The without disclosure part tells everything you need to know here. If it’s such a benign and maybe even beneficial thing to do then why are you hiding it? What possible reason could you have not to label that? In an open source Community shouldn’t everything like that be known?
There are so many levels of LLM involvement and once you make this distinction you actually have to devote some of your limited resources to define and enforce it. So I think it might not be strictly beneficial, but possibly also have downsides.
Where would you draw the line at which point it counts as LLM involvement? Having one run as some sort of spell/syntax checker? Doing some research (and being influenced by it) before hand coding something? Having it create a working prototype and then reimplementing it by hand? If you use code from somewhere else to solve a problem and ai use has not been disclosed for this code, do you automatically have to assume LLM usage was involved or is there plausible deniability?
I think in the end you’d have to use too many resources check it and debate where the line is drawn, when the real question is how you retain human knowledge and engagement within your community.
I wonder what’s the reason to make it optional? I think I’ve seen this approach with other projects as well. Isn’t transparency and accountability a good thing? Also, this kind of information helps immensely when reading pull requests or silly bug reports. And Debian acknowledge there might be licensing issues. So it might become some sort of liability to them once it taints everything and we can’t even tell?! So why? What’s the upside? Adorn oneself with borrowed plumes and not being forced to disclose the fact? Or too much bookkeeping?
Not really worth discussing - it’s not benign, and it can be made purposefully not benign by a third party without notification or knowledge. A third party who has already demonstrated a penchant for world domination, both technologically and physically.
I should hope that open source developers are exclusively using open source models that are trained on open source projects.
I mean, I would think, at least. It seems to me that most of the people in charge of big projects are usually FOSS purists.
That’s part of the reason why AI scrapers are breaking the small web. FOSS purists really have no significant defense against it aside from Anubis.
Real DoS protection comes from capacity, which costs serious dollars, especially in this day and age where botfarms can be hired by the hour for rather cheap and record-breaking attacks seem to happen like monthly.
The alternative is using a CDN, but there are none that align with FOSS ideals. And for CDNs to be really effective, you need them to break open TLS and handle the decrypted traffic, which raises privacy concerns on top.
But anyways…most license agreements would make it a requirement that if you’re using an open-source model, that it be properly attributed, right?
I should hope that open source developers are exclusively using open source models that are trained on open source projects.
Most developers who use these tools (even FLOSS developers) appear to be using the corporate owned models that were definitely trained on both proprietary source code and code that is incompatible with the GPL license. Some EU courts have also already judged that LLM code cannot be copyrighted, which also means it cannot be licensed as GPL.
Currently, all code generated with an LLM has a 3 to 10% chance of unknowingly plagiarizing the copyrighted code it was trained on, and any FLOSS project that uses it is making a huge gamble that their codebase won’t be scanned by corporations in the future looking for violations to sue about, shut down rival FLOSS projects, etc.
Eye contact is benign for most of us. We still give it a context warning in civilized circles. It costs us almost nothing, and lets people make an informed decision what you engage with.
The without disclosure part tells everything you need to know here. If it’s such a benign and maybe even beneficial thing to do then why are you hiding it? What possible reason could you have not to label that? In an open source Community shouldn’t everything like that be known?
There are so many levels of LLM involvement and once you make this distinction you actually have to devote some of your limited resources to define and enforce it. So I think it might not be strictly beneficial, but possibly also have downsides.
Where would you draw the line at which point it counts as LLM involvement? Having one run as some sort of spell/syntax checker? Doing some research (and being influenced by it) before hand coding something? Having it create a working prototype and then reimplementing it by hand? If you use code from somewhere else to solve a problem and ai use has not been disclosed for this code, do you automatically have to assume LLM usage was involved or is there plausible deniability?
I think in the end you’d have to use too many resources check it and debate where the line is drawn, when the real question is how you retain human knowledge and engagement within your community.
I wonder what’s the reason to make it optional? I think I’ve seen this approach with other projects as well. Isn’t transparency and accountability a good thing? Also, this kind of information helps immensely when reading pull requests or silly bug reports. And Debian acknowledge there might be licensing issues. So it might become some sort of liability to them once it taints everything and we can’t even tell?! So why? What’s the upside? Adorn oneself with borrowed plumes and not being forced to disclose the fact? Or too much bookkeeping?
I think it’s just the simple fact that there’s no way to enforce it
Which tells a lot about how good they are. Slop is slop because it’s bad, but a high quality PR isn’t
Conversely… if it’s so benign, why should it have a label?
Not really worth discussing - it’s not benign, and it can be made purposefully not benign by a third party without notification or knowledge. A third party who has already demonstrated a penchant for world domination, both technologically and physically.
Code in general is proven not to be benign
Excuse you my code doesn’t even compile properly, so it can not be malign by definition.
I should hope that open source developers are exclusively using open source models that are trained on open source projects.
I mean, I would think, at least. It seems to me that most of the people in charge of big projects are usually FOSS purists.
That’s part of the reason why AI scrapers are breaking the small web. FOSS purists really have no significant defense against it aside from Anubis.
Real DoS protection comes from capacity, which costs serious dollars, especially in this day and age where botfarms can be hired by the hour for rather cheap and record-breaking attacks seem to happen like monthly.
The alternative is using a CDN, but there are none that align with FOSS ideals. And for CDNs to be really effective, you need them to break open TLS and handle the decrypted traffic, which raises privacy concerns on top.
But anyways…most license agreements would make it a requirement that if you’re using an open-source model, that it be properly attributed, right?
Most developers who use these tools (even FLOSS developers) appear to be using the corporate owned models that were definitely trained on both proprietary source code and code that is incompatible with the GPL license. Some EU courts have also already judged that LLM code cannot be copyrighted, which also means it cannot be licensed as GPL.
Currently, all code generated with an LLM has a 3 to 10% chance of unknowingly plagiarizing the copyrighted code it was trained on, and any FLOSS project that uses it is making a huge gamble that their codebase won’t be scanned by corporations in the future looking for violations to sue about, shut down rival FLOSS projects, etc.
Eye contact is benign for most of us. We still give it a context warning in civilized circles. It costs us almost nothing, and lets people make an informed decision what you engage with.
It would be Useful for doing a retrospective on whether AI is helpful or not