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From TFA:

> When the Supreme Court declined to hear the Thaler appeal in March 2026, it did not endorse the lower court's reasoning or settle the question nationally. Cert denial means the Court chose not to hear the case, nothing more. What it does mean is that the DC Circuit's ruling stands, the Copyright Office's position is intact, and no court has yet gone the other way.

Your quoted text is no longer in TFA.

Lets hire humans as pAIrrots? They see it, they rearrange it, they rename variables and then they "authored" it. What a job- to start for as junior, but if you understand whats happening, you may augment the AIs code by giving "feedback" with enough time.

Also, I don't think there is any example testing the conclusion. There is no case to point at that any of the factors they listed are sufficient to convey authorship. Would love to be pointed to a case where rejecting decisions and redirecting to a different approach was deemed human authorship. What we do know is that you can disclaim the part of the code a human didn't author. In fact, the Copyright Office requires you disclose and disclaim. If anyone out there has more factual and citable sources please share.

> meaningful human authorship

How is this defined? Is my code review "meaningful" ? Are my amendments and edits to the generated code "human authorship" ?

But it means that the appellate decision will retain precedence, no? Wouldn’t losing precedence be the primary legal effect of overturning that decision? All case law that hasn’t touched the Supreme Court could theoretically be challenged, but most of it isn’t, and it’s considered the law until it isn’t anymore, right? How would this be any different?

Fair and correct. Cert denial means the Court declined to hear the case, not that it endorsed the lower court's reasoning or settled the question nationally. The DC Circuit ruling stands and the Copyright Office's position is consistent, but that is stable doctrine rather than Supreme Court-settled law. Updated the piece to reflect this distinction accurately.

It does settle the law in as far as maintaining the status quo.

The Supreme Court declining to take up an issue is taking a position.

Now different circuits can take a different view of the same issue. This is a common reason why the Supreme Court will grant cert: to resolve a circuit split. Appeals court judges know this and have at times (allegedly) intentnionally split to force an issue to the Supreme Court.

Even without settling the issue appeals courts will look at how other circuits have ruled and be guided by their reasoning, generally. The fact that the Supreme Court declined to grant cert actually carries weight.

The LLM is just a database. It's like saying 'I own the copyright to what comes out of an API because I crafted the query' or 'I own the copyright to the responses I get from the bots on the Starship Titanic because I crafted the message they respond to'.

Funny how the copyright industry was able to spin copyright infringment into the pejorative "stealing". If you still have the item, what was stolen?

Dowling v. United States, 473 U.S. 207 (1985): The Supreme Court ruled that the unauthorized sale of phonorecords of copyrighted musical compositions does not constitute "stolen, converted or taken by fraud" goods under the National Stolen Property Act

Copyright isn't some natural state of being though, it's something that's granted to people by the government to "promote the progress of science and useful arts". If copyright hinders things then I think it's reasonable that exceptions would be made.

Copyright laundering is an illusion.

If the LLM generates output that a court decides is sufficiently derivative, and especially (but not necessarily) if the LLM was trained on the source material being infringed, then whoever redistributes the derivative output is going to be liable for copyright infringement.

Creation of the LLM itself is transformative, but LLM output which infringes is not.

Do you think that human directing the agent owns copyright for any legal reason?

The case Community for Creative Non Violence Vs Reid (https://en.wikipedia.org/wiki/Community_for_Creative_Non-Vio...) solidifies a supreme court opinion that someone contracting a work and directing an author does not grant authorship to the commissioner of the work, it grants authorship to the person actually doing the work.

The author can grant authorship and copyright to the commissioner with a contract, but the monkey picture (and others) have solidified that only humans can be granted copyright. Since LLMs aren't human they can't hold copyright, and if the LLM doesn't have legal copyright then they don't have legal rights to assign copyright to you.

but the ability for the agent to build it in the first place is based off of stolen IP.

I honestly don't understand why the attitude that underlies this is so prevalent.

When I write code, what I write and how I write it is informed by having read countless source code files over my education and my career. Just as I ingest all that experience to fine-tune how my later code is written, so does the LLM from the code it's seen.

The immediate retort to that is that the LLM is looking at code that wasn't its to read. But I don't think that's a valid objection. Pretty much by definition, everything I've learned from has a copyright on it, and other than my own code on my own time, that copyright is owned by someone else. Much of the code that's built up my understanding has been protected by NDA, or even defense-department classifications: it wasn't mine in any way. But it still informs how I do all my future coding.

By analogy: I'm also an artist, especially since my retirement. My approach to photography was influenced by Ansel Adams, and countless other artists whose works I've seen displayed in museums, or in publications and online. My current approach to painting was inspired by Bob Ross and others, and the teachers who have helped me develop. I've taken pieces of what I've seen in all their work, and all of that comes out in my photos and paintings, to varying degrees.

I've taken ideas from others in code and in art, and produced something (hopefully!) different by combining those bits with my own perspective. I don't think anyone has a claim on my product because of this relationship.

Likewise, I know that many of my successors have learned from my code (heck, I led teams, wrote one book about software development!). And I hope that someday my artwork has developed to the point where there's something in it that's worth someone else's attention to assimilate. I've never for a minute - even decades before the advent of LLMs - hoped or even imagined that my work would remain locked up with me, and that the ideas would follow me to the grave.

As they say, we are all standing on the shoulders of giants. None of us would be able to achieve the tiniest fraction of what we have, without assimilating what has come before us. Through many layers of inheritance it's constantly being incorporated in subsequent works.

In a few decades at best, I'll be dead. It probably won't be very long after that when people even forget my name. But the idea that something I've done - my work in developing software systems, or in my photography and painting - will continue to have ripples through time, inspires me and gives me hope that I'll have some tiny shred of immortality beyond my personal demise.

I wonder what OSS licenses would have looked like if we saw all of this coming.

I've created my own DSL, and instruct Claude Code how to generate code for this DSL using skills.

Since this is a new language, and not documented on the web nor on Github, Claude's ability is not based off of stolen IP. At best it's trained on other language concepts, just like we can train ourselves on code on GitHub.

Maybe a good reason to create a new programming language?

I could possibly see an argument for the owner being whoever paid for the tokens used, but honestly I think the argument for that is weaker than what you're suggesting; I'm merely playing devil's advocate here.

I don't think there's even a valid argument for any other ownership model, or at least none that I can think of.

No, that human owns the copyright on the prompt, not on the work product.

I agree with this sentiment, because the person directing the agent can still direct it in a way where it'll produce a better or worse output than another person directing it.

This interpretation makes sense. I think even the 'fair use' clause in the US doesn't protect LLMs. One argument I've heard often is that LLMs synthesize their training set to produce novel output in the same way as a human would... That may be the case, but legally an LLM isn't a human. You can't look at the output of an LLM and say that it's 'fair use' with respect to its training set; it hasn't been established that AI has the same 'fair use' right as a human does; it's already pushing it that companies have this right (let alone an AI agent); anyway, that's just one problem... Also, this is ignoring the fact that the researchers who compiled the training set COPIED the original copyrighted data in order to produce that training set. They either copied the entire work into the training set or they fed the entire work directly into the LLM; in either case; at some point, the entire work was copied verbatim into the LLM's input layer before it was ingested by the AI. The researchers copied the copyrighted content without permission.

Also, when it comes to code, the case is even more damning because the vast majority of the code which LLMs are trained on was not only copyright but subject to an MIT license (at best) and even the MIT license, which is the most permissive license in existence, still says clearly:

"Permission is hereby granted, free of charge, to any person obtaining a copy of this software"

The word 'person' is used very intentionally here.

I think there should be several kinds of AI taxes which should be distributed to all copyright holders. There should be a tax to go to writers (and book authors), a tax to go to open source developers and a tax for the general population to distribute as UBI to account for small-form content like comments and photography...

People invested a lot of time building their entire careers around the assumption of copyright protection; so for it to be violated on such a scale would be a massive betrayal.

I find idea that the code could be copyrightable as weak. There are only so many ways to write a for loop. Similarly you can't copyright schematics (apart from exact visual representation as form of art). Code is just a schematic.

You can think that's how it should be. But that's not necessarily how it is. I'm reminded of the famous monkey selfie copyright dispute [1]. A photographer set up a camera and gave it to a monkey but after a legal dispute, courts decided nobody owned the copyright.

I can totally see this applying here as well.

Now this doesn't resolve the issue of AIs being trained on copyrighted works it had no rights to. The counterargument is that this is a derivative or transformative work but I don't believe that's settled law at all.

[1]: https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput...

Depends on the scale of LLM involvement, the copyright office left a pretty big carve out for things that are human sourced and then modified by LLM, or the reverse, LLM output thats modified by human intention. (They had to do this because there are already pseudo random elements to digital artwork, like say, render clouds and render noise, that might otherwise poison an artwork). In fact I dont think this has been tested with Highlight area > Prompt a change to this area of the image workflows.

They also mention in the same document that were LLMs to more closely approximate deterministic tools, they would be open to reevaluating. That is Requesting X gets X without substantial wiggle room.

I dont think that last part has been tested with an extremely large set of prompts and human generated input to create a more deterministic output. Even outside of code, where you see large prompts, creative writing LLM tools, NovelAI or Sudowrite for instance can have pages and pages of spec for the LLM, sometimes close to 50% of the size of the final output.

Then there's testing, review etc, human processes confirming that the output meets spec, updating it where needed intelligently.

There are also foreign courts, with similar rules about human intention, that have found in favor of prompts only, where it could be demonstrated that multiple rounds of prompts were used to refine the image.

I wouldnt call this settled at all tbh. And to be honest, a lot of this doesnt require exposure. you dont need to own up to LLM use in a lot of settings, proving LLM use is so difficult its easy to jump up the ladder from LLM (100%) to LLM (50%) and ultimately claim ownership.

The people who will get busted for this are basically just super lazy leaving ChatGPT responses in, failing to pay an editor, failing to modify images for anything more than layouts.

> But a compiler is deterministic — same input, same output. An LLM isn't.

Temperature 0 determinism is subject to active research. NVIDIA tried but failed so far, DeepSeek V4 seems to have done it. I hope judges won't be swayed by this an AI generated code will classified as uncopyrightable, just like Images are.

But is there anything stopping a human from applying for copyright in their own name? Does the fact that somebody can recreate the prompt invalidate their claim?

Best part is, it's likely to have a different answer in every country, who knows what'll happen, not every country implicitly sides with the ones with the most money.

I love that genAI art will not be copyrightable and genAI code will be. The power of the Almighty Dollar at work.

The work-for-hire doctrine actually supports your intuition more than the AI authorship question does. The reason Anthropic likely owns Claude Code has little to do with whether Claude wrote it and everything to do with the employment contracts of the engineers who directed it. The DMCA takedown question is genuinely interesting though because DMCA requires the claimant to assert copyright ownership in good faith. If a court later found the codebase was predominantly AI-authored and therefore not copyrightable, the 8,000 takedowns could be challenged as bad faith DMCA claims. That is a different and more tractable legal question than the ownership one.

It's not wishful thinking, and ownership isn't a foregone conclusion.

Sure the courts could mint a communist society with a few weird decisions about property rights, but this being the US do you really suppose that's likely?

There's really no legal question of any kind that models aren't people and therefore cannot own property (and also cannot enter into legal contract as would be required to reassign the intellectual property they don't and can't own)

They won't want to own code that is malicious\illegal\used in crime, although it's really weird to me that no one (in LEO) seems to care that, for example, grok generates CSAM, revenge porn, probably other illegal things, so they'll probably get to have their cake and eat it too.

I'm not sure Anthropic would appreciate the liability that ownership would imply.

> Third - we just take a big smelly dump on the teamwork - it's easier and cheaper to let one developer drive the whole change from backend to frontend, despite there are (or were) two different teams - one for FE, one for BE.

Agree with your other points, but IMO this one has always been better. You often need to design the backend and frontend to work with each other, and that requires a lot more coordination when it's separate teams.

people quickly have forgotten: when copilot was announced, there were warnings not to use it for company code because of the license attribution problem. so what's changed? that anthropic is willing to defend and indemnify?

Also, it's supremely easy do the wrong abstractions long term and compromise premature internal designs that will start to starve of human mental modeling, hence explaining with accountability how things work and what the plans are when an incident happens. Also, if the wrong generalizations are introduced, coded correctly and reviewed and approved by AIs, then who's even driving really?

I rarely see #3 yield better solutions, it's usually better to collaborate as a team on requirements and gotchas, but let one person own implementation.

I opened my popcorn for the unholy trinity of HN x law x AI, your comment was one of my faves, love the purple prose. :)

The fourth point about code commenting is the one that connects directly to the ownership question. When developers write comments to explain intent, those comments are evidence of human creative direction. When Claude writes the code and the comments, and the developer merges without adding their own explanation of the architectural decisions, the record of human authorship disappears along with the institutional knowledge. The documentation problem and the copyright problem are the same problem.

> But recipes still are protected intellectual property by trade secret law if they are treated as a secret by the holder of the recipe.

Trade secrets aren't very well protected, though.

You can sue the person who leaked/stole your secret, but if others keep sharing it once it is leaked you can do nothing to them.

> Software written by AIs are also not expressions of human creativity

I mean I'm not the biggest fan of AI on the planet by any means (which I think my post history would prove, lol), but isn't prompt design and steering the AI "human creativity"? In one of my AI-assisted projects I spent like a week in unending threads of posts trying to make the AI do stuff the way I wanted, testing the output, finding a bazillion of bugs and "basic bitch" solutions, asking for more robust this and edge case that. It felt like I wrote a novel. How is that not creativity (Crayon-eater or Picasso, creativity is creativity)?

> Almost no one thinks their code is copyrightable or seriously thinks their code is a moat.

You'd be surprised! Among non-software management types, they often think of the code as extremely valuable IP and a trade secret. I'm a CTO and I've made comments before to non/less technical peers about how the code (generally speaking) isn't that big of a secret, and I routinely get shocked expressions. In one case the company almost passed on a big contract because it required disclosure of the source code (with an NDA). When I told them that was a silly reason and explained why, they got it, but the old way of thinking still permeates and is a hard habit to break.

Edit: Fixed errant copy pasta error. Glad that wasn't a password :-)

> Almost no one thinks their code is copyrightable

Every open source license is built on the premise that code is copyrightable.

Nobody ever talks about convergence.

You, right now, are taking about convergence.

If there is no artwork, there can be no copyright. If every character of the code to write is basically predetermined by the APIs you need to call, there is no artwork and no copyright.

Build a novel new API, and you'll be protected though.

> Almost no one thinks their code is copyrightable

Then why does reverse engineered code need to be a clean room implementation?

Ask any emulator developer or the developers of ReactOS

https://reactos.org/forum/viewtopic.php?t=21740

> Almost no one thinks their code is copyrightable

I think this is an unusual opinion.

Code may not be copyrightable in as small chunks as you put there, but in terms of larger pieces I think companies and individuals very often labour under the belief that code is intellectual property under copyright law.

If code isn't copyrightable, from where comes the GPL?

And why does anyone care if (for instance) some Microsoft code might have accidentally ended up in ReactOS, causing that project to need to go into a locked-down review mode for months or years? For that matter why do employers assert that they own the copyright in contracts?

I think it's the opposite - almost everyone thinks their code is copyrightable, outside of APIs and interop stuff, or things so simple as to be trivial.

Why were the HFT firms suing employees?

>it should be pretty clear that if you provided the tool the specification for the code you want, you have already provided creative input.

If you provided a human contractor with the specifications for the code you want, the courts have repeatedly made clear you have not provided the creative input from a copyright perspective, and the contractor needs to explicitly assign those rights to you if want to own the copyright on the code.

Specifications are not necessarily creative input. Eg if I write a prompt that just says “write a rate limiter in Python”, there’s really no creative input. I didn’t decide on the API, or the algorithm to bucket requests, or where to store counters, or etc. I just gave it statements of fact, which are inherently not creative.

Compilers are different in that the resulting binaries are not separately copyrighted. They are the same object to the Copyright Office because one produces the other, in the same way that converting an image to a PDF is still the same copyright.

LLMs don’t do that. The stuff coming in may not be copyrighted, and may not be copyrightable. The stuff that comes out is not a rote series of transformations, there are decisions being made. In common use, running a prompt 10 times might yield 10 meaningfully different results.

I’m dubious the outcome will be “any level of prompting is enough creativity”.

The compiler analogy is the right one to reach for and the Copyright Office addressed it directly: the question is not whether you provided input, it is whether the creative expression in the output reflects human authorship. With a traditional compiler, the programmer authors every expression in the source. With an LLM, the programmer authors the intent and the model makes the expressive decisions about structure, naming, pattern, and implementation. Whether that distinction matters legally is what Allen v. Perlmutter is working through right now. The summary judgment briefing completed in early 2026 and it may be the next landmark ruling on exactly this question.

To me this is like asking who owns the binary files a compiler generates.

Probably, yes, but the burden of proof is with us not them.

I'm already glad some companies have the guts to open their models because proving it for open models is probably a lot easier than for a model behind a service.

What's an example of data that might have been stolen?

The media industry loves to quote ridiculous numbers on lost revenue due to piracy etc. May be a rough ballpark numbers will get them to do something about this theft.

Can someone put a rough estimate on potential revenue loss (direct and incidental) from training AI with industry wise breakup.

The article addresses this explicitly:

> Works predominantly generated by AI without meaningful human authorship are not eligible for copyright protection

Note the word "predominantly", and the discussion that follows in the article about what the courts and the copyright office said.

No such assumption is made in the article.

Nor does it give a single answer.

Mere prompting is still not enough for copyright, and the problem is unsolved on how much contribution a human needs to make to the generated code.

In the case for generated images copyright has been assigned only to the human-modified parts.

Even worse, it will be slightly different in other nations.

The only one that accepts copyright for the unchanged output of a prompt is China.

I'm sure it's not quite that simple. Only parts the parts of those knock-off works that aren't public domain could be copyrightable. If you only own the copyright to ten lines in a 10k line codebase, then it's probably fair use for someone else to just to take the whole thing.

Plus what if Anna Karenina was GPL?

You use humans to edit AI code? When you level up you are just using AI to write, AI to review, AI to edit, AI to test. Not a lot of steps left for meat bags.

Ok what about all the Anthropic’s engineers who say they don’t write code at all and it’s 100% AI-generated?

> This is of course assuming you take AI-generated code unchanged.

How much code do you need to change in order for it to be original? One line? 10%? More than 50%?

That's arbitrary and quite unproductive convo to be honest.

If you modify the work, that creates a derived work from whatever copyright the original works has, not a new work that is fully copyrightable.

As the article says in the Tl;DR at the top the code may be contaminated by open source licenses

> Agentic coding tools like Claude Code, Cursor, and Codex generate code that may be uncopyrightable, owned by your employer, or contaminated by open source licenses you cannot see

> This is of course assuming you take AI-generated code unchanged. But you don't, in my experience. And that generates a new work fully copyrightable even if the original wasn't.

That's not how copyright works. The modified version is derivative. You can't just take the Linux kernel, make some changes, and slap a new license on it.

Wrong. This territory was heavily covered in music before this code concept - it has to be “transformative” in the eyes of the law. Even going in and cleaning up code or adding 10-25% new code won’t pass this threshold. Don't bother arguing with me on this, just accept reality and deal with it.

What is being licensed by the End User License Agreement (EULA) is the copyright on the code and its artefacts (executable bytes, etc.) - you can't have an EULA without having the copyright to license.

Plus companies just violate GPL everywhere billions of times with impunity (see: every phone ever) and nothing happens to them.

A recipe isn't copyrightable but is still protected under trade secret law. I imagine that the same would apply. I think the major difference with software copyright is that I can just decompile your binary or copy a binary and give it to other people. For SAAS companies that don't distribute binaries, I imagine they basically have the same protections against rogue employees.

To look at it another way, just because some code I work on at my job is derived from open source MIT-licensed code doesn't mean I personally have the right to distribute it if my company doesn't want me to. I'd guess this comes under some generic "confidential information" clause in the employment contract.

That is exactly the right question and the answer is genuinely strange. Uncopyrightable work falls into the public domain, which means anyone can use it, copy it, or build on it freely. The employer can still call it a trade secret and protect it through confidentiality obligations in employment contracts, but that protection is contractual rather than property-based. A trade secret loses protection the moment it is disclosed. So the employer's claim over purely AI-generated code is essentially: "you cannot share this" rather than "we own this." Those are meaningfully different legal positions, and most companies have not thought through which one they actually have.

Presumably company policy would be implicated here, not copyright law. Whether or not it's copyrightable, what you create using AI is work product.

Depending on the scale. If you ask Clause to one-shot an app from a nebulous description, you get a prototype which you would understandably loathe to own the code of. If you plan carefully and limit the scope, you get code that you understand, can approve of, and are okay owning further down the line.

At what point is liability the only "job" left for humans?

Presumably, every company that has non-LGPL CC code in production wants to own it...

There’s so much FOMO right now around AI that no one is thinking clearly. I wouldn’t be so confident in your company.

Meta's confidence almost certainly rests on the employment contracts and IP assignment clauses, not on a legal theory that AI output is inherently copyrightable. The enterprise agreement with Anthropic assigns outputs to the licensee. The employment contract assigns work product to Meta. Those two documents together give Meta a defensible ownership position regardless of the authorship question. The interesting gap is for developers using personal accounts or consumer plans on side projects, where neither of those documents exists.

> Code from pirated text books

Anthropic "solved" this by intermingling the texts extracted from pirated books (illegal) with texts extracted from the physical books they bought and destroyed (legal), so no one can clearly say if the copyrighted material it spits out came from a legal source or not. Everyone rejoiced.

The sound recording analogy breaks down at the point where the recorder makes no creative decisions. Pressing record captures what is already there. Prompting Claude generates something that did not exist, through decisions the model makes about structure, naming, pattern, and implementation. The closer analogy is hiring a session musician and telling them the key and tempo. You own the recording under work-for-hire if they signed the right contract, but the creative expression in the performance is theirs unless explicitly assigned. The button you push to start the model is not the same button as the one on the recorder.

Why should it be any different than it ever was? If a release manager checked it but didn’t catch the vulnerability, they have some culpability. If the developer shipped the code without checking it, they have some culpability too. Ultimately, if they both work under an organization that they report to, they’re responsible to that organization, which is, in turn, accountable to its customers (and investors perhaps.)

LLMs really change nothing about this.

No one. The usual.

This sounds like a problem that's pretty easy to get around.

CC does not need LGPL code. There's more than enough BSD and Apache code to go around.

And they can generate synthetic data that is better than LGPL for their training.

It's also a problem that does not seem feasible to meaningfully enforce.

It's easy to generate CC code and lie and say you didn't. It would be hard to prove that you did, especially if you took any precautions to make it even slightly difficult that you did.

With sufficient obfuscation (which models seem to provide intrinsically), how would anyone know to sue? On top of that, only the most major sorts of litigation have the legal force to pierce even the flimsiest of obfuscation... this is likely all moot.

If some GPL-licensed group were to sue some commercial software project that they do not have the source code for, what would even give it away? But they throw $1 million at a lawyer who can at least get it to the discovery phase somehow, and the source code is provided. It looks to be shit, but maybe an expert witness would come along and say "that looks inspired by the open source project". Where does it go from there? The model is a black box, but maybe you've got a superhero lawyer who manages to rope in Anthropic or OpenAI, and you can see how it produced the code given those prompts. What now? Are there any expert witnesses who both could say and would say that it was "bulk copying-pasting code". And if it were, what jury is going to go for that theory of the crime? Copying-and-pasting, but the code doesn't match, except in short little strings that any code might match. This isn't a slamdunk, and it's not going to proceed very far unless it's another Google-vs-Oracle shitfest.

The chardet dispute is the closest thing to an active test case on this specific question, and you are right that it has not resolved into settled law. "Emerging legal consensus" was imprecise. The more accurate framing is: the legal community's working assumption, based on how copyright doctrine treats derivative works, is that training-data provenance travels with the output. That assumption has not been tested definitively in court yet.

thanks for this; it's definitely a fair point. I updated the piece to reflect this

The meaningful human authorship question is the elephant, agreed, and the regulators have deliberately refused to quantify it for exactly the reason you describe any bright line number becomes a target to game rather than a standard to meet.

The logging point is sharper than it might appear. In a copyright dispute over AI-assisted code, interaction logs could cut both ways. A plaintiff trying to establish human authorship would want the logs to show substantial architectural redirection, multiple rejections of Claude output, and documented reasoning for structural decisions. A defendant challenging that authorship claim would subpoena the same logs to show verbatim acceptance of output without modification.

The practical implication i guess here,that the developers who want to preserve a copyright claim over AI-assisted code should treat their prompt history as a legal document from the start. It seems all over the world the logs are the evidence. Whether they help or hurt depends entirely on what they show.

Not if claude does the writing. MS doesn't write things for you, and if it did, you would not be entitled to a copyright in whatever it wrote for you.

This is actually closer to how the Copyright Office thinks about it than the article makes clear. The registration guidance that emerged from the Thaler proceedings specifically asks applicants to describe the human creative contributions and how the AI was used. A documented workflow showing requirement, architectural decision, rejection of AI output, human restructuring, and review creates a paper trail that maps directly onto what the Office looks for. The can you show how it got here test you are describing is the practical version of the legal standard.

Copyright law kind of transcends national borders by certain international treaties like the Berne Convention. Which is why the US copyright holders could enforce their "woulnd't steal a car" threats in Europe.

Most of this is based on Copyright legal framework, which is surprisingly homogeneous around the world. The discussions about ownership of AI-generated material are exactly the same in EU.

It is copyrightable. A *human* can copyright code they wrote.

How is it for human developers now if the company tool is a cloud tool and not running on company servers?

The model ownership question and the output ownership question run on separate legal tracks and the piece focuses on the second deliberately. On the first: the model weights are owned by Anthropic under work-for-hire from their engineers regardless of what the training data contained. Training data copyright infringement is a separate tort claim against Anthropic, not a basis for anyone else to claim ownership of the model. The Bartz settlement resolved the pirated books claim without disturbing Anthropic's ownership of the weights. Owning the training data does not give you ownership of the model trained on it, any more than owning the paint gives you ownership of the painting.

The original bargain you describe, limited term in exchange for public disclosure, is exactly what makes the current situation strange. If AI-generated output falls into the public domain immediately, that is actually closer to the original intent of copyright than 95-year terms. The legal question is whether that outcome happens by design or by accident, and what it means for the people building products on top of AI-generated codebases right now.

AI is a monster to our current copyright system - monster in the philosophical sense, that is, an example that destroys the concept.

First, its creation is (claimed to be) extremely useful for society, but in order to be created it requires ignoring copyright for pretty much everything ever written. Something we kinda shrugged under the table.

Then, it introduces an extreme jump down in creation effort - so if the focus is protection of effortful creation, nothing with AI use qualifies. But of course, you'd want society to benefit from effortlessness in general, spending more effort than needed in a task is the opposite of efficiency.

Sadly, IP "ownership" and copyright law are vastly more complex than ownership of physical stuff.

Or were you planning to reproduce the (say) Ford Motor Company's trademarked symbol in wood? If so, you're right back in the stinkin' swamp.

What is the wood in your example?

This is like a machine you ask for timber and you get timber but you didn’t need to provide any wood

On that matter, wouldn't an AI flag for submissions help hn? I wouldn't flag a submission for LLM style as it is too harsh, but I don't want to read them -- if only because I don't like LLM prose.

There are so many submissions where most of the discussion is about whether the content has any human effort behind, or the LLM was just a purely assistive role like translating. It's really devaluing hn, IMO. Not sure how much an AI flag would help, or introduce new issues, given how difficult the problem is, though.

Curious: how do you exactly detect an AI-generated comment?

You are definitely right to flag it, apologize for that. I used an AI assistant for the replies, and I will make sure not to use one going forward.