This tool remains the equivalent of money laundering for violation of Open Source licenses (or software licenses in general).
If the model was trained entirely using code that Microsoft has copyright over (for example: the MS Windows codebase, the MS Office codebase, etc.) then they could offer legal assurances that they have usage rights to the generated code as derivative works.
Without such assurances, how do you know that the generated code is not subject to copyright and what license the generated code is under?
Are you comfortable risking your company's IP by unknowingly using AGPLv3-licensed code [1] that Copilot "generated" in your company's products?
[1] https://en.wikipedia.org/wiki/GNU_Affero_General_Public_Lice...
Are you sure that Disney and Games Workshop will not mind if make your own Mickey Mouse / Warhammer 40K cross-over movie for profit? (I would watch it!)
AI can help generate it, so it must be okay.
So do you believe in legal protections for trademarked and copyrighted works or not?
If an AI assistant generates content that includes copyrighted or trademarked elements is the content "too useful to be crippled by restrictive laws" or "protected by laws which will still be strong" ?
With everything from scihub getting blocked and people getting subscription fatigue, it is an excellent time for the restrictive laws to be replaced.
No argument there; that'd be a huge victory.
But until that happens, tools for "smart completions" need to provide appropriate licensing and attribution metadata.
This would not risk your company's IP.
"The GNU Affero General Public License is a modified version of the ordinary GNU GPL version 3. It has one added requirement: if you run a modified program on a server and let other users communicate with it there, your server must also allow them to download the source code corresponding to the modified version running there."
So your company is okay providing all their source code to users?
I know that some companies do this, but most do not.
Nothing is forcing them to do that. If they are infringing they simply need to delete the infringing code and rewrite it by hand.
If you use AGPLv3-licensed code in your codebase, you are agreeing to the terms of the license.
Practically all corporate legal teams for companies that creates software will strictly prohibit the use of AGPLv3-licensed software, if not all GPL-based licenses.
So you either agree to the license terms or you are breaking the law.
If your company violates copyright law, it can be taken to court and sued for damages or forced compliance to the license terms:
https://www.mend.io/resources/blog/the-100-million-case-for-...
https://www.natlawreview.com/article/gpl-open-source-litigat...
If the remedy for copyright infringement were just "oh, we got caught, guess we'll stop now", that would provide substantial incentive for people to violate licenses as long as they hoped they wouldn't get caught. The remedy for such violations needs to be substantial enough that it's not profitable to temporarily get away with.
I am jaded from practice around GDPR where the thinking of companies goes along the line: if we are caught, we will pay extra, but now we make big cash. And who knows, maybe we won't get caught.
"GitHub’s defense obligations do not apply if (i) the claim is based on Code that differs from a Suggestion provided by GitHub Copilot, (ii) you fail to follow reasonable software development review practices designed to prevent the intentional or inadvertent use of Code in a way that may violate the intellectual property or other rights of a third party, or (iii) you have not enabled all filtering features available in GitHub Copilot."
Do they define what constitutes "reasonable software development review practices designed to prevent the intentional or inadvertent use of Code in a way that may violate the intellectual property or other rights of a third party" ?
I was trying to find out what these exact filtering settings are but I land at this page [1].
The other links just download the Product Specific terms PDF again.
Not sure if this is an oversight or intentionally intended to be circular.
[1] https://docs.github.com/en/copilot/configuring-github-copilo...
To me this whole thing is like pandora's box and it will not in any way be put back into the box. In the long run isn't arguing about the code it generates and how it generates it mostly tilting at windmills? I've already met new / junior programmers that have used copilot and chatgpt to help them see how to approach certain problems or try to get better framing for what they couldn't quite get into the most accurate words to google.
I too would prefer these tools embody the ideal: no license violation, perfect citation of where the archetypes of the code came from. I've commented here today (amongst some great FOSS software engineers) to see if a genuine respectful conversation can be had about how just like torrents this one isn't going to be put back in the box no matter how many legal precedents attempt (or succeed) in cutting off heads of the hydra. It's utility seems like it will steamroll any attempts to stop or slow it down.
Am I wrong? Is it a fools errand to ask?
What? I don't see any utility outside of education and even there it's pretty sketchy.
For business, legal compliance is not a joke and instantly shuts it down. The only businesses willing to use ChatGPT for generating code would be naive young startups who don't realize some assembly is still required and the instructions are missing no matter how much they query the bot. That's called expertise (which they don't yet have). It's not good enough to just write the code. Someone has to comprehend it so they can tweak it as needed. At some point the tweaks will become unwieldy and require actual software engineering that the bot doesn't know how to do (transform from one design pattern to another and know which to use). More power to them if they can cobble something together and then succeed at maintaining it. By the time they're through they'll have pulled off so many miracles that they won't need the bot anymore and become experts. That's quite the trial by fire, but hey everyone has to find their way!
I'd have no objections to a tool that generated suggestions that came with attributions and license metadata, ready to insert into your project's file for third-party licenses. AI code suggestions are impressive.
I have objections to a tool that generates derived works from code without respecting the licenses of that code. For permissively licensed Open Source code, including that code without attribution deprives authors of their due credit (said credit often being how people get employment or funding). For copyleft Open Source code, including that code without using a compatible license violates the conditions upon which people made that code available for others to build upon and share. For proprietary code, including that code at all incurs legal risks.
We’ll hang back until other companies have litigated their way to some legislation around it.
No matter what is said, there are no license guarantees on the generated code, as you don’t know the exact provenance, so it seems only sensible to be on the safe side.
I would prefer to see full license attributions included in generated responses, though. Something that then also wouldn't be that difficult to generate a licenses file from?
Amazon's CodeWhisperer has a "reference tracker" that tells you the license of training data code if the generated response is within some similarity threshold, but that's still not good enough imo.
I don't think it's possible to do better than that with this technology.
I guess this is where the threshold comes from. Choose a generous margin and over-attribute rather than under-attribute.
Exactly. By all means build tools like this, but build them to actually comply with Open Source licenses. Provide a list of the licenses you don't mind copying from, and get back attributions with your suggestions.
Copilot could comply with MIT licenses by just outputting an MIT license with ALL the authors of code used in training.
But sure, disk size could be a problem.
They absolutely did, yes. The approach you're suggesting would work from a legal perspective, but the size might pose practical problems.
The result looks like my own code and is utilizing the already existing parts of my application. The code it writes for me solves problems that you cannot find a standard solution for anywhere and is definitely not something that could be attributed.
How Copilot is trained is an issue but answering the question "where did this code come from and what license is it under" would be impossible.
Not at all. I'm saying it's derived from large amounts of code, without respecting the licenses on that code.
> How Copilot is trained is an issue but answering the question "where did this code come from and what license is it under" would be impossible.
Then it shouldn't exist outside of demos of what could exist in the future if the showstopper legal problem gets solved. Let's get people treating that constraint as business-critical and start coming up with clever solutions, and see how long "impossible" lasts.
I understand that some folks don't believe the same thing, and use copyleft licenses so that their code can't be re-used in a closed way, and that's fair. Github shouldn't be training their product on copyleft licenses.
It's fair to call out its misuse of certain licenses, but "the equivalent of money laundering for violation of Open Source licenses" is simply inaccurate, as many licenses allow this type of re-use explicitly.
If you do, then by all means they're welcome to use it without attribution or preservation of copyright notices, per the terms of the license you used.
But for all the Open Source code, even permissive Open Source code, that does require attribution or preservation of copyright notices, that's still a license violation. People don't often think of permissive Open Source licenses as something that can be violated, but they absolutely can be.
Double-checking whether the generated part is a verbatim copy negates the speed advantage.
Possible infringements from similarity are even harder to search.
Was looking for a way to instruct CodePilot to abide by the following rules:
- Only use Apache v2, MIT or BSD licensed work for its recommendations. (Or a specific license set)
- Only use code trained on public repositories.
- Provide code attributions of the source code where the recommendations originate from.
I'm not sure if the last point is possible given these GPT type architectures but it would really help during code reviews.
Even if you use code under these license, you are still supposed to credit the authors by reproducing the license. So you need to know where it came from. Do you credit all the software the model was trained on?
The remaining use of OSS code has attributions.
That's a brilliant idea everyone can just copy and past the exact same attribution file and be done with it.
That's what a good chunk of people do anyway at work. No one really cares nor will care. We were already moving in that direction anyway this will just accelerate it.