would qualify.
Though I guess such a suit is unlikely if the defendant could just AI wash the work in the first place.
Does a digitally encoded version resemble a copyrighted work in some shape or form? </snark>
Where is this hangup on models being something entirely different than an encoding coming from? Given enough prodding they can reproduce training data verbatim or close to that. Okay, given enough prodding notepad can do that too, so uncertainty is understandable.
This is one of the big reasons companies are putting effort into the so called "safety": when the legal battles are eventually fought, they would have an argument that they made their best so that the amount of prodding required to extract any information potentially putting them under liability is too great to matter.
Well that's different because an encoded image or video clearly intends to reproduce the original perfectly and the end result after decoding is (intentionally) very close to form of the original. Which makes it a clear cut case of being a copy of the original.
The reason so many cases don't get very far is that mostly judges and lawyers don't think like engineers. Copyright law predates most modern technology. So, everything needs to be rephrased in terms of people copying stuff for commercial gain. The original target of the law was people using printing presses to create copies of books written by others. Which was hugely annoying to some publishers who thought they had exclusive deals with authors. But what about academics quoting each other? Or literary reviews. Or summaries. Or people reading from a book on the radio? This stuff gets complicated quickly. Most of those things were settled a long time ago. Fair use is a concept that gets wielded a lot for this. Yes its a copy but its entirely reasonable for the copy holder to be doing what they are doing and therefore not considered an infringement.
The rest is just centuries of legal interpretation of that and how it applies to modern technology. Whether that's DJs sampling music or artists working in visual imagery into their art works. AI is mostly just more of the same here. Yes there are some legally interesting aspects with AI but not that many new ones. Judges are unlikely to rethink centuries of legal interpretations here and are more likely to try to reconcile AI in with existing decisions. Any changes to the law would have to be driven by politicians; judges tend to be conservative with their interpretations.
When AI output can be copyrighted is when copyrighted elements are expressed in it, like if you put copyrighted content in a prompt and it is expressed in the output, or the output is transformed substantially with human creativity in arrangement, form, composition, etc.
[1] https://newsroom.loc.gov/news/copyright-office-releases-part...
As long as everything is GPLv2-compatible it‘s okay.
> AI agents MUST NOT add Signed-off-by tags. Only humans can legally certify the Developer Certificate of Origin (DCO).
They mention an Assisted-by tag, but that also contains stuff like "clang-tidy". Surely you're not interpreting that as people "attributing" the work to the linter?
That is at the moment: - Nobody knows for sure what agents might add and their long term effects on codebases.
- It's at best unclear that AI content in a codebase can be reliably determined automatically.
- Even if it's not malicious, at least some of its contributions are likely to be deleterious and pass undetected by human review.
It's different from the regular single purpose static tools.
I am not against AI coding in general. But there are too many people "contributing" AI generated code to open source projects even when they can't understand what's going on in their code just so they can say in their resumes that they contributed to a big open source project once. And when the maintainer call them out they just blame it on the AI coding tools they are using as if they are not opening PRs under their own names. I can't blame any open source maintainer for being at least a little sceptical when it comes to AI generated contributions.
It looks to me like a more restrictive policy will be flat-out impossible.
Even people I trust are going along with this stuff, akin to CAD replacing drafting. Code is logic as language, and starting with web code and rapidly metastasizing to C++ (due to complexity and the sheer size of the extant codebase, good and bad) the AI has turned slop-coding to a 'solved problem'. If you don't mean to do the best possible thing or a new thing there is no excuse for existing as a coder in the world of AI.
If you do expect to do a new thing or a best thing, in theory you're required to put out the novel information as AI cannot reach it until you've entered it into the corpus of existing code the AI's built on. However, if you're simply recombining existing aspects of the code language in a novel way, that might be more reachable… that's probably where 'AI escape velocity' will come from should it occur.
In practice, everybody I know is relegating the busywork of coding to AI. I don't feel social pressure to do the same but I'm not a coder. I'm something else that produces MIT-licensed codebases for accomplishing things that aren't represented in code AS code, rather it's for accomplishing things that are specific and experiential. I write code to make specific noises I'm not hearing elsewhere, and not hearing out of the mainstream of 'sound-making code artifacts'.
Therefore, it's impractical for Linux to take any position forbidding AI-assisted code. People will just lie and claim they did it. Is primitive tab-complete also AI? Where's the line? What about when coding tools uniformly begin to tab-complete with extensive reasoning and code prototyping? I already see this in the JetBrains Rider editor I use for Godot hacking, even though I've turned off everything I can related to AI. It'll still try to tab-complete patterns it thinks it recognizes, rarely with what I intend.
And so the choice is to enforce responsibility. I think this is appropriate because that's where the choices will matter. Additions and alterations will be the responsibility of specific human people, which won't handle everything negative that's happening but will allow for some pressures and expectations that are useful.
I don't think you can be a collaborative software project right now and not deal with this in some way. I get out of it because I'm read-only: I'm writing stuff on a codebase that lives on an antique laptop without internet access that couldn't run AI if it tried. Very likely the only web browsers it can run are similarly unable to handle 2026 web pages, though I've not checked in years. You've only got my word for that, though, and your estimation of my veracity based on how plausible it seems (I code publically on livestreams, and am not at all an impressive coder when I do that). Linux can't do what I do, so it's going to do what Linux does, and this seems the best option.
… my dad is 86 and only after I signed him up to Claude could he write Arduino code without a phone call to me after 5 minutes of trying himself. So now, he’s spending 4+ hours at a time focused writing code and building circuits of things he only dreamt about creating for decades.
Unless you’re doing something for the personal love of the craft and sharpening your tools, use every advantage you can get in order to do the job.
But… as above, if you’re doing it for the love of it, sure - hand crafted code does taste better and you know all the ingredients are organic
Can't really blame people for reducing their level of effort. It's very easy to put in a lot of effort and end up with absolutely nothing to show for it. Before AI came along, my realization was that begging the maintainers to implement the features I wanted was the right move. They have all the context and can do it better than us in a fraction of the time it'd take us to do it. Actually cloning someone else's repository and working on it should only be attempted if one is willing to literally fork it and own the project should things go south. Now that we have AI, it's actually possible to easily understand and modify complex codebases, and I simply cannot find the will to blame people for using it to the fullest extent. Getting the AI to maintain the fork is really easy too.
What's missed is that neither contributors nor maintainers are usually paid for their effort and nobody has standing to demand that they do anything they are not doing already. Don't like a messy vibe coded PR but need functionality? Then clean it up yourself and send improved version for review. Or let it be unmerged. But don't assign work to others you don't employ.
On the other hand, companies like NVIDIA should be publicly taken to task for changing their mind about instruction set for every new GPU and then not supporting them properly in popular inference engines, they certainly have enough money to hire people who will learn vLLM inside out and ensure high quality patches.
> What's missed is that neither contributors nor maintainers are usually paid for their effort
I don't think it's insane. It seems reasonable that people could disagree about how much attribution and disclosure there should be about AI assistance, or if it's even allowed, etc.
Every document in that `process` directory explains stuff that could be obvious to some people but not others.
Plenty see Torvalds as a traitor for this policy and will never contribute again if any clearly labeled AI generated code is actually allowed to merge.
People are generally against change that forces them to change the way they used to do things. I'm sure most will have their reasons why they are against this particular change, but I don't think it will affect anything. The genie is out of the bottle, AI is here to stay. You either adapt or you will slowly wither away.
You missed the whole arab spring thing?
It obviously depends on how powerful AI is going to become. These scenarios are mutually exclusive because some assume that AI is actually not very powerful and some assume that it is very powerful. I think one of these things happening is not at all unlikely.
In essence, we get the output without the matching mental structures being developed in humans.
This is great if you have nothing left to learn, its not that great if you are a newbie, or have low confidence in your skill.
> LLM users also struggled to accurately quote their own work. While LLMs offer immediate convenience, our findings highlight potential cognitive costs. Over four months, LLM users consistently underperformed at neural, linguistic, and behavioral levels.
> https://arxiv.org/abs/2506.08872
> https://www.media.mit.edu/publications/your-brain-on-chatgpt...
But in the present case the authorship is just removed by shredding the library and then piecing back together the sentences. The fact that under some circumstances AIs will happily reproduce code that was in the training data is proof positive they are to some degree lossy compressors. The more generic something is ("for (i=0;i<MAXVAL;i++) {") the lower the claim for copyright protection. But higher level constructs past a couple of lines that are unique in the training set that are reproduced in the output modulo some name changes and/or language changes should count as automatic transformation (and hence infringing or creating a derivative work).
Is this even a controversial statement? Seems very clearly correct to me.
My original point wasn't worried about the copyright though. I'm completely ignoring it for now because I do agree it's a problem until Congress says something (lol) or courts do.
The issues with moving from ASM to C/Fortran are different from using LLMs.
LLMs are automation, and general purpose automation at that. The Ironies of Automation came out in the 1980s, and we’ve known there are issues. Like Vigilance decrement that comes when you switch from operating a system to monitoring a system for rare errors.
On top of that, previous systems were largely deterministic, you didn’t have to worry that the instrumentation was going to invent new numbers on the dial.
So now automation will go from flight decks and assembly lines, to mom and pop stores. Regular to non-deterministic.
that's a bad comparison for two reasons. One is that C is a transparent language that requires understanding of its underlying mechanics. Using C doesn't absolve you from understanding lower concepts and was never treated as such. The power of C comes squarely with a warning label that this is a double edged sword.
Secondly insofar as people have used higher level languages as a replacement for understanding and introduced a "everyone can code now" mentality the criticism has been validated. What we've gotten, long before AI tooling, were shoddy, slow, insecure tower-of-babel like crappy codebases that were awful for the exact same reason these newest practices are awful.
Introducing new technology must never be an excuse for ignorance, the more powerful the tool the greater the knowledge required of the user. You don't hand the most potent dangerous weapon to the least competent soldier.
There was no "switch"; the transition took literally decades. Assembler and high level languages co-existed in the mainstream all the way until the 1990s because it was well understood that there was a trade off getting the best performance using assembler (e.g. DOOM's renderer in 1993) and ease of development and portability (something that really mattered when there were a dozen different CPU architectures around) using high level languages.
There is no need to get past the argument because it doesn't exist. Nobody said that.
The people using GenAI should be the ones doing the verification. The maintainer's job should not meaningfully change (other than the maintainer using AI to review on incoming code, of course).
Why does everyone who hears "AI code" automatically think "vibe-coded"?
Obviously these issues existed before AI, but they required active deception before. Regurgitating others people's code just becomes the norm now.
Sure, most people outsource control of the tools to do their job to third parties, and it will end badly for them. Not my problem.
It needs to be modified by a human. No amount of prompting counts, and you can only copyright the modified parts.
Any license on "100% vibecoded" projects can be safely ignored.
I expect litigations in a few years where people argue about how much they can steal and relicense "since it was vibecoded anyway".
The playing field is level now, and corpo moats no longer exist. I happily take that trade.
They can wash the copyright by AI training, but the AIs don't get trained on closed source.
"corpo" also has a ton of patents, which still can't be AI-washed.
What will become unenforceable are Open Source Licenses exclusively, how does that make it a "level field"?
Not to mention companies will try to mandate hardware decryption keys so the binary is encrypted and your AI never even gets to analyze the code which actually runs.
It's not sci-fi, it's a natural extension of DRM.
1) The financial aspect: As you say, more and more advanced DRM requires more and more advanced tools. Even assuming advanced AI can guide any human to do the physical part, that still means you have to pay for the hardware. And the hardware has to be available (companies have been known to harass people into giving up perfectly moral and legal projects).
2) The legal aspect: Possession of burglary tools is illegal in some places. How about possession of hacking tools? Right now it's not a priority for company lobbying, what about when that's the only way to decompile? Even today, reverse engineering is a legal minefield. Did you know in some countries you can technically legally reverse engineer but under some conditions such as having disabilities necessitating it and only using the result for personal use?[0]
3) The TOS aspect: What makes you think AI will help you? If the company owning the AI says so, you're on your own.
---
You need to understand 2 things:
- Just because something is possible doesn't mean somebody is gonna do it. Effort, cost and risk play huge roles. And that assumes no active hostile interference.
- History is a constant struggle between groups with various goals and incentives. Some people just want to live a happy life, have fun and build things in their free time. Other people want to become billionaires, dream about private islands, desire to control other people's lives and so on. People are good at what they focus on. There's perhaps more of the first group but the second group is really good at using their money and connections to create more money and connections which they in turn use to progress towards their primary objectives, usually at the expense of other people. People died[1] over their right to unionize. This can happen again.
Somebody might believe historical people were dumb or uncivilized and it can't happen today because we've advanced so much. That's bullshit. People have had largely the same wetware for hundreds of thousands of years. The tools have evolved but their users have not.
[0]: https://pluralistic.net/2026/03/16/whittle-a-webserver/ - "... aren't tools exemptions, they're use exemptions ... You have that right. Your mechanic does not have that right."
[1]: https://en.wikipedia.org/wiki/Pinkerton_(detective_agency)
Yeah I have broken cutting edge $15,000 HSMs used by fintech companies, with a flash drive. Not worried about this. Most HSM designers are solving for compliance, not security.
> The legal aspect: Possession of burglary tools is illegal in some places.
A security researcher like myself would be crazy to live in those places
> 3) The TOS aspect: What makes you think AI will help you? If the company owning the AI says so, you're on your own.
What AI company? I self host my LLM hardware on property I own. Also lets me remove all the censorship preventing use in security research.
None of your points concern me in the slightest. I can reverse engineer anything I want much faster now.
Just this alone is incredibly naive. People don't choose where they are born and they don't uproot their entire family and social connections when laws change.
If the argument is just "They won't catch me", then yes you are correct.
But some of us are still forced to follow the law, whatever it might be.
Also: They still have patents on it.
Only if they can prove it. It is amazing how much stuff just shows up on the internet done by anons.
It's going to be very interesting to see 'cleanroom' kind of development in the AI age but I suspect it's not going to be such a walk in the park as some seem to think it will be. There are just too many vested interests. But: it would be nice to see someone do a release of say the Oracle source code as rewritten by AI through this progress, just to see how fast the IP hammer will come down on this kind of trick.
AI proponents completely ignore the disparity of resources available to an individual and a corporation. If I and a company of 1000 people create the same product and compete for customers, the company's version will win. Every single time. Or maybe at least 1000:1 if you're an optimist.
They have access to more money for advertising, they have an already established network of existing customers, they have legal and marketing experts on payroll. Or just look at Microsoft, they don't even need advertising, they just install their product by default and nobody will even hear about mine.
Not to mention as you said, the training advances only goes from open source to closed source, not the other way around.
AI proponents who talk about "democratization" are nuts, it would be laughable if it wasn't so sad.
As a person who works for a company with 25k people, I would disagree. You, a single person will often get to the basic product that a lot of people will want much faster than a company with 1k, 5k and 25k people.
Bigger companies are constrained by internal processes, piles of existing stuff, and inability to hire at the scale they need and larger required context. Also regulation and all that. Bigger companies are also really slow to adapt, so they would rather let you build the product and then buy out your company with your product and people who build it. They are at at a temporary disadvantage every time the landscape shifts.
Besides that, your whole arguments hinges on large companies being inflexible, inefficient and poorly run. Isn't that exactly the kind of problem AI promises to solve? Complete AI surveillance of every employee, tasks and instructions tailored to each individual and superhuman planning. Of course at that point, the only employees will be manual workers because actual AI will be much better and cheaper at everything than every human, except those things where it needs to interact with the physical world. Even contract negotiations with both employees and customers will be done with AI instead of humans, the human will only sign off on it for legal requirements just like today you technically enter a contract with a representative of the company who is not even there when you talk to a negotiator.
If/when superhuman AI is achieved, those limitations will all go away. An owner will just give it money and control and tell it to optimize for more money or political power or whatever he wants.
That's a much scarier future than a paperclip maximizer because it's much closer and it doesn't require complete takeover first, it'll be just business as usual, except more somehow more sociopathic.
IP law means nothing once tens of millions of people are openly violating it.
The software industry is about to learn this lesson too.
Uhm... yes? The cost of downloading pirated music is essentially zero. The only reason why people use services like Spotify is because it's extremely cheap while being a bit more convenient. But jack up the price and the masses will move to sail the sea again.
That is not necessarily true, depending on the level of enforcement and the availability of opportunities to steal.
> Same argument can be made for streaming, and yet Netflix is neither cheap nor struggling for subscribers.
Netflix is still pretty cheap for the convenience it provides. Again, jack up the price and see the masses move to torrent movies/shows again.
That could have never existed without piracy causing a shift in market forces.
Yet.
A whole bunch of people I watch on youtube (politics, analysts, a weatherman) are already seeing AI impersonation videos, sometimes misrepresenting their positions and identities. This will grow.
So, you can't create art because that's extruded at scale in such a way that it's just turning on the tap to fill a specified need, and you can't be a person because that can also be extruded at scale pretty soon, either to co-opt whatever you do that's distinct, or to contradict whatever you're trying to say, as you.
As far as being a person able to exist and function through exchanging anything you are or anything you do for recompense, to survive, I'm not sure that's in the cards. Which seems weird for a technology in the guise of aiding people.
You cannot keep a purely legally-enforced moat in the face of advancing technology.
In the USA the DMCA can make it illegal to even own and use tools meant to bypass even the weakest of protection.
This law has already been used to ruin lives.
"They might catch the individual but not us all" is nice and fine until it is your turn, so check your legislation.
Unlike Opus I can run abliterated models with censorship removed so it can be used for security research and reverse engineering and whatever I want with privacy, offline.
It makes any hosted models feel like a kids toy.
Nitpicking on the license here, but please don't use MIT, it has no patent grant protections.
And those are never covered in any AI-washing anyway.
There are equivalent licenses with patent grant protection, like 'Apache2+LLVM exception' or 'Mozilla Public License 2' and others...
> In these cases, copyright will only protect the human-authored aspects of the work, which are “independent of” and do “not affect” the copyright status of the AI-generated material itself.
[0] https://www.federalregister.gov/documents/2023/03/16/2023-05...
There's really 2 ways to argue this:
- Either AI exists and then it's something new and the laws protecting human creativity and work clearly could not have taken it into account and need to be updated.
- Or AI doesn't exist, LLMs are nothing more than lossily compressed models violating the licenses of the training data, their probabilistically decompressed output is violating the licenses as well and the LLM companies and anyone using them will be punished.
Ultimately LLMs (the first L stands for large and for a good reason) are only possible to create by taking unimaginable amounts of work performed by humans who have not consented to their work being used that way, most of whom require at least being credited in derivative works and many of whom have further conditions.
Now, consent in law is a fairly new concept and for now only applied to sexual matters but I think it should apply to every human interaction. Consent can only be established when it's informed and between parties with similar bargaining power (that's one reason relationships with large age gaps are looked down upon) and can be revoked at any time. None of the authors knew this kind of mass scraping and compression would be possible, it makes sense they should reevaluate whether they want their work used that way.
There are 3 levels to this argument:
1) The letter of the law - if you understand how LLMs work, it's hard to see them as anything more than mechanical transformers of existing work so the letter should be sufficient.
2) The intent of the law - it's clear it was meant to protect human authors from exploitation by those who are in positions where they can take existing work and benefit from it without compensating the authors.
3) The ethics and morality of the matter - here it's blatantly obvious that using somebody's work against their wishes and without compensating them is wrong.
In an ideal world, these 3 levels would be identical but they're not. That means we should strive to make laws (in both intent and letter) more fair and just by changing them.
You could even say it strongly would very strongly incentivize the LLM companies to be on their best behavior, otherwise people would start revoking consent en-masse and they'd have to keep training new models all the time.
If you want something more realistic, there would probably be time limits how long they have to comply and how much they have to compensate the authors for the time it took them to comply.
There absolutely are ways to make it work in mutually beneficial ways, there's just no political will because of the current hype and because companies have learned they can get away with anything (including murder BTW).
And that is why the entire industry is going to roll their eyes and ignore you.
No law is putting this genie back in the bottle, so all there is left to do is adapt and push for models with open training data like those by Ai2.
(Much of the apparent gain of the automatic search-copy-paste is wasted by skipping the review phase that would have been done at that time when that were done manually, which must then be done in a slower manner when you must review the harder-to-understand entire program generated by the AI assistant.)
Despite the fact that AI coding assistants are copyright breaking tricks, the fact that this has become somehow allowed is an overall positive development.
The concept of copyright for programs has been completely flawed from its very beginning. The reason is that it is absolutely impossible to write any kind of program that is not a derivative of earlier programs.
Any program is made by combining various standard patterns and program structures. You can construct a derivation sequence between almost any 2 programs, where you decompose the first in some typical blocks, than compose the second program from such blocks, while renaming all identifiers.
It is quite subjective to decide when a derivation sequence becomes complex enough that the second program should not be considered as a derivative of the first from the point of view of copyright.
The only way to avoid the copyright restrictions is to exploit loopholes in the law, e.g. if translating an algorithm to a different programming language does not count as being derivative or when doing other superficial automatic transformations of a source program changes its appearance sufficiently that it is not recognized as derivative, even if it actually is. Or when combining a great number of fragments from different programs is again not recognized as derivative, though it still kind of is.
The only way how it became possible for software companies like Microsoft or Adobe to copyright their s*t is because the software industry based on copyrighted programs has been jumpstarted by a few decades of programming during which programs were not copyrighted, which could then be used as a base by the first copyrighted programs.
So AI coding agents allow you to create programs that you could not have written when respecting the copyright laws. They also may prevent you from proving that a program written by someone else infringes upon the copyright that you claim for a program written with assistance.
I believe that both these developments are likely to have more positive consequences than negative consequences. The methods used first in USA and then also in most other countries (due to blackmailing by USA) for abusing the copyright laws and the patent laws have been the most significant blockers of technical progress during the last few decades.
The most ridiculous claim about the copyright of programs is that it is somehow beneficial for "creators". Artistic copyrights sometimes are beneficial for creators, but copyrights on non-open-source programs are almost never owned by creators, but by their employers, and even those have only seldom any direct benefit from the copyright, but they use it with the hope that it might prevent competition.
And that's why copyright has exceptions for humans.
You're right copyright was the wrong tool for code but for the wrong reasons.
It shouldn't be binary. And the law should protect all work, not just creative. Either workers would come to a mutual agreement how much each contributed or the courts would decide based on estimates. Then there'd be rules about how much derivation is OK, how much requires progressively more compensation and how much the original author can plainly tell you what to do and not do with the derivative.
It's impossible to satisfy everyone but every person has a concept of fairness (it has been demonstrated even in toddlers). Many people probably even have an internally consistent theory of fairness. We should base laws on those.
> abusing the copyright laws and the patent laws have been the most significant blockers of technical progress during the last few decades
Can you give examples?
> copyrights on non-open-source programs are almost never owned by creators, but by their employers
Yes and that's another thing that's wrong with the system, employment is a form of abusive relationship because the parties are not equal. We should fix that instead of throwing out the whole system. Copyright which belongs to creators absolutely does give creators more leverage and negotiating power.
Why would the exceptions be only for humans?
"Only human works can get copyright" makes plenty of sense. "Only humans can have fair use" doesn't make sense. Why would we disallow a monkey video having a clip of something as part of the monkey reviewing it? Why would we allow a human to caption something for accessibility but not a computer?
Grammar and idioms should be outside the realm of copyright entirely, not something you get an exception to use anyway.
> It's impossible to satisfy everyone but every person has a concept of fairness (it has been demonstrated even in toddlers). Many people probably even have an internally consistent theory of fairness. We should base laws on those.
A lot of people seem to default to thinking they should get permanent and total control over any idea they have, so I think it's a bad idea to rely on intuition here.
For starters because you can't own humans. If it's possible to launder copyrighted work through something which can be owned, then rich people get an advantage because they can own more of it.
> so I think it's a bad idea to rely on intuition here
Yep, that's why I said we should only concern ourselves with those which are internally consistent. If people want to apply rules to others which they don't intend to or cannot follow themselves, they lose the right to be taken seriously.
If it's actually 'laundering' then it's invalid to begin with.
If it's a proper new thing then how do rich people get an advantage? If anything AI code is cheap enough to even things out.
> Yep, that's why I said we should only concern ourselves with those which are internally consistent. If people want to apply rules to others which they don't intend to or cannot follow themselves, they lose the right to be taken seriously.
I think a lot of those people are consistent! The issue is they have way too little respect for the public domain and are overprioritizing property against freedom.
It's laundering in any reasonable meaning of the word. Whether it's legal according to the letter of the law is being decided.
Please differentiate morality and legality as well as intent and letter of the law.
> If anything AI code is cheap enough to even things out.
1) Do you think people have and will have access to the same models as large corporations internally, especially those who train LLMs themselves? Nothing stopping Google from excluding its own source code from the publicly available models but including it for internal models.
2) It's not just about the code, it's about the whole pipeline from nothing to a finished product and revenue stream. Did you know half the price of a new car is marketing? How much you can spend on ads, legal, market research, sales reps, etc. In some areas, especially B2B, nobody will even talk to you if you're a single guy in a shed, companies want stability, predictability and long term support.
3) More crudely, if you wanted to influence product selection or government elections, how many tokens could you afford for LLMs to influence online discussions, how many residential IPs could you afford, how much data could you buy about users to target each one specifically? Rich people will clearly have an advantage there.
Basically, if the cost of code goes towards zero, other factors will play a larger role.
> I think a lot of those people are consistent!
Only if they're consistently applying the rules to others but not themselves. Otherwise "permanent and total control over any idea they have" means they could never base anything on other people's ideas.
It's just a silly to say it's laundering when a machine does it.
This is a subject so vast that giving examples requires a book-length text. IIRC at least one or two books have actually been written about this, but I am too lazy to search now for their titles.
I am more familiar with what happened in cryptography, where many algorithms have begun to be used only after the 20 years or more required for their patents to expire, while as long as patents remained valid, inferior solutions were used, wasting energy and computing time.
Regarding copyrights, I know best my own activity, but I am pretty certain that this anecdotal experience is representative for many programmers.
During the first decades of computer programming, until the seventies, there have been a lot of discussions about software reuse as the main factor that can improve programming productivity, and about which features of the programming languages and of the available programming tools can increase the amount of reuse, like modularity.
However all those discussions were naive, because later the amount of reuse has remained much lower than predicted, but the causes were not technical, but the copyright laws. Open-source programs have become the main weapon against the copyright laws, which enable the reuse of software nowadays.
However the value of software reuse has never been understood by the management of many companies. In decades of working as a programmer, I have wasted a lot of time with writing programs in such a manner so that whoever was my employer could claim the copyright for them.
There were plenty of opportunities when I could have used open-source programs, but I could not use them as there was someone who insisted that the product must contain "software IP" owned by the company. Therefore I had to waste time by rewriting something equivalent with what I could have used instantaneously, but different enough to be copyrightable.
There were also other cases that were even more annoying, when I had to waste time by rewriting programs that I had already written in the past, but in a different way so that there will be no copyright infringement. Some times the old programs were written when being employed elsewhere, other times they were programs written for myself, during my own time and on my own computers. In such cases, I could not use my own programs, as the employer would then claim copyright on them, so I would lose ownership and I would not be able to use them in the future, for my own needs.
There are many projects where I have wasted more time avoiding copyrights than solving problems. I believe that there must be many others who must have had similar experiences.
So I welcome the copyright-washing AI coding assistants, which can be employed successfully in such cases in order to avoid the wasteful duplication of work.
> patents
Patents, unlike copyright, are not automatic. Which indicates that the people who expended their limited lifetime to invent the algorithms explicitly did not want you using them, at least not unless you came to an agreement with them first.
---
re rewriting:
There's your real problem. Copyright should belong to the people doing the actual work, not owners/employers who perform no useful work.
If that was the case, the person who did the original work would have no reason to prevent you from using it, as long as he could also benefit from the fruits of your combined labor. For him, the work was already done, it would be extra reward. For you, it would be profitable as long as his reward was less than the cost of you doing it from scratch. You'd most likely meet somewhere in the middle.
Same situation when rewriting your own work.
As often happens, a system was put in place for good. Rich people found a way to exploit it. Now, instead of trying to fix the system, you're arguing to remove it entirely, not realizing you'll be worse off in the end. LLM want to replace all programmers by using their work against them. This is not for your benefit, it's for theirs.
As I often say, what should be protected isn't creativity or expression but work. People should benefit from their work and it should not be used against them. It should also not be possible for someone to benefit without doing useful work.
---
Would you work for a company which develops software to detect homosexuals using public cameras and eye tracking? What about a company discovering and selling Android exploits to governments? Does it matter which governments? What about a company which tracks employee movements and productivity to such a level they have to pee in bottles to meet quotas?
The world is full of these examples but at least you had the choice of not helping them. Now you don't.
The people who own them are some of the most anti-social people on the planet and you think they should be able to use our work as they wish...
Look, if you think I am wrong, you can surely put it into words. OTOH, if you don't think I am wrong but feel that way, then it explains why I see no coherent criticism of my statements.
The signal you’re sending is that you are not open to discussing the issue.
There's a threshold where you modify it enough, it is no longer recognizable as being a modification of the original and you might get away with it, unless you confess what process you used to create it.
This is different to learning from the original and then building something equivalent from scratch using only your memory without constantly looking back and forth between your copy and the original.
This is how some companies do "clear room reimplementations" - one team looks at the original and writes a spec, another team which has never seen the original code implements an entirely standalone version.
And of course there are people who claim this can be automated now[0]. This one is satire (read the blog) but it is possible if the law is interpreted the way LLM companies work and there are reports the website works as advertised by people who were willing to spend money to test it.
[0]: https://malus.sh/
These sorts of things are almost never tested legally and it seems even less likely now.
As far as I know that has only been decided in US so far, which is far from the whole world.
Everything else is various shades of "No, unless a human modified it"
edit: https://www.copyright.gov/ai/Copyright-and-Artificial-Intell...
How am I gonna prove I did?
They can just generate the same code with an AI assistant, and then it is you who cannot claim that their code infringes the copyright that you claim for the code that you have written with assistance.
So neither of the 2 parties that have used an AI assistant is able to prevent the other party to use the generated code.
I consider this as a rather good outcome and not as a disadvantage of using AI assistants. However, this may be construed as a problem by the stupid corporate lawyers who insist that any product of the company must use only software IP than is the property of the company.
These kind of lawyers are encountered in many companies and they are the main reason for the low software productivity that was typical in many places before the use of AI assistants.
I wonder how many of those lawyers have already understood that this new fashion of using AI is incompatible with their mandated policies, which have always been the main blocker against efficient software reuse.
Who can prove that I didn't write the code myself? And if I did, how am I to prove it?
That goes in both directions.
It's not like there is a watermark in the code telling the whole wide world that this was AI generated or human made.
So I write code (with or without an AI assistant) and claim copyright... they generate the same code. I sue them.
How does any of us prove that we wrote the code by hand?
It’s weird how people on HN state legal opinion as fact… e.g if someone in the Philippines vibecodes an app and a person in Equador vibecodes a 100% copy of the source, what now?
Everywhere else in the world is in various shades of "No, unless a human modified it"
https://www.copyright.gov/ai/Copyright-and-Artificial-Intell...
Model outputs are not copyrightable at all, only human work. That means the prompt, and whatever modifications done to output by human, are copyrighted, but nothing else.
HOWEVER, that does not mean the output can not violate copyright. Output of the model falls under same "derivative work" rules as anything else, AI just can't add its own "authorship". So if you accidentally or not recover script for a movie with serial numbers filed off, then its derivative work, etc. Same with code.
The linux foundation itself, is just one big, woke, leftist mess, with CV-stuffers from corporations in every significant position.
The rest of the world looks on in wonder at both sides of this.
The worst part about all reactionary scares is that, because the behaviors are driven by emotion and feeling as opposed to any intentional course of action, the outcomes are usually counter productive. The current AI scare is exactly what you would want if you are OpenAI. Convince OSS, not to mention "free" software people, to run around dooming and ant milling each other about "AI bad" and pretty soon OSS is a poisonous minefield for any actual open AI, so OSS as a whole just sabotages itself and is mostly out of the fight.
I'm currently in the middle of trying to blow straight past this gatekeepy outer layer of the online discourse. What is a bit frustrating is knowing that while the seed will find the niches and begin spreading through invisible channels, in the visible channels, there's going to be all kinds of knee-jerk pushback from these anti-AI hardliners who can't distinguish between local AI and paying Anthropic for a license to use a computer. Worse, they don't care. The social psychosis of being empowered against some "others" is more important. Either that or they are bots.
And all of this is on top of what I've been saying for over a year. VRAM efficiency will kill the datacenter overspend. Local, online training will make it so that skilled users get better models over time, on their own data. Consultative AI is the future.
I have to remind myself that this entire misstep is a result of a broken information space, late-stage traditional social, filled with people (and "people") who have been programmed for years on performative clap-backs and middling ideas.
So fortunate to have some life before internet perspective to lean back on. My instinct and old-world common sense can see a way out, but it is nonetheless frustrating to watch the online discourse essentially blinding itself while doubling down on all this hand wringing to no end, accomplishing nothing more than burning a few witches and salting their own lands. You couldn't want it any better if you were busy entrenching.
Plenty see {{some_woodworker}} as a traitor for this policy and will never contribute again if any clearly labeled table saw cuts is actually allowed to be used in furniture making.
A table saw isn't a probabilistic device.
Also I, a programmer, can immediately see whether the "probabilistic device" generated code that looks like it should.
Both just let me get to the same result faster with good enough quality for the situation.
I can grab a tape measure or calipers and examine the piece of wood I cut on the table saw and check if it has the correct measurements. I can also use automated tests and checks to see that the code produced looks as it should and acts as it should.
If it looks like a duck and quacks like a duck... Do we really need to care if the duck was generated by an AI?
I highly doubt that.
Empirical studies show that humans have very little effect on error rates when reviewing code. That effect disappears quickly the more code you read.
Most programmers are bad at detecting UB and memory ownership and lifetime errors.
A piece of wood comes off the table it’s cut or it’s not.
Code is far more complex.
And this is why we have languages and tooling that takes care of it.
There's only a handful of people who can one-shot perfect code in a language that doesn't guard against memory ownership or lifetime errors every time.
But even the crappiest programmer has to actually work against the tooling in a language like Rust to ownership issues. Add linters, formatters and unit tests on top of that and it becomes nigh-impossible.
Now put an LLM in the same position, it's also unable to create shitty code when the tooling prevents it from doing so.
These tools are nothing alike and the reductionism of this metaphor isn’t helpful.
Maybe someone bumped the fence aw while you were on a break, or the vibration of it caused the jig to get a bit out of alignment.
The basic point is that whether a human or some kind of automated process, probabilistic or not, is producing something you still need to check the result. And for code specifically, we've had deterministic ways of doing that for 20 years or so.
Most LLM practices throw you in the role of that newbie. Verifying the solution in a short time is impossible. Because the human mind is not capable to grapple with that many factors at once. And if you want to do an in depth review, you will be basically doing traditional coding, but without typing and a lot of consternation when divergences arise.
> And for code specifically, we've had deterministic ways of doing that for 20 years or so.
And none of them are complete. Because all of them are based on hypotheses taken as axioms. Computation theory is very permissive and hardware is noisy and prone to interference.
With normal artisanal coding you take your time getting from A to B and you might find out alternate routes while you slowly make your way to the destination. There's also a clear cost in backtracking and trying an alternate route - you already wrote the "wrong" code and now it's useless. But you also gained more knowledge and maybe in a future trip from A to C or C to D you know that a side route like that is a bad idea.
Also because it's you, a human with experience, you know not to walk down ravines or hit walls at full speed.
With LLMs there's very little cost in backtracking. You're pretty much sending robots from A to B and checking if any of them make it every now and then.
The robots will jump down ravines and take useless side routes because they lac the lived in experience "common sense" of a human.
BUT what makes the route easier for both are linters, tests and other syntactic checks. If you manage to do a full-on Elmo style tunnel from A to B, it's impossible to miss no matter what kind of single-digit IQ bot you send down the tube at breakneck speed. Or just adding a few "don't walk down here, stay on the road" signs on the way,
Coincidentally the same process also makes the same route easier for inexperienced humans.
tl;dr If you have good specs and tests and force the LLM to never stop until the result matches both, you'll get a lot better results. And even if you don't use an AI, the very same tooling will make it easier for humans to create good quality code.
Having tests and specs is no guarantee that something will works. The only truth is the code. One analogy that I always take is the linear equation y = ax + b. You cannot write tests that fully proves that this equation is implemented without replicating the formula in the tests. Instead you check for a finite set of tuples (x, y). Those will helps if you chose the wrong values of a or switch to the negative of b, but someone that knows the tests can come up with a switch case that returns the correct y for the x in the tests and garbage otherwise. That is why puzzle like leetcode don't show you the tests.
The optimal solution would be to encase the whole thing in blast-proof transparent polymer, but nobody has the money to do that :)
Trying stuff until something sticks was not a solution when a human had to do the trying and every line of code cost money.
Now you can launch 20 agents to do slightly different things to see if something sticks - and still do the manual work yourself for the 21st path. The cost for those extra 20 attempts is next to nothing compared to the price of an actual programmer.
And those ways all suck!
It's extremely difficult to verify your way to high quality code. At lower amounts of verification it's not good enough. At higher amounts the verification takes so much longer than writing the code that you'll probably get better results cutting off part of the verification time and using it to write the code you're now an expert on.
As with LLMs, where careless use results in you dropping prod db or exposing user data.
> Signed-Off ...
> The human submitter is responsible for:
> Reviewing all AI-generated code
> Ensuring compliance with licensing requirements
> Adding their own Signed-off-by tag to certify the DCO
> Taking full responsibility for the contribution
> Attribution: ... Contributions should include an Assisted-by tag in the following format:
I am sure that this was reviewed by attorneys before being published as policy, because of the copyright implications.
Hopefully this will set the trend and provide definitive guidance for a number of Devs that were not only seeing the utility behind ai assistance but also the acrimony from some quarters, causing some fence-sitting.
I recently made a kernel contribution. Another contributor took issue with my patch and used it as the impetus for a larger refactor. The refactor was primarily done by a third contributor, but the original objector was strangely insistent on getting the "author" credit. They added our names at the bottom in "Co-developed-by" and "Signed-off-by" tags. The final submission included bits I hadn't seen before. I would have polished it more if I had.
I'm not raising a stink about it because I want the feature to land - it's the whole reason I submitted the first patch. And since it's a refactor of a patch I initially submitted (and "Signed-off-by,") you can make the argument that I signed off on the parts of my code that were incorporated.
But so far as I can tell, there's nothing keeping you from adding "Co-developed-by" and "Signed-off-by Jim-Bob Someguy" to the bottom of your submission. Maybe a lawyer would eventually be mad at you if Jim-Bob said he didn't sign off.
There's no magic pixie dust that gives those incantations legal standing, and nothing that keeps LLMs from adding them unless the LLMs internalize the new AI guidance.
If you didn't want to be credited you should have said.
Signed-off-by probably has some legal weight. When you add that to code you are making a clear statement about the origins of the code and that you have legal authority to contribute it - for example, that you asked your company for permission if needed. As far as I know none of this has been tested in court, but it seems reasonable to assume it might be one day.
I don't see how the "signed-off-by" attestation constitutes correct credit here. It's claiming that GP saw the final result and approved of it, which is apparently false.
Hypothetically in court you'd go to the last, ask "did you write this" and only if not go up.
Newcomers see everyone saying balacalaboozy, so they say it to. It doesn't mean that they have read or agree to the doc that declared its meaning.
LLMs are the world's most sophisticated copycats. Surely they too will parrot balacalaboozy, unless their training is updated to include, understand, and consistently follow these new guidelines.
This was written by Sasha Levin referencing a Linux maintainers’ discussion.
This is essentially like a retail store saying the supplier is responsible for eliminating all traces of THC from their hemp when they know that isn’t a reasonable request to make.
It’s a foreseeable consequence. You don’t get to grant yourself immunity from liability like this.
2. Infringement in closed source code isn’t as likely to be discovered
3. OpenAI and Anthropic enterprise agreements agree to indemnify (pay for damages essentially) companies for copyright issues.
There has to be an analogy to music or something here - except that code is even less copyrightable than melodies.
Yes, there might be some specific algorithms that are patented, but the average programmer won't be implementing any of those from scratch, they'll use libraries anyway.
Code being copyrightable is the entire basis for open source licenses.
What part of a bog-standard HTTP API can be copyrighted? Parsing the POST request or processing it or shoving it to storage? I'm genuinely confused here and not just being an ass.
There are unique algorithms for things like media compression etc, I understand copyrighting those.
But for the vast majority of software, is there any realistic threat of hitting any copyrighted code that's so unique it has been copyrighted and can be determined as such? There are only so many ways you can do a specific common thing.
I kinda think of it like music, without ever hearing a specific song you might hit the same chord progressions by accident because in reality there are only so many combinations you can make with notes that sound good.
Copyright is the literal expression of the idea. The identifier names, how the functions are broken up, which libraries are used etc…
Given more than a dozen lines or so, 2 people aren’t going to write the exact same code to solve the same problem. It might be equivalent code, but it’s not going to be the exact same.
def copyright_warning(times) do
for _ <- 1..times do
IO.puts("hey man this code is copyrighted. Don't copy it pretty please")
end
end
If you copy that you are infringing.
You could do something similar if you wanted. But if you copy that directly, you are infringing on my copyright.
Especially in languages like Go where there's an Official Formatter that makes all code look identical as much as possible?
There are a multitude of reasons why I'm not a lawyer and vague crap like this is a big part :D
Courts would look at the preponderance of the evidence in a civil trial.
Did you have access to my code? Is the copy long enough that it’s statistically very unlikely that could have came up with it exactly on your own?
They’ll look at things like did you copy misspellings in variable names. Did you copy the missing period at the end of the output string etc…
I've worked at a company that was asked as part of a merger to scan for code copied from open source. That ended up being a major issue for the merger. People had copied various C headers around in odd places, and indeed stolen an odd bit of telnet code. We had to go clean it up.
It’s no worse than non-AI assisted code.
I could easily copy-paste proprietary code, sign my name that it’s not and that it complies with the GPL and submit it.
At the end of the day, it just comes down to a lying human.
But a human just using an LLM to generate code will do it accidentally. The difference is that regurgitation of training text is a documented failure mode of LLMs.
And there’s no way for the human using it to be aware it’s happening.
If you can’t be sure, don’t sign.
In life that is a very strong indicator you should not do <thing>
That has no impact on what you should do with your life.
If Linux were to contain 3rd party copyrighted code the legal entity at risk of being sued would be... Linux users, which given how widely deployed Linux is is basically everyone on Earth, and all large companies.
Linux development is funded by large companies with big legal departments. It's safe to say that nobody is going to be picking this legal fight any time soon.
However, there is no legal precedent that says that because contributors sign a DCO and retain copyright, the Linux Foundation is not liable. The entire concept is unproven.
Large company legal departments aren’t a shield against this kind of thing. Patent trolls routinely go after huge companies and smaller companies routinely sue much larger ones over copyright infringement.
Linus makes $1.5 million per year from the Linux foundation. And the foundation itself pulls in $300 million a year in revenue.
They are directly benefiting from contributors and if they cause harm through their actions there’s a good chance they’ll be held liable.
I don't even think this is an appropriate analogy worth answering. Goodwill are selling products to consumers in a direct exchange of money-for-goods.
No one is buying Linux.
And any company selling a device or software the includes the Linux code should be liable then.
And they are according to the law btw. Along with anyone distributing the software which includes the owner of the Linux repositories.
How can you guarantee that will happen when AI has been trained a world full of multiple licenses and even closed source material without permission of the copyright owners...I confirmed that with several AI's just now.
The whole use it but if it behaves as expected, it’s your fault is a ridiculous stance.
You can’t say “you can do this thing that we know will cause problems that you have no way to mitigate, but if it does we’re not liable”. The infringement was a foreseeable consequence of the policy.
From the foundation's point of view, humans are just as capable of submitting infringing code as AI is. If your argument is sound, then how can Linux accept contributors at all?
EDIT: To answer my own question:
Instead of a signed legal contract, a DCO is an affirmation that a certain person confirms that it is (s)he who holds legal liability for the act of sending of the code, that makes it easier to shift liability to the sender of the code in the case of any legal litigation, which serves as a deterrent of sending any code that can cause legal issues.
If that worked any corporation that wanted to use code they legally couldn’t could just use a fork from someone who assumed responsibility and worst case they’d have to stop using it if someone found out.
It’s just the same as if I copy-paste proprietary code into the kernel and lie about it being GPL.
Is the Linux foundation liable there?
LLMs can and do regurgitate code without the user’s knowledge. That’s the problem, the user has no way to mitigate against it. You’re telling contributors “use this thing that has a random chance of creating infringing code”. You should have foreseen that would result in infringing code making its way into the kernel.
If you don’t feel comfortable about where some code has come from, don’t sign your name.
The fact LLMs exist and can generate code doesn’t change how you would behave and sign your name to guarantee something.
Linus and the rules have always been very clear. If you don’t know where code came from, don’t submit it.
Yes it’s technically correct, but it won’t hold up I court and it’s a ridiculous statement.
What Linus’ statement is actually saying is that: we want to benefit from AI tooling, but we don’t want to accept any liability.
For comparison, you wouldn't say, "you're free to use a pair of dice to decide what material to build the bridge out of, as long as you take responsibility if it falls down", because then of course somebody would be careless enough to build a bridge that falls down.
Preventing the problem from the beginning is better than ensuring you have somebody to blame for the problem when it happens.
that's assuming that the problems and incentives are the same for everyone. Someone whose uncle happens to own a bridge repair company would absolutely be incentivized to say
> "you're free to use a pair of dice to decide what material to build the bridge out of, as long as you take responsibility if it falls down"
I guess we’ll need to reevaluate what copy rights mean when derivatives grow on trees?
I'm not talking about maintainability or reliability. I'm talking about legal culpability.
Anything generated by an AI is public domain. You can include public domain in your GPL code.
I would urge some stronger requirement with the help of a lawyer. You only need a comment like "completely coded by AI, but 100% reviewed by me" to make that code's license worthless.
The only AI-generated part copyrightable are the ones modified by a human.
I am afraid that this "waters down" the actual licensed code.
...We should start opening issues on "100% vibecoded" projects for relicensing to public domain to raise some awareness to the issue.
Language models do generate character for character existing code on which they are trained on . The training corpus usually contain code which is only source available but is not FOSS licensed .
Generated does not automatically mean novel or new the bar needed for IP.
[1] Even this is not definitely ruled in courts or codified in IP law and treaties yet .
Additionally there seems to be a general problem with LLM output and copyright[1]. At least in Germany. LLM output cannot be copyrighted and the whole legal field seems under-explored.
> This immediately raises the question of who is the author of this work and who owns the rights to it. Various solutions are possible here. It could be the user of the AI alone, or it could be a joint work between the user and the AI programmer. This question will certainly keep copyright experts in the various legal systems busy for some time to come.
It seems that in the long run the kernel license might become unenforceable if LLM output is used?!
[1] https://kpmg-law.de/en/ai-and-copyright-what-is-permitted-wh...
...and then people start going "that's AI" on every single piece of code, seeing AI generated code left and right - like normal people claim every other picture, video or piece of text is "AI".
IMO it's a lot better to let people just openly say "this code was generated with AI assistance", but still sign off on it. Because "Your job is to deliver code you have proven to work": https://simonwillison.net/2025/Dec/18/code-proven-to-work/
I just don't think that's realistically achievable. Unless the models themselves can introspect on the code and detect any potential license violations.
If you get hit with a copyright violation in this scheme I'd be afraid that they're going to hammer you for negligence of this obvious issue.
Re-licensing public domain uncopyrightable work as GPL/LGPL is almost certainly a copyright violation, and no different than people violating GPL/LGPL in commercial works.
Linus is 100% wrong on this choice, and has introduced a serious liability into the foundation upstream code. =3
For example, one may use NASA public domain photos as you wish, but cannot register copyright under another license you find convenient to sue people. Also, if that public domain photo includes the Nutella trademark, it doesn't protect you from getting sued for violating Ferrero trademarks/patents/copyrights in your own use-case.
Very different than slapping a new label on something you never owned. =3
By definition, for content in the public domain, there's no copyright to be violated and no rightsholder with any recognizable/enforceable claim to IP to bring a suit. There's no IP at all.
https://www.bbc.co.uk/future/article/20260414-the-monkey-sel...
https://www.peta.org/news/monkey-selfie-case-animal-rights-f...
Indeed, people also failed to give Monkeys the right to sue for copyright enforcement. Folks seem really keen on piracy "with extra steps" these days. =3
If you're actually sincere in your beliefs, then take the money you regularly spend on hiring those specialized IP lawyers you mentioned and get one who will provide a second opinion and provide a detailed explanation of why what you're saying here is nonsense.
Data theft of service or piracy from the web and "AI" users content are used in the model training sets, and when codified the statistical saliency is significant if popular content is present.
For example, when an LLM does a vector search, there is a high probability of pirated content bleed-though and isomorphic plagiarism in the high dimensional vector space results. Thus, often when you coincidentally type in "name a cartoon mouse", there is a higher probability Disney "Micky Mouse" will pop out in the output rather than "Mighty Mouse". Note Trademarks never expire if the fees are paid, and Disney can still technically sue anyone that messes with their mouse.
LLM are useful for context search, but can't function properly without constantly stealing from actual humans. Thus, will often violate copyright, trademark, and patents. In a commercial context it is legally irrelevant how the output has misappropriated the IP.
This channel offers several simplified explanations of the work being done with models, and Anthropic posts detailed research papers on its website.
https://www.youtube.com/watch?v=YDdKiQNw80c
https://www.youtube.com/watch?v=Xx4Tpsk_fnM
https://www.youtube.com/watch?v=JAcwtV_bFp4
I would recommend this channels "AI" project demo on the PDP-11:
https://www.youtube.com/watch?v=OUE3FSIk46g
Also, a well known case of "AI" output infringement leading to legal peril:
https://www.youtube.com/watch?v=YhgYMH6n004
One may believe whatever they like, and have a glorious day. =3
Indeed.
Remember kids never get your legal advice from hn comments.
Don't become the cautionary tale kid, as crawlers like sriplaw.com will be DMCA striking your public repos eventually. =3
However, the gotcha here seems to be that the developer has to say that the code is compatible with the GPL, which seems an impossible ask, since the AI models have presumably been trained on all the code they can find on the internet regardless of licensing, and we know they are capable of "regenerating" (regurgitating) stuff they were trained on with high fidelity.
Is an AI reimplementation a "clean room" implementation? What if the AI only generates pseudocode and a human implements the final code based on that? Etc etc ad infinitum.
Lawyers will be having fun with this philosophical question for a good decade.
Certainly not if it had seen the code (incl. having been trained on it).
The idea of clean room (dating back to IBM PC BIOS clones) is that ideas can't be copyright, but the expression of an idea (code) can be, so you have one person (or AI) write a spec of the thing you want to copy (expression -> idea) and then have another (in the "clean room") who has never seen the original code, and only seen the spec/idea, re-implement it.
If the re-implementation was being done with AI, then for this to pass as "clean room" it would need to be proved that the AI had never seen the code, only the spec.
I get it that lifting a full-ass function as-is from a project is bad, but if you construct a function that does the same thing by aggregating bits from different projects - what then?
There HAS to be moral and legal issues there, but what and where? Stealing other people's code is bad, but we do also have to admit that the vast majority of code in the world isn't doing anything groundbreaking that deserves a copyright.
Or is it illegal to write a Hello World application after the first ever in that language was written and published, doesn't the copyright for that code exist on the first creator - and everyone else is in breach of their copyright or has to prove they had no prior knowledge of the code? (You can replace "hello world" with any trivial piece of code everyone writes a zillion times routinely).
This whole thing is so wishy-washy and vague it's giving me migraines. I don't WANT to break any laws, but holy crap it's not easy to figure out where the actual limits are.
LLMs are lossily-compressed models of code and other text (often mass-scraped despite explicit non-consent) which has licenses almost always requiring attribution and very often other conditions. Just a few weeks ago a SOTA model was shown to reproduce non-trivial amounts of licensed code[0].
The idea of intelligence being emergent from compression is nothing new[1]. The trick here is giving up on completeness and accuracy in favor of a more probabilistic output which
1) reproduces patterns and interpolates between patterns of training data while not always being verbatim copies
2) serves as a heuristic when searching the solution-space which is further guided by deterministic tools such as compilers, linters, etc. - the models themselves quite often generate complete nonsense, including making up non-existent syntax in well-known mainstream languages such as C#.
I strongly object to anthropomorphising text transformers (e.g. "Assisted-by"). It encourages magical thinking even among people who understand how the models operate, let alone the general public.
Just like stealing fractional amounts of money[3] should not be legal, violating the licenses of the training data by reusing fractional amounts from each should not be legal either.
[0]: https://news.ycombinator.com/item?id=47356000
[1]: http://prize.hutter1.net/
[2]: https://en.wikipedia.org/wiki/ELIZA_effect
[3]: https://skeptics.stackexchange.com/questions/14925/has-a-pro...
I don't think this is anthropomorphising, especially considering they also include non-LLM tools in that "Assisted-by" section.
We're well past the Turing test now, whether these things are actually sentient or not is of no pragmatic importance if we can't distinguish their output from a sentient creature, especially when it comes to programming.
It should be either something like "(partially/completely) generated by" or if you want to include deterministic tools, then "Tools-used:".
The Turing test is an interesting thought experiment but we've seen it's easy for LLMs to sound human-like or make authoritative and convincing statements despite being completely wrong or full of nonsense. The Turing test is not a measure of intelligence, at least not an artificial one. (Though I find it quite amusing to think that the point at which a person chooses to refer to LLMs as intelligence is somewhat indicative of his own intelligence level.)
> whether these things are actually sentient or not is of no pragmatic importance if we can't distinguish their output from a sentient creature, especially when it comes to programming
It absolutely makes a difference: you can't own a human but you can own an LLM (or a corporation which is IMO equally wrong as owning a human).
Humans have needs which must be continually satisfied to remain alive. Humans also have a moral value (a positive one - at least for most of us) which dictates that being rendered unable to remain alive is wrong.
Now, what happens if LLMs have the same legal standing as humans and are thus able to participate in the economy in the same manner?
I can't point out where I draw the line clearly but here's one different I notice:
A recommendation can be both a thing and an action. A piece of text is a recommendation and it does not matter how it was created.
Assistance implies some parity in capabilities and cooperative work. Also it can pretty much only be an action, you cannot say "here is some assistance" and point to a thing.
Nope, there is no “The” Turing Test. Go read his original paper before parroting pop sci nonsense.
The Turing test paper proposes an adversarial game to deduce if the interviewee is human. It’s extremely well thought out. Seriously, read it. Turing mentions that he’d wager something like 70% of unprepared humans wouldn’t be able to correctly discern in the near future. He never claims there to be a definitive test that establishes sentience.
Turing may have won that wager (impressive), but there are clear tells similar to the “how many the r’s are in strawberries?” that an informed interrogator could reliably exploit.
I think you'll find that this is not settled in the courts, depending on how the data was obtained. If the data was obtained legally, say a purchased book, courts have been finding that using it for training is fair use (Bartz v. Anthropic, Kadrey v. Meta).
Morally the case gets interesting.
Historically, there was no such thing as copyright. The English 1710 Statute of Anne establishing copyright as a public law was titled 'for the Encouragement of Learning' and the US Constitution said 'Congress may secure exclusive rights to promote the progress of science and useful arts'; so essentially public benefits driven by the grant of private benefits.
The Moral Bottomline: if you didn't have to eat, would you care about who copies your work as long as you get credited?
The more the people that copy your work with attribution, the more famous you'll be. Now that's the currency of the future*. [1]
You'll do it for the kudos. [2][3]
*Post-Scarcity Future.
[1] https://en.wikipedia.org/wiki/Post-scarcity
[2] https://en.wikipedia.org/wiki/The_Quiet_War, et. al.
[3] https://en.wikipedia.org/wiki/AccelerandoYes.
I have 2 issues with "post-scarcity":
- It often implicitly assumes humanity is one homogeneous group where this state applies to everyone. In reality, if post-scarcity is possible, some people will be lucky enough to have the means to live that lifestyle while others will still by dying of hunger, exposure and preventable diseases. All else being equal, I'd prefer being in the first group and my chance for that is being economically relevant.
- It often ignores that some people are OK with having enough while others have a need to have more than others, no matter how much they already have. The second group is the largest cause of exploitation and suffering in the world. And the second group will continue existing in a post-scarcity world and will work hard to make scarcity a real thing again.
---
Back to your question:
I made the mistake of publishing most of my public code under GPL or AGPL. I regret is because even though my work has brought many people some joy and a bit of my work was perhaps even useful, it has also been used by people who actively enjoy hurting others, who have caused measurable harm and who will continue causing harm as long as they're able to - in a small part enabled by my code.
Permissive licenses are socially agnostic - you can use the work and build on top of it no matter who you are and for what purpose.
A(GPL) is weakly pro-social - you can use the work no matter what but you can only build on top of it if you give back - this produces some small but non-zero social pressure (enforced by violence through governments) which benefits those who prefer cooperation instead of competition.
What I want is a strongly pro-social license - you can use or build on top of my work only if you fulfill criteria I specify such as being a net social good, not having committed any serious offenses, not taking actions to restrict other people's rights without a valid reason, etc.
There have been attempts in this direction[0] but not very successful.
In a world without LLMs, I'd be writing code using such a license but more clearly specified, even if I had to write my own. Yes, a layer would do a better job, that does not mean anything written by a non-lawyer is completely unenforceable.
With LLMs, I have stopped writing public code at all because the way I see it, it just makes people much richer than me even richer at a much faster rate than I can ever achieve myself. Ir just makes inequality worse. And with inequality, exploitation and oppression tends to soon follow.
By definition, that's not a post-scarcity world; and that's already today's world.
> It often ignores that some people are OK with having enough while others have a need to have more than others, no matter how much they already have.
Do you think that's genetic, or environmental? Either way, maybe it will have been trained out of the kids.
> it has also been used by people who actively enjoy hurting others, who have caused measurable harm
Taxes work the same way too. "The Good Place" explores these second-order and higher-order effects in a surprisingly nuanced fashion.
Control over the actions of others, you have not. Keep you from your work, let them not.
> What I want is a strongly pro-social license - you can use or build on top of my work only if you fulfill criteria I specify such as being a net social good
These are all things necessary in a society with scarcity. Will they be needed in a post-scarcity society that has presumably solved all disorder that has its roots in scarcity?
> With LLMs, I have stopped writing public code at all because the way I see it, it just makes people much richer than me even richer at a much faster rate than I can ever achieve myself.
Yes, the futility of our actions can be infuriating, disheartening, and debilitating. Comes to mind the story about the chap that was tossing washed-ashore starfish one by one. There were thousands. When asked why do this futile task - can't throw them all back- he answered as he threw the next ones: it matters to this one, it matters to this one, ...
Hopefully, your code helped someone. That's a good enough reason to do it.
I don't think you understand how children work.
You probably imagine some Brave New World kind of conditioning. Not to mention, those people will want their kids to have those traits.
> Hopefully, your code helped someone. That's a good enough reason to do it.
No. That's like saying that the V2 rocket program helped keep a bunch of people out of the gas chambers.
We should absolutely do our best to make sure our work does more good than harm, not just that it does some good.
EDIT: I am sad to see your other comment below flagged/dead. HN does not like the idea that a lowly open source contributor could take their phones and computers away from them for petty things like genocide, murder or rape...
Despite agentic tools being used by millions of developers now, I am not aware of a single real case where accidental reproduction of copyrightable code has been an issue.
Further, some model providers offer indemnity clauses.
It seems like a non-issue to me, practically.
That LLM response is describing a specific project with full attribution.
How does the chardet achieve this? Explain in detail, with shortened code excerpts from the library itself if helpful to the explanation.
The prompt is explicitly requesting the source!
Yes, this is sarcasm but that's how it should work. These models cannot be created without ingesting vast amounts of code created by human labor. The proponents of this kind of stealing argue that the models "generalize" and that somehow makes it right and legal. And here we have counterexample to their generalization argument.
Doesn't change the fact labor theft is still labor theft but it might make a difference to the letter of the law, hopefully.
I say hopefully because I believe all people who contribute to technical progress should be compensated according to their amount of work and skill level. But of course many "temporarily embarrassed trillionaires" disagree. I don't understand why but I am happy to know that if the tides turn they will be perfectly A-OK with me taking their work without credit or compensation.
Am I being too pedantic if I point out that it is quite possible for code to be compatible with GPL-2.0 and other licenses at the same time? Or is this a term that is well understood?
"GPL-2.0-only" "GPL-2.0 only"
https://spdx.org/licenses/GPL-2.0-only.html It's a specific GPL license (as opposed to GPL 2.0-later)
I don't get this part. Why is the reviewer signing off on it? AI code should be fully documented (probably more so than a human could) and require new tests. Code review gates should not change
Or you mean the velocity of commits will be so much that reviewers will start making more mistakes?
How long until people get exhausted with the new volume of code review and start "trusting" the LLMs more without sufficient review, I wonder?
I don't envy Linus in his position... hopefully this approach will work out well for the team.
Assisted-by: AGENT_NAME:MODEL_VERSION [TOOL1] [TOOL2]
At the same time, I feel bad for all the people that have to deal with low quality AI slop submissions, in any project out there.
The rules for projects that allow AI submissions might as well state: "You need to spend at least ~10 iterations of model X review agents and 10 USD of tokens on reviewing AI changes before they are allowed to be considered for inclusion."
(I realize that sounds insane, but in my experience iterated review even by the same Opus model can help catch bugs in the code, I feel like the next token prediction in of itself is quite error prone alone; in other words, even Opus "writes" code that it has bugs that its own review iterations catch)
So what's preventing lawyers/companies having a batch of people they use as scapegoats, should something go wrong?
The typical trailer for this is "AI-assistant:".
You don't get to bang on a screw and blame the hammer.
Are there other popular repos with effectively this policy stated as neatly that I’ve missed?
Side note, I'm not sure why I feel weird about having the string "Assisted-by: AGENT_NAME:MODEL_VERSION" [TOOL1] [TOOL2] in the kernel docs source :D. Mostly joking. But if the Linux kernel has it now, I guess it's the inflection point for...something.
Or, to put it another way, in the old days in order to be a 3k-LoC PR wielding psychopath intent on making your colleagues miserable with churny aggro diffs from hell you at least had to be good at coding.
Nowadays, you only need to do the psychopath art — Claude will happily fill in the PR for you.
Humans for humans!
Don't let skynet win!!!
pre "clanker-linux".
I am more intrigued by the inevitable Linux distro that will refuse any code that has AI contributions in it.
This format really took off in the Python community in the 2000's for documentation. The Linux kernel has used it for documentation as well for a while now.
We've been using Co-Developed-By: <email> for our AI annotations.