GitHub Copi­lot inves­ti­ga­tion

RSI took away my ability to write any significant amount of code 30 yrs ago. co-pilot plus speech recognition restored that ability. what impressed me most was that from a textual description,co-pilot gave me code that could have been written by my mind and pre-injury hands.

from the comments here, if I push copilot into giving me code that I would have written for a given problem and that code violates licenses, then who is responsible for the copyright violation? co-pilot for giving me code that looks like copyrighted code or me for tweaking co-pilot commands to give me the code I envisioned which looks like copyrighted code?

also consider that the very tools used for solving problems in code lead coders to a small number of solutions for a given problem. is it plagiarism or parallel original thought?

also consider that when I wrote code, if I was solving a similar problem to what I solved before, I recreated that previously used code fragment (or larger) and use it to solve the problem at hand. I had zero issues leaving a trail of duplicate code behind me especially if the code was a major part of a software patent.

I didn't care, my code was lauded for it's readability and reliability. reuse the same concepts in multiple variations, you get real good and writing code correctly.

maybe co-pilot like programs could scan existing code bases and find examples of code fragment plagiarism with the goal of showing that software copyrights are useless.

Embrace, Extend, Extinguish. Takes a while to get to the Extinguish phase.

And it seems pretty clear to me that it is fair use, because it's not merely reproducing or creating a derivative work, but actually extracting patterns and modeling the works in a way that is intended to be used to create new and unrelated works. The fact that an occasional piece of code here and there might be reproduced verbatim is no different than e.g. Cliffs Notes occasionally quoting a passage, and Cliffs Notes are a well established case of fair use that to me, at least, seems even closer to "the line" than Copilot or Stable Diffusion.

FTA: "On the other hand, maybe you’re a fan of Copi­lot who thinks that AI is the future and I’m just yelling at clouds. First, the objec­tion here is not to AI-assisted cod­ing tools gen­er­ally, but to Microsoft’s spe­cific choices with Copi­lot. We can eas­ily imag­ine a ver­sion of Copi­lot that’s friend­lier to open-source devel­op­ers—for instance, where par­tic­i­pa­tion is vol­un­tary, or where coders are paid to con­tribute to the train­ing cor­pus."

This is the same argument that people use about Stable Diffusion, and it's kinda meh to me...I guess it'd be nice to allow people to opt-out, like Stable Diffusion is doing with their next versions, especially since a negligible percentage of people will do so and it won't affect the models at all. But yes, it basically is yelling at clouds. Opt-in would cripple models, and some people would make them anyways and just keep them secret, which is worse for the world. And at the end of the day, this really does just seem to me like a fair use of stuff that you've published on the Internet for anyone with a browser to look at. The AI models of the future are going to gobble the whole net up, and if you don't want them ingesting your stuff and learning from it, then you just shouldn't make it freely available.

If OpenAI/GitHub/MS really wanted to get ahead of this and head off any potential legal conflict, they could always just open source the models and weights, which would be in line with the name "OpenAI"...it would be a minor project to scrape all the correct headers to add to a license file(s), but negligible compared to the many millions of dollars spent on training.

One thing I worry about is if the uncertainty around copyright violation cools down activity in open models while raising the price of commercial offerings. Commercial entities can afford devoting resources towards mitigating copyright violations such as eating the cost of maintaining a database of frequently copied code and identifying most likely origin combined with a large semantic database of code snippets.

An open equivalent might be wary of being accused of contributing to copyright violations since in that scenario, there is no way to force people to respect it.

Absolutely incorrect, fair use applies to *reproducing* small volumes of work, not analyzing it. If I published an article gleaning some conclusion based on an analysis of 10,000 issues of the New York Times, that would still 100% be fair use; similarly, Google is absolutely allowed to publish word count metrics based on their scanned book repo, even though publishing the books themselves is not fair use. You are trying to read something into the fair use doctrine that is absolutely not there (to the extent that anything is there, which very little is other than "I'll know it when I see it" and prior case law, unfortunately).