Personally it would make the choice to say no to the entire thing a whole lot easier if they self-reported on themselves automatically and with no recourse to hide the fact that they've used LLMs. I want to see it for dependencies (I already avoid them, and would especially do so with ones heavily developed via LLMs), products I'd like to use, PRs submitted to my projects, and so on, so I can choose to avoid them.

Mostly this is because, all things considered, I really do not need to interact with any of that, so I'm doing it by choice. Since it's entirely voluntary I have absolutely no incentive to interact with things no one bothered to spend real time and effort on.

If you choose not to use software written with LLM assisstance, you'll use to a first approximation 0% of software in the coming years.

Even excluding open source, there are no serious tech companies not using AI right now. I don't see how your position is tenable, unless you plan to completely disconnect.

This is shouting at the clouds I'm afraid (I don't mean this in a dismissive way). I understand the reasoning, but it's frankly none of your business how I write my code or my commits, unless I choose to share that with you. You also have a right to deny my PRs in your own project of course, and you don't even have to tell me why! I think on github at least you can even ban me from submitting PRs.

While I agree that it would be nice to filter out low effort PRs, I just don't see how you could possibly police it without infringing on freedoms. If you made it mandatory for frontier models, people would find a way around it, or simply write commits themselves, or use open weight models from China, etc.

I mean sure, in the same sense that law enforcement would be a lot easier if all the criminals just came to the police station and gave themselves up

Again though, people can trivially hide the fact they used an LLM to whatever extent, so we kind of need to adjust accordingly.

Even if saying no to all LLM involvement seemed pertinent, it doesn't seem possible in the first place.

Accountability. Same reason I want to read human written content rather than obvious AI: both can be equally shit, but at least with humans there's a high probability of the aspirational quality of wanting to be considered "good"

With AI I have no way of telling if it was from a one line prompt or hundreds. I have to assume it was one line by default if there's no human sticking their neck out for it.

The human who submitted the PR is 100% accountable either way, thats partly my point.

Disclosing AI has its purposes, I agree, but its not like we can reliably get everyone to do it anyway, which also leads me to thinking this way.

LLMs can make mistakes in different ways than humans tend to. Think "confidently wrong human throwing flags up with their entire approach" vs. "confidently wrong LLM writing convincing-looking code that misunderstands or ignores things under the surface."

Outside of your one personal project, it can also benefit you to understand the current tendencies and limitations of AI agents, either to consider whether they're in a state that'd be useful to use for yourself, or to know if there are any patterns in how they operate (or not, if you're claiming that).

Burying your head in the sand and choosing to be a guinea pig for AI companies by reviewing all of their slop with the same care you'd review human contributions with (instead of cutting them off early when identified as problematic) is your prerogative, but it assumes you're fine being isolated from the industry.

Sure, the point about LLM "mistakes" etc being harder to detect is valid, although I'm not entirely sure how to compare this with human hard to detect mistakes. If anything I find LLM code shortcomings often a bit easier to spot because a lot of the time they're just uneeded dependencies, useless comments, useless replication of logic, etc. This is where testing come into play too and I'm definitely reviewing your tests (obviously).

>Burying your head in the sand and choosing to be a guinea pig for AI companies by reviewing all of their slop with the same care you'd review human contributions with (instead of cutting them off early when identified as problematic) is your prerogative, but it assumes you're fine being isolated from the industry.

I mean listen: I wish with every fiber of my being that LLMs would dissapear off the face of the earth for eternity, but I really don't think I'm being "isolating myself from the industry" by not simply dismissing LLM code. If I find a PR to be problematic I would just cut it off, thats how I review in the first place. I'm telling some random human who submitted the code to me that I am rejecting their PR cause its low quality, I'm not sending anthropic some long detailed list of my feedback.

This is also kind of a moot point either way, because everyone can just trivially hide the fact that they used LLMs if they want to.

> If anything I find LLM code shortcomings often a bit easier to spot because a lot of the time they're just uneeded dependencies, useless comments, useless replication of logic, etc.

By this logic, it's useful to know whether something was LLM-generated or not because if it was, you can more quickly come to the conclusion that it's LLM weirdness and short-circuit your review there. If it's human code (or if you don't know), then you have to assume there might be a reason for whatever you're looking at, and may spend more time looking into it before coming to the conclusion that it's simple nonsense.

> This is also kind of a moot point either way, because everyone can just trivially hide the fact that they used LLMs if they want to.

Maybe, but this thread's about someone who said "I'd like to be able to review commits and see which were substantially bot-written and which were mostly human," and you asking why. It seems we've uncovered several feasible answers to your question of "why would you want that?"

>It seems we've uncovered several feasible answers to your question of "why would you want that?"

Fair enough