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GitHub Copi­lot inves­ti­ga­tion

githubcopilotinvestigation.com

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Re: GitHub Copi­lot inves­ti­ga­tion

#691

Earlier quoted context omitted.

I really appreciated the argument in the book "The New Breed," which is that we should adapt ideas around the governance of animals to governance of ML: You can train your dog to attack random passersby, but if you do, you're a monster and ultimately responsible for the dog's actions. Likewise, you can tell Copilot to crank out code specific algorithms written by specific people, but if you do so, you're still creati…

This just sounds like blaming the researchers to me. How would i ever know if my "boring code completion" was actually copyright infringement? Your argument just disallows discussing the problem while doing absolutely nothing about it. If you train your dog to NOT attack random passersby and it still does, that dog is euthanized no matter your intentions.

If you build a system that has a high likelihood of breaking the law in normal expected use, and then it's found to break the law, shouldn't we disincentivize that in some way? Is that just blaming the researchers/developers, or is that just making people respect the law?

I think the important thing to note in both dog attack scenarios presented is that the owner is responsible in both cases. Either they purposefully created an unsafe situation or they were negligent in protecting the public from their property. Whether the dog is euthanized is about preventing it from happening again. Preventing it from happening in the first place is done by making the owner liable to disincentivize it.

Re: GitHub Copi­lot inves­ti­ga­tion

#692
post #530

Earlier quoted context omitted.

I use Copilot all the time and I’ve never once used it to generate a whole prepackaged function that’s more than maybe three lines. So no, I don’t benefit from its reproducing other people’s code at all. Tell me you don’t use Copilot without telling me about it.

That isn't sufficient to get you off the hook. Copyright covers derivative work, not just code that's reproduced verbatim.

"Derivative work" is a very specific thing, and it's contrasted with "transformative work" in a way that matters a lot, and fair use intersects heavily with both.

Even when it comes to stuff that seems reaaaaally close to pure derivative: Googling "How long does it take to boil water?" => "If you're boiling water on the stovetop, in a standard sized saucepan, then it takes around 10 minutes for the correct temp of boiling water to be reached. In a kettle, the boiling point is reached in half this time."

That's a verbatim snippet pulled directly from https://unocasa.com/blogs/tips/how-long-to-boil-water, and yet Google exists and continues to do stuff like this under the fair use doctrine despite massive efforts to attack/monetize their service. [To be fair, Google does link results, which probably insulates them because it's less hurtful to the commercial interests of the source; that said, with open source there generally are no commercial interests to hurt (open source attribution will be a tough sell as an actual commercial interest), and that's specifically called out in the law as a factor]

Copilot is even less explicitly at risk IMO, in that it never even stores the text, nor can it reliably retrieve it. I have no idea what makes anyone think it should be more vulnerable than Google.

From the copyright.gov page on fair use (https://www.copyright.gov/fair-use/, worth reading in detail for anyone who cares about this stuff, also has links to a monumental number of cases with shockingly intelligible summaries): "Additionally, “transformative” uses are more likely to be considered fair. Transformative uses are those that add something new, with a further purpose or different character, and do not substitute for the original use of the work."

Copilot without any shadow of a doubt does add something new, with a further purpose, and does not substitute for the original use of any codebase on Github (it can't create any of the codebases in full, without manual guidance so extreme that you'd have to be using the actual original codebase as a reference, so it clearly cannot substitute for a single one of them, and that's what a lawyer will argue, likely successfully).

In the Google vs. Oracle case (see https://www.copyright.gov/fair-use/summaries/google-llc-orac...), a big piece of the fair use finding was that "its value in significant part derives from the value that those who do not hold copyrights, namely, computer programmers, invest of their own time and effort to learn." and "further[s] the development of computer programs”. It's hard to see where Copilot wouldn't fall into that category, as well, and that's precedent on (multiple) appeal.

By my reading this should be a slam-dunk fair use ruling, unless precedent gets really upended, and Butterick is wasting a ton of time and effort for absolutely zero potential gain other than some bragging rights, but to each his own...I guess we all have to grind our axes from time to time.

Re: GitHub Copi­lot inves­ti­ga­tion

#693
post #642

Earlier quoted context omitted.

> which is what copilot has been show to sometimes do In those cases it seems that humans are already copying code without also propagating licenses appropriately. LLMs are more likely to memorize things which occur a lot (and I'd bet rare things that are representative of some conceptual axis). The main examples presented so far, Davis and Carmack, have the property of having been copied a lot. The generative model…

That seems like a weak defense: "sure, we violated copyright but only because many other people do, too". Kinda the same problem as YouTube. Lots of people copy movies on the high seas, but if you are as big as yt you cannot easily get away with it.

No, this is not meant as a defense. My point is that it's an issue that is already rampant and what Copilot (or any model) does is make it more readily visible.

This is not like youtube because Github is already hosting those violations and people are already inappropriately copying or including such code. It matters not whether the local inclusion was fetched by copilot or a human fetched it using more manual steps through search.

Re: GitHub Copi­lot inves­ti­ga­tion

#694
To stay sane: for myself as a developer, I consider github copilot as a (much) faster google/code search work-flow. I can copy / or re-mix code I find in a google search, but it's my responsibility to figure out the copyright situation of that code.

Imagine if something like google didn't exist, and then it suddenly did. People would be saying: "This newfangled computer algorithm is giving everyone copies of my code with a misattributed licence, just by typing the function name and site:github.com !"

Re: GitHub Copi­lot inves­ti­ga­tion

#695
post #640

Earlier quoted context omitted.

I see this basic logic in almost AI ethics threads, and it starts with a big assumption: "humans learn from copyrighted source material without copyright violation". This then gets tenuously extended to "ai also learns, so it must not be in violation of copyright law". The first assumption is highly flawed though. Humans routinely do violate copyright law. Plagiarism is a huge problem in many sectors; un-cited direct…

+1. And let's not forget too that "AI", that is, ML models, are not "autonomous" in the way that humans are autonomous. Sure, we use the word "learn" to describe what they do, which is one word that we also use to describe what people do. But ML models are always wielded by people or corporations for particular purposes. If a corporation was to directly publish some copy that appears plagiarized, we'd call that plagi…

The main reason AI will be reproducing copyrighted works while the original license is not trivial to identify will be that in those instances, humans are already violating copyright at a high rate. It's just flown under the radar thus far as required machinery to so easily surface violations was not available.

Copilot is capable of going beyond retrieval and is competent at using variables, comments, types and local context to infer intention and generate appropriate code and even comment on it. Whenever copilot correctly predicts code of yours that's a novel combination of concepts, copilot has originated novel code.

For esoteric concepts, you usually already have to know how to prime it but Copilot is especially useful when it helps you bump into things you didn't know you didn't know (one way to increase the odds of this happening is to write out your thinking so far in markdown or comments. You'd be surprised how helpful and clever Copilot can be in some instances). My point here is Github isn't charging $10/month for run of the mill retrieval. My opinion is code-gen LLMs contribute value and more open versions are worth building.

Re: GitHub Copi­lot inves­ti­ga­tion

#696
post #634
post #535

Earlier quoted context omitted.

That's hardly a new thing! For instance, Google search makes billions of dollars by indexing content that other people make.

Google Search links to the original content. Copilot doesn't.

As I responded to someone else, this isn't always true. Google "when was George Washington born".

Re: GitHub Copi­lot inves­ti­ga­tion

#697
post #486

Here are a few thoughts I haven't formulated before: It seems clear enough to me that training AIs on copyrighted works is typically or commonly a fair use under existing law, because the AIs can and commonly do learn non-copyrightable elements and aspects of those works. It's very obvious from enormous numbers of examples that current AI systems are capable of learning much more abstract features of human culture (g…

I really appreciated the argument in the book "The New Breed," which is that we should adapt ideas around the governance of animals to governance of ML: You can train your dog to attack random passersby, but if you do, you're a monster and ultimately responsible for the dog's actions. Likewise, you can tell Copilot to crank out code specific algorithms written by specific people, but if you do so, you're still creati…

[deleted]

Re: GitHub Copi­lot inves­ti­ga­tion

#698
How can I, as the lead of a small team, make sure none of my code ends up on copilot (or any other submission of our IP to third parties)? We use Devops internally, and IDE decision is up to the developer.

Im unsure if vscode etc submit samples or just interact with GitHub.

Edit: and furthermore, make sure it doesn’t import code from third parties. I don’t want my code being infringed upon, but also don’t want to accidentally infringe on others’ work. Legal or not.

Re: GitHub Copi­lot inves­ti­ga­tion

#699
Oh god please no. GitHub Copilot is a wonderful technology. I am not taking anything away from you if Copilot suggests code that is similar or identical to your copyrighted code. You were not going to sell it to me anyway.

The following is supposed to be OK: somebody reads your GPLed code, learns abstract concepts from it, teaches it to me, I write code that uses the same algorithm. But it's not OK to abbreviate the process and reach the same result directly with Copilot. That is some Talmudic level reasoning. In a sane legal system, one would note that it is legal to do when jumping through pointless hoops, so it should be legal per se, and the system should be adjusted.

Copyright is increasingly at odds with technological development. Not just since AI applications, at least since Napster or since floppy disks. Of course Matthew Butterick as a lawer would disagree - "It is difficult to get a man to understand something, when his salary depends on his not understanding it."

Re: GitHub Copi­lot inves­ti­ga­tion

#700
One way to fix the problem would be to somehow feed Copilot a corpora of closed source code. This would either force Microsoft to add necessary copyright protections, or - which is imho more likely - would prove that those protections are already in place, but disabled for open source code.

A good start would be to take a leaked code of Windows, and then mechanically adjust all the names, constant values, and code formatting, and then publish it and observe.

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