Comment by nl | Hacker News Reader

Comment by nl | Hacker News Reader

The original reporting has more details: https://www.developer-tech.com/news/judge-dismisses-majority...

In particular this:

An amended version of the complaint had taken issue with GitHub’s duplication detection filter, which allows users to “detect and suppress” Copilot suggestions matching public code on GitHub.

The developers argued that turning off this filter would “receive identical code” and cited a study showing how AI models can “memorise” and reproduce parts of their training data, potentially including copyrighted code.

However, Judge Tigar found these arguments unconvincing. He determined that the code allegedly copied by GitHub was not sufficiently similar to the developers’ original work. The judge also noted that the cited study itself mentions that GitHub Copilot “rarely emits memorised code in benign situations.”

I think this is the key point: reproduction is the issue, not training. And as noted in the study[1] reproduction doesn't usually happen unless you go to extra lengths to make it.

[1] Not sure but maybe https://dl.acm.org/doi/abs/10.1145/3597503.3639133? Can anyone find the filing?

> reproduction doesn't usually happen unless you go to extra lengths to make it.

And who is to say that people who want to copy your code without adhering to your license terms or pay won't go to extra lengths? or am I missing something here?

At that point, they might as well copy your original code without going through an LLM to do it

Well then you end up with a work that a judge will allow to proceed to trial.

Only expressive software is protected by copyright and sometimes that interpretation should be handled by a jury.

It’s trained on publicly available code, so what would be the point of that? If you’re looking to specifically infringe the copyright of code available on the open web, using an LLM code completion engine is just about the most roundabout and unreliable way to achieve that.

Isn't this all about turning community developed GPL licensed code into your own (LLM regurgitatetd) code that you can than make proprietary, saving a lot of money and not giving back anything to the original community?

That's not generally how the legal system works. If you've disabled the duplication filter, and then generated substantial amounts of duplicated GPL code and then violated the GPL license, a judge is not going to say "Well, fair enough, you used the loophole of copying code through an LLM, after all." They're going to treat it as a willful copyright violation, the same as if you'd just copied and pasted it.

And again, I have to ask: why? Why would you think that putting tons of time and effort into tricking the model into repeating memorized code is going to be a better investment than just using it normally to implement the functionality you want?

It is but "AI" is considered such an "important" technology at the moment that no judge is going to want to be the one that "destroys innovation" by enforcing copyright law. If the perception of the technology changes in the political world in an unfavorable manner, these cases would go the other way or (if there's precedent) they'll pass laws overturning the precedents.

Wouldn’t the person themselves be in violation at that point and the owner of the code could go after them? (I know this wouldn’t be super practical but it seems to match what would have without an LLM in between).

Possibly. But how would they know unless they searched all the LLM's sources for any snippets it suggested?

This is the primary impediment to my large org at $work using llm-based coding tools: potential accidentally duplicated source code and the legal implications (including the risk of a viral copyleft license easter egg).

> And who is to say that people who want to copy your code without adhering to your license terms or pay won't go to extra lengths? or am I missing something here?

It seems like they could just download your code from Github and violate your license like that so.. unclear why they'd bother doing it via copilot.

Copilot cooyright-washes the license. So even we'll behaved devs could unknowingly copy code without complying with the license.

Although legally there may be a problem, in practice this seems to be a bit of a "so what?" scenario. Our hypothetical dev is using a tool that writes a function. It writes the function. The dev was going to get a function that did what he wanted one way or another so it isn't clear that it makes much difference if the function happens to be a clone of a copyrighted function.

If it were my GPLed code being copied, it doesn't seem to make any difference whether I press copyright claims or not. It won't help me compete against this dev's company. They'd use Copilot to rewrite the code differently. The speed of improvement in code-writing tools doesn't give me much hope that my code is uniquely clever.

It's unclear to me that that is the case. If I prompt an image generation model specifically to generate an unlicensed picture of Batman, I do not suspect that a judge is going to be sympathetic to the argument that the t-shirt I was selling was made by DALL-E so I should be free of any copyright infringement claims against me.

Why would specifically prompting the LLM to generate similarly copyrighted code be any different? That's what's being discussed here - that people will "go the extra lengths" to intentionally copy your code.

The "It wasn't me, it was the tool, even though I directed the tool quite specifically to do the thing that happened" is not a new defense in the legal systems of the world. We are already generally are able to deal with these without significant issue.

It's very unusual this happens for non-boilerplate code unless you deliberately disable the duplicate the duplicate filter.

> reproduction doesn't usually happen unless you go to extra lengths to make it.

Because then you can blame it on Copilot instead of outright stealing

This is legal for a person to do, right? Why should it not be legal for an LLM to do?

AFAIK but IANAL, I can go look at a solution in a GPLed library and then code that solution in my proprietary code base. As in, "oh, I see, the used a hash map for that and a list of this, and locked at this point. I'll code up something similar". As along as you don't "copy the code" you're fine.

Am I wrong?

Is it just a matter of scale? (hey there LLM, re-write all of OpenOffice into ClosedOffice).

> This is legal for a person to do, right? Why should it not be legal for an LLM to do?

Because humans are human. We are rewarded extra super duper rights that inanimate things, such as a computer program, are not rewarded.

I think we should therefore work to demonstrate this is not the case, which is very hard to do. No idea why we would work under the absolutely insane, never-before-seen assumption that computer programs deserve human rights. I don't know where this line of reasoning started, or why, but at it's core it's so unbelievably preposterous (and against the very wellbeing of mankind).

"Can anyone find the filing?"

https://arxiv.org/pdf/2202.07646

Personally, I would not rely on blogs like "developer-tech.com" for unbiased information about "AI" litigation.

I would read the order and draw own conclusions.^1 (Note the plaintiffs are attempting to file an interloctory appeal re: the dimissal of the DMCA claims.)

1 https://ia904708.us.archive.org/6/items/gov.uscourts.cand.40...

No doubt I am in the minority but I am more interested in the contract claims, which have survived dismissal, than in the DMCA ones. If plaintiffs can stop the "training" of "AI" through contract, then in theory DMCA violations can be avoided.^2

2 For example, license terms which specifically prohibit using the licensed source code to train language models.

Is there a "fair use" defense to contract liability.^3

3 https://cdn.ca9.uscourts.gov/datastore/opinions/2006/05/16/0...

> Is there a "fair use" defense to contract liability.

NAL, but in common law jurisdictions and maybe others there can be various implicit terms to any contract, like fair dealing.

Also if you can literally claim fair use, unless you signed a contract waiving that right (if that's even possible), it doesn't matter.

Heck, most software licensing in the USA is purporting to grant you rights that you already have from the Copyright Act. That's right, in US law you own the authorized copy you receive. The license claiming that you don't is questionable at best. To be fair the courts somehow have managed to become divided on this, but the plain language of the law itself is crystal clear, explicitly granting the right to make additional copies as necessary for execution.

Also that hardly matters when the fake license can still be "enforced" via lawfare. Most everyone is going to choose to pay up rather than fight a protracted legal battle against Microsoft.

https://www.courtlistener.com/opinion/506070/acorn-structure...

https://www.courtlistener.com/opinion/604886/national-car-re...

IANAL but I think for the specific dismissed claims in this specific case, reproduction is the issue, and it doesn't indicate anything about training.

I think it would be extremely hard to make claims against GitHub for training AI with code on GitHub, assuming GH has the typical "right to use data to improve service" clause that usually shows up on free-service EULAs.

> I think this is the key point: reproduction is the issue, not training. And as noted in the study[1] reproduction doesn't usually happen unless you go to extra lengths to make it.

But Microsoft is selling a service capable of such reproduction. They're selling access to an archive containing copyrighted code.

To me it's the equivalent of selling someone a DVD set of pirated movies. The DVD set doesn't "reproduce" the copyrighted material unless you "prompt" it to (by looking through the set to find the movie, and then putting it in your DVD player), but it was already there to begin with.

Strongly disagree with your analogy here. Lots of services are capable of doing things that are against the law but in general it's the actual breaking of the law that is prosecuted.

The closest thing to what you are suggesting is the Napster ruling, where a critical part was that the whole service was only about copyright infringement. In the Github case most people are using it to write original code which is not a copyright violation so there is substantial non-infringing use.

But what I think doesn't matter. The judge disagreed with that interpretation too.

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