Comment on AI’s Unpaid Debt: How LLM Scrapers Destroy the Social Contract of Open Source
melfie@lemy.lol 6 days agoI’d also be curious about where that 15-20% productivity increase comes from in aggregate.
This is from a Stanford study that is summarized here:
linkedin.com/…/does-ai-actually-boost-developer-p…
There are other studies with different conclusions, but this one aligns with my own experience. To your point about how AI won’t reproduce the Linux kernel, this study also points out that AI is significantly less effective, even going into the negative, with complex codebases, which is in agreement with what you said, since the Linux kernel certainly qualifies as a complex codebase.
they are stealing code meant to be free and public with any derivative works, profiting off it, and then refusing to honor the license model of the code/project they stole.
I agree big tech is using open source unethically, but how much different is this situation from the other ways big tech profits from open source without contributing back?
yoasif@fedia.io 6 days ago
Destroying "share alike" doesn't undermine the core value of open source? What IS the core value?
melfie@lemy.lol 6 days ago
The LLMs are not distributing the GPL code, their weights are being trained on it. You can’t just have Copilot pump out something that works like the Linux kerne or Blender, except with different code that isn’t subject to the GPL license. At best, the AI can learn from it and assist humans with developing a proprietary alternative. In that case, it’s not really that much better than having humans study a GPL codebase and make a proprietary alternative without AI. It’s still going to cost a lot of money to replicate the thing no matter what, so why not just save money and use the GPL code and contribute back?
yoasif@fedia.io 6 days ago
You can't "train" on code you haven't copied. That is kind of obvious, right? So did they have the right to copy and then reproduce the work without attribution?
melfie@lemy.lol 6 days ago
Yeah, I guess this is a bit of gray area. With GPL, you only have rights to code if it was distributed to you. In the case of GPL code that has only been distributed to select people and none of those people distributed it to the general public, but GitHub still trained their models on the private repo, then that would technically be in violation of the license. This would be a more niche scenario, though, since the intent normally is public distribution.