Direct link to the LLM Policy Discussion: https://invent.kde.org/plasma/plasma-workspace/-/work_items/187
Example of a KDE dev not wanting environmental concerns to play any role, despite KDE having an environmental project:
Devs rejecting any notion of transparency by disclosing AI usage in code submissions (in direct opposition to advice from the FSFE):
And all of this is coming right after the debacle with an AI slop project being allowed to give a presentation at Akademy, and the person asking how this was allowed being blocked by KDE:
https://lemmy.nz/post/42029517
as well as the discussion thread bringing up legitimate concerns about AI usage being closed:
https://discuss.kde.org/t/sorry-to-bring-up-a-contentious-topic-kde-ai-llm-policy/46333/164
As someone who genuinely loves KDE, and has even donated to the project multiple times, I sadly have to accept that the majority of KDE have hopped onto the Pro-AI train, and they will not be dissuaded otherwise.
Yes, that’s fine. And it’s also easy to enforce - just treat any code as if it’s written by a human (except obviously machine generated code like hardware descriptions etc).
Being against AI and LLMs is all fine and dandy, but it kinda takes ridiculous shape now.
However, I would prefer if open source tools would only allow the usage of open weight models and self-hosted systems. But then again, that’s my idealism talking.
I hate vibe coding, detest it, i’m tired of it. it wastes time and resources. That being said I use AI for debugging and as a glorified rubber duck. I don’t let it write ANYTHING but I will allow it to review code and make suggestions. Generally, I’d say 8 times out of 10 the suggestions are garbage BUT it will lead me down the right path. it’s a rubber duck that can talk back. So in that regards it has improved my build times, it has sped me up without actually touching the code itself.
THAT’s what AI/LLMs SHOULD be used for. an assistant that doesn’t directly interact with the project. a consultant to your code if you will.
unfortunately many people can’t make that separation and they sit on both sides of the fence.
LLMs are great for rubberducking and diagnosis, forensics, and the like.