Subjecting every real contributor to the "AI guardian" would be unfair, and shadow banning is ineffective when you're dealing with a large number of drive-by nuisances rather than a small number of dedicated trolls. Public humiliation is actually a great solution here.

> Subjecting every real contributor to the "AI guardian" would be unfair

Had my first experience with an "AI guardian" when I submitted a PR to fix a niche issue with a library. It ended up suggesting that I do things a different way which would have to involve setting a field on a struct before the struct existed (which is why I didn't do that in the first place!)

Definitely soured me on the library itself and also submitting PRs on github.

How effective is it against people who just simply does not care?

I suspect people are doing it to pad their resume with "projects contributed to" rather than to troll the maintainers, so if they're paying any attention they probably do care...

Most people do, and those who don't still get banned so...

what you say, is of course the only relavent issue. I can attest to my own experiences on both sides of this situation, one running a small business that is bieng inundated by job seekers who are sending AI written letters and resumes, and dealing with larger companys that have excess capacity to throw at work orders, but an inability to understand detail, AND, AND!, my own fucking need to survive in this mess, that is forceing me to dismiss certain niceties and adhearance to "proffesional" (ha!), norms. so while the inundation from people from India(not just), is sometimes irritating, I have also wrangled with some of them personaly, and under all that is generaly just another human, trying to make by best they can, so....

You could easily guard against bullshit issues. So you can focus on what matters. If the issue is legit goes ahead to a human reviewer. If is run of the mill ai low quality or irrelevant issue, just close. Or even nicer: let the person that opened the issue to "argue" with the ai to further explain that is legit issue for false positives.

How is an llm supposed to identify an llm-generated bullshit issue...? It's the fox guarding the henhouse.

Just try and you'll see if it can work. Just copy paste some of these issues give context of the project and ask if makes sense

the only way to stop a bad guy with a llm is with a good guy with a llm

That's just shoveling money to tech companies

I intensely dislike the idea that we need more AI in order to deal with AI.

If I ever need to start using an AI to summarize text that someone else has generated with AI from a short summary, I'm gonna be so fucking done.

I relate, and then realized that's been the basis of spam handling for decades now. It's depressing, and we aren't putting this genie back in the bottle unfortunately.

How so?

Spam, for decades, has been a matter of just shoveling truckloads of emails out the door and hoping that one or two get a gullible match.

Blocking spam, for decades, has been a matter of heuristic pattern-matching.

I don't see how that is the same as "fighting LLMs with LLMs", or how it could be said to be the same as how spam is made and used.

It's analogous in the sense that tons of machine-submitted emails exist for the sole purpose of being mechanically triaged. The technology might be slightly different (it may not be LLMs through and through), but the pattern is the same.

You're done dude. I'm sure it's already happening.

What are you going to do now?

It's not happening because I'm not using an AI to summarize text. At the moment slop text is also fairly easy to recognise, so I can just ignore it instead.

It's not already happening as of today? You can adapt or... You heard of Darwin right?

Small brain: create a solution looking for a problem

Big brain: create a solution solving an existing problem

Galaxy brain: create a solution that creates its own problems