My question on AI generated contributions and content in general: on a long enough timeline, with ever improving advancements in AI, how can people reliably tell the difference between human and AI generated efforts?
Sure now it is easy, but in 3-10 years AI will get significantly better. It is a lot like the audio quality of an MP3 recording. It is not perfect (lossless audio is better), but for the majority of users it is "good enough".
At a certain point AI generated content, PR's, etc will be good enough for humans to accept it as "human". What happens then, when even the best checks and balances are fooled?
> disclosure if "a significant portion of the contribution is taken from a tool without manual modification", and labeling of such contributions with "a clear disclaimer or a machine-readable tag like '[AI-Generated]'.
Quixotic, unworkable, pointless. It’s fundamentally impossible (at least without a level of surveillance that would obviously be unavceptable) to prove the “artisanal hand-crafted human code” label.
> contributors should "fully understand" their submissions and would be accountable for the contributions, "including vouching for the technical merit, security, license compliance, and utility of their submissions".
This is in the right direction.
I think the missing link is around formalizing the reputation system; this exists for senior contributors but the on-ramp for new contributors is currently not working.
Perhaps bots should ruthlessly triage in-vouched submissions until the actor has proven a good-faith ability to deliver meaningful results. (Or the principal has staked / donated real money to the foundation to prove they are serious.)
I think the real problem here is the flood of low-effort slop, not AI tooling itself. In the hands of a responsible contributor LLMs are already providing big wins to many. (See antirez’s posts for example, if you are skeptical.)
Very reasonable stance. I see reviewing and accepting a PR is a question of trust - you trust the submitter to have done the most he can for the PR to be correct and useful.
Something might be required now as some people might think that just asking an LLM is "the most he can done", but it's not about using AI it's about being aware and responsible about using it.
A lot of low quality AI contributions arrive using free tiers of these AI models, the output of which is pretty crap. On the other hand, if you max out the model configs, i.e. get "the best money can buy", then those models are actually quite useful and powerful.
OSS should not miss out on the power LLMs can unleash. Talking about the maxed out versions of the newest models only, i.e. stuff like Claude 4.5+ and Gemini 3, so developments of the last 5 months.
But at the same time, maintainers should not have to review code written by a low quality model (and the high quality models, for now, are all closed, although I heard good things about Minmax 2.5 but I haven't tried it).
Given how hard it is to tell which model made a specific output, without doing an actual review, I think it would make most sense to have a rule restricting AI access to trusted contributors only, i.e. maintainers as a start, and maybe some trusted group of contributors where you know that they use the expensive but useful models, and not the cheap but crap models.
My two cents: I've been coding practically my entire life, but a few years back I sustained a pretty significant and lasting injury to my wrists. As such, I have very little tolerance for typing. It's been quite a problem and made full time work impossible.
With the advent of LLMs, AI-autocomplete, and agent-based development workflows, my ability to deliver reliable, high-quality code is restored and (arguably) better. Personally, I love the "hallucinations" as they help me fine-tune my prompts, base instructions, and reinforce intentionality; e.g. is that >really< the right solution/suggestion to accept? It's like peer programming without a battle of ego.
When analyzing problems, I think you have to look at both upsides and downsides. Folks have done well to debate the many, many downsides of AI and this tends to dominate the conversation. Probably thats a good thing.
But, on the flip side, I personally advocate hard for AI from the point-of-view on accessibility. I know (more-or-less) exactly what output I'm aiming for and control that obsessively, but it's AI and my voice at the helm instead of my fingertips.
I also think it incorrect to look at it from a perspective of "does the good outweigh the bad?". Relevant, yes, but utilitarian arguments often lead to counter-intuitive results and end up amplifying the problems they seek to solve.
I'd MUCH rather see a holistic embrace and integration of these tools into our ecosystems. Telling people "no AI!" (even if very well defined on what that means) is toothless against people with little regard for making the world (or just one specific repo) a better place.
This resonates. Recently, I've started to consider Claude as a partner. I like how he's willing to accept he's wrong when you provide evidence. It can be more pleasant than working with humans.
As someone who got a pretty severe case of carpal tunnel in his youth that can still blow up today, I have to admit I have worried about my ability to work. "Will I have to become a manager?" Etc.
> I'd MUCH rather see a holistic embrace and integration of these tools into our ecosystems. Telling people "no AI!" (even if very well defined on what that means) is toothless against people with little regard for making the world (or just one specific repo) a better place.
If it makes them go thru AI contributions to make sure there is no AI nonsense in them, that's already massive win.
The AI on itself is not a problem
> But, on the flip side, I personally advocate hard for AI from the point-of-view on accessibility. I know (more-or-less) exactly what output I'm aiming for and control that obsessively, but it's AI and my voice at the helm instead of my fingertips.
and you are the 1% (assuming your claims are true and not hallucinated gains, which are common in AI world too), vast majority of AI contributions are peak lazy, or at best goal-seeking with no regard of the target, consequences or quality
THAT is what people complain about. If AI was just used to shortcut the boring, augument the knowledge and produce better quality code, there would be very little arugments against AI-driven contributions. But that is not the case, the AI pundits will purposefully not check the AI output just because that would require time and knowledge and that looks bad on "how faster AI makes you" KPI
lol You are actually trying to argue and say "Oh actually, I love how AI fucks up, it makes me keep on my toes."
That's like saying I love hiring fuck ups that randomly do out of context and out of ruleset work for me when I ask them to perform tasks.
I would also argue to you that "folks" have done more well to debate the upsides of AI. It is pretty much all I ever see when I come to this website any more the last couple of years. Oh, and by coincidence, the operator/owner of the website just happens to be at the helm of ChatGPT. How convenient.
On the code side of the issue, I would say that AI completion and chat are ok because people are still forced to interact with the generated code. When coding with agents people have to go out of their way to do it
That's a super nice story. Sometimes we tend to forget the contributions of AI for the visually impaired or hearing-impaired people—for example, subtitles on Meta glasses or audio descriptions and such.
Concerns about the wasting of maintainer’s time, onboarding, or copyright, are of great interest to me from a policy perspective. But I find some of the debate around the quality of AI contributions to be odd.
Quality should always be the responsibility of the person submitting changes. Whether a person used LLMs should not be a large concern if someone is acting in good-faith. If they submitted bad code, having used AI is not a valid excuse.
Policies restricting AI-use might hurt good contributors while bad contributors ignore the restrictions. That said, restrictions for non-quality reasons, like copyright concerns, might still make sense.
Fork it to Slobian and let the clankers go to town creating, approving and merging pull requests by themselves. Look at the install base to see what people prefer.
An interesting concept that stood out to me. Committing the prompts instead of the resulting code only.
It it really true the LLM's are non-deterministic? I thought if you used the exact input and seed with the temperature set to 0 you would get the same output. It would actually be interesting to probe the commit prompts to see how slight variants preformed.
The quality argument against LLM-generated code has always seemed weak to me. Maintainers already review patches because humans routinely submit bad code. The review process is the filter.
The website is absolutely atrocious, dark mode has pitch-black background with bold 100% white glowing text in foreground, shitty font, way to wide text.
Seriously how is lwn.net even still so popular with such an atrocious unreadable ugly website. Well yes I get the irony of asking that on HN (I use an extension to make it better).
This reminds me of the Hacktoberfest situation where maintainers were getting flooded with low-quality PRs. This could be that, but on steroids and constantly, not just one month.
Did anyone say it is a risk? What if courts eventually decide that users of products of closed models have to pay some reasonable fee to the owners of the training data?
In some sense, I think the promise of free software is more real today than before because everyone else's software is replicable for relatively cheap. That's probably a much stronger situation for individual freedom to replicate and run code than in the era of us relying on copyright.
LLM-generated code is incompatible with libre software. It's extremely frustrating to see such a lack of conviction to argue this point forcefully and repeatedly. It's certainly bad enough to see such a widespread embrace of this dangerous and anti-libre technology within proprietary software teams, but when it comes to FLOSS, it should be a no-brainer to formalize an emphatic anti-slop contributor policy.
Given the 10x+ productivity rate, it would be reasonable to establish a higher quality acceptance bar for AI submissions. 50-100% more performance, correctness, usability testing , and one round of human review.
If a change used to take a day or two, and now requires a few minutes, then it's fair to ask for a couple hours more prompting to add the additional tangible tests to compensate for any risks of hallucinations or low quality code sneaking in
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[ 3.3 ms ] story [ 67.7 ms ] threadSure now it is easy, but in 3-10 years AI will get significantly better. It is a lot like the audio quality of an MP3 recording. It is not perfect (lossless audio is better), but for the majority of users it is "good enough".
At a certain point AI generated content, PR's, etc will be good enough for humans to accept it as "human". What happens then, when even the best checks and balances are fooled?
The ones that make the headlines here on HN are not subtle at all, they're probably the bottom of the barrel of AI users.
Quixotic, unworkable, pointless. It’s fundamentally impossible (at least without a level of surveillance that would obviously be unavceptable) to prove the “artisanal hand-crafted human code” label.
> contributors should "fully understand" their submissions and would be accountable for the contributions, "including vouching for the technical merit, security, license compliance, and utility of their submissions".
This is in the right direction.
I think the missing link is around formalizing the reputation system; this exists for senior contributors but the on-ramp for new contributors is currently not working.
Perhaps bots should ruthlessly triage in-vouched submissions until the actor has proven a good-faith ability to deliver meaningful results. (Or the principal has staked / donated real money to the foundation to prove they are serious.)
I think the real problem here is the flood of low-effort slop, not AI tooling itself. In the hands of a responsible contributor LLMs are already providing big wins to many. (See antirez’s posts for example, if you are skeptical.)
Something might be required now as some people might think that just asking an LLM is "the most he can done", but it's not about using AI it's about being aware and responsible about using it.
A lot of low quality AI contributions arrive using free tiers of these AI models, the output of which is pretty crap. On the other hand, if you max out the model configs, i.e. get "the best money can buy", then those models are actually quite useful and powerful.
OSS should not miss out on the power LLMs can unleash. Talking about the maxed out versions of the newest models only, i.e. stuff like Claude 4.5+ and Gemini 3, so developments of the last 5 months.
But at the same time, maintainers should not have to review code written by a low quality model (and the high quality models, for now, are all closed, although I heard good things about Minmax 2.5 but I haven't tried it).
Given how hard it is to tell which model made a specific output, without doing an actual review, I think it would make most sense to have a rule restricting AI access to trusted contributors only, i.e. maintainers as a start, and maybe some trusted group of contributors where you know that they use the expensive but useful models, and not the cheap but crap models.
With the advent of LLMs, AI-autocomplete, and agent-based development workflows, my ability to deliver reliable, high-quality code is restored and (arguably) better. Personally, I love the "hallucinations" as they help me fine-tune my prompts, base instructions, and reinforce intentionality; e.g. is that >really< the right solution/suggestion to accept? It's like peer programming without a battle of ego.
When analyzing problems, I think you have to look at both upsides and downsides. Folks have done well to debate the many, many downsides of AI and this tends to dominate the conversation. Probably thats a good thing.
But, on the flip side, I personally advocate hard for AI from the point-of-view on accessibility. I know (more-or-less) exactly what output I'm aiming for and control that obsessively, but it's AI and my voice at the helm instead of my fingertips.
I also think it incorrect to look at it from a perspective of "does the good outweigh the bad?". Relevant, yes, but utilitarian arguments often lead to counter-intuitive results and end up amplifying the problems they seek to solve.
I'd MUCH rather see a holistic embrace and integration of these tools into our ecosystems. Telling people "no AI!" (even if very well defined on what that means) is toothless against people with little regard for making the world (or just one specific repo) a better place.
This resonates. Recently, I've started to consider Claude as a partner. I like how he's willing to accept he's wrong when you provide evidence. It can be more pleasant than working with humans.
I think you have a good point
If it makes them go thru AI contributions to make sure there is no AI nonsense in them, that's already massive win.
The AI on itself is not a problem
> But, on the flip side, I personally advocate hard for AI from the point-of-view on accessibility. I know (more-or-less) exactly what output I'm aiming for and control that obsessively, but it's AI and my voice at the helm instead of my fingertips.
and you are the 1% (assuming your claims are true and not hallucinated gains, which are common in AI world too), vast majority of AI contributions are peak lazy, or at best goal-seeking with no regard of the target, consequences or quality
THAT is what people complain about. If AI was just used to shortcut the boring, augument the knowledge and produce better quality code, there would be very little arugments against AI-driven contributions. But that is not the case, the AI pundits will purposefully not check the AI output just because that would require time and knowledge and that looks bad on "how faster AI makes you" KPI
That's like saying I love hiring fuck ups that randomly do out of context and out of ruleset work for me when I ask them to perform tasks.
I would also argue to you that "folks" have done more well to debate the upsides of AI. It is pretty much all I ever see when I come to this website any more the last couple of years. Oh, and by coincidence, the operator/owner of the website just happens to be at the helm of ChatGPT. How convenient.
Wish you the best.
Quality should always be the responsibility of the person submitting changes. Whether a person used LLMs should not be a large concern if someone is acting in good-faith. If they submitted bad code, having used AI is not a valid excuse.
Policies restricting AI-use might hurt good contributors while bad contributors ignore the restrictions. That said, restrictions for non-quality reasons, like copyright concerns, might still make sense.
It it really true the LLM's are non-deterministic? I thought if you used the exact input and seed with the temperature set to 0 you would get the same output. It would actually be interesting to probe the commit prompts to see how slight variants preformed.
LLM submissions are cheap to send and expensive to receive.
This creates a spam (slop) problem, just like in other contexts.
Seriously how is lwn.net even still so popular with such an atrocious unreadable ugly website. Well yes I get the irony of asking that on HN (I use an extension to make it better).
If a change used to take a day or two, and now requires a few minutes, then it's fair to ask for a couple hours more prompting to add the additional tangible tests to compensate for any risks of hallucinations or low quality code sneaking in