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Comment by mr-wendel | Hacker News Reader

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.

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> 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.

That doesn't address the controversy because you are a reasonable person assuming that other people using AI are reasonable like you, and know how to use AI correctly.

The rumors we hear have to do with projects inundated with more pull requests that they can review, the pull requests are obviously low quality, and the contributors' motives are selfish. IE, the PRs are to get credit for their Github profile. In this case, the pull requests aren't opened with the same good faith that you're putting into your work.

In general, a good policy towards AI submission really has to primarily address the "good faith" issue; and then explain how much tolerance the project has for vibecoding.

>other people are reasonable like you

No AI needed. Spam on the internet is a great example of the amount of unreasonable people on the internet. And for this I'll define unreasonable as "committing an action they would not want committed back at them".

AI here is the final nail in the coffin that many sysadmins have been dealing with for decades. And that is that unreasonable actors are a type of asymmetric warfare on the internet, specifically the global internet, because with some of these actors you have zero recourse. AI moved this from moderately drowning in crap to being crushed under an ocean of it.

Going to be interesting to see how human systems deal with this.

> Spam on the internet is a great example of the amount of unreasonable people on the internet.

AI also generates spam though, so this is a much bigger problem than merely "unreasonable" people alone.

I mean, AI generates spam at the behest of unreasonable people currently, and we can just think of it as a powerful automated extension of other technologies. We could say it's a new problem in quantity but the same old problem in kind.

Now, with that said I don't think we're very far from automated agents causing problems all on their own.

Every order of magnitude of difference constitutes a categorical difference.

The ability to create spam instantly, fitted perfectly to any situation, and doing that 24/7, everywhere, is very different from before. Before, spam was annoying but generally different enough to tell apart. It was also (in general) never too much as to make an entire platform useless.

With AI, the entire internet IS spam. No matter what you google or look at, there's a very high chance it's AI spam. The internet is super duper extra dead.

And the incentive to spam. AI pull request writers feel like they're helping the project, not hurting it, so they do it a lot more.

And even if you figure out a reliable way to detect AI, guess what, USERS USE IT TOO for legitimate content, so you can't even use system like this. It's horrid

I tried to build something: https://github.com/YM2132/PR_guard which aims to help in these cases. It's not perfect but with stronger AI detection tools (Pangram) it could be improved although the issue of cost then arises and who pays for it.

"The internet is super duper extra dead."

I get unreasonably angry when I read this statement, or similar ones.

If you mean "portions of the web I go to or my email inbox", you may be right.

But for the rest of us that hang out in one or multiple private spaces, sometimes with connections between them, the internet is better connected and easier to find people, groups, information, and interests than ever before.

> Going to be interesting to see how human systems deal with this.

At least a bunch of lawyers already got hit when their court filings cited hallucinated cases. If this trend continues, I'll not be surprised when some end up disbarred.

This seems self-correcting. Every lawyer, and maybe court, will use AI to review the other party's filings for such things. AI overseeing what is true and what is not - nothing disturbing about that distopian future.

> AI here is the final nail in the coffin

so far*

> The rumors we hear have to do with projects inundated with more pull requests that they can review, the pull requests are obviously low quality, and the contributors' motives are selfish. IE, the PRs are to get credit for their Github profile. In this case, the pull requests aren't opened with the same good faith that you're putting into your work.

"Open source" does not mean "open contribution", i.e. just because the software is open source does not imply that your contribution (or in particular a not-high-effort contribution) is welcome.

A well-known application that is open source in the strictest sense, but not open contribution is SQLite.

Google Guava Java library is very similar -- open source, but almost never accepts outside contributions. Is the golang base library similar?

Not so far. All my contributions where welcomed.

> The rumors we hear have to do with projects inundated with more pull requests that they can review, the pull requests are obviously low quality, and the contributors' motives are selfish.

There's a way to handle this: put an automatic AI review of every PR from new contributors. Fight fire with fire.

(Actually, this was the solution for spam even before LLMs. See "A plan for SPAM" by Paul Graham. Basically, if you have a cheap but accurate filter (specially, a filter you can train for your own patterns), it should be enabled as a first line of defense. Anything the filter doesn't catch and the user had to manually mark as spam should become data to improve the filter)

Moreover, if the review detects LLM-generated content but the user didn't disclose it, maybe there should be consequences

The curl project is proof of this. No rumors

Right, I was going to ask what "rumors"? The whole thing is documented in numerous projects, so much so that typically the inevitable AI guideline discussion is directly the result of a flood of low quality "contributions" that can't be handled by people managing the project.

It's not a rumor, it's a pattern.

How is an AI policy going to help prevent bad faith actors, though?

People who are doing those harmful things with AI aren’t going to stop because of a policy. They are just going to lie and not admit their submissions are AI generated.

At that point, you will still have to review the code and reject it if it is bad quality, just like you had to without an AI policy. The policy doesn’t make it any easier to filter out the bad faith AI submissions.

In fact, if we DO develop an efficient way to weed out the bad faith PRs that lie about using AI, then why do we need the policy at all? Just use that same system to weed out the bad submissions, and just skip the policy completely.

Some of them will lie. Plenty of people do just follow the rules or are acting in good faith though, so at the very least it can help cut it down.

If the policy will make them at least double check AI didn't put its nonsense in, that's already a win

The point of a policy is to make a decision and then communicate that decision, so that you don't end up in a lengthy argument (or make inconsistent decisions) each time a particular situation arises.

You're right that it won't stop anyone doing harmful things with AI - all it does is codify what is and isn't considered acceptable by a project, and make it easier to justify rejections.

If a project wants to continue evaluating submissions on a case-by-base basis (and has the manpower to do it without the support of a policy) then that's entirely their choice, of course.

Policies protect people on the project by making rejection of bad faith actors easier on them (less energy spent, less work needed).

They're also a statement of organizational's support for people who reject slop PRs and help when the AI using author generates a smear blog post against the reviewer like we've seen before.

I see the solution as only engaging with reasonable persons and ignore the rest.

And the problem is filtering them out. That is real work that can be draining and demoralizing as unreasonable persons usually have their sad story why they are the way they are, but you cannot do therapy or coaching for random strangers while trying to get a project going.

So if people contribute good things, engage with them. If they contribute slob (AI generated or not) - you say no to them.

There must be a mechanism to rate the person submitting the PR. Anyone that wants to submit code to a well-known repo would first need to build a demonstrable history of making high-quality contributions to lesser known projects. I'm not very familiar with the open source scene but I'd find it very surprising if such a mechanism was not already in place. Seems like an obvious solution to the problem of vibe coders submitting slop.

Oh it is a obvious solution, but not trivial to implement in a robust way.

> build a demonstrable history of making high-quality contributions to lesser known projects.

> Seems like an obvious solution

I'm not sure how you would rank quality of submissions for grading contributors like this. Just because a project accepted your PR doesnt make it high quality, the best we can hope for is that it was better than no accepting it?

I think we need one of those solution to spam checklists[1], but for AI slop.

[1] https://craphound.com/spamsolutions.txt

> 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.

This is the technique I've picked up and got the most from over the past few months. I don't give it hard, high-level problems and then review a giant set of changes to figure it out. I give it the technical solution I was already going to implement anyway, and then have it generate the code I otherwise would have written.

It cuts back dramatically on the review fatigue because I already know exactly what I'm expecting to see, so my reviews are primarily focused on the deviations from that.

This, and I curate a tree of MD docs per topic to define the expected structure. It is supposed to output code that looks exactly like my code. If not, I manually edit it and perhaps update the docs.

This is how I've found myself to be productive with the tools, or since productivity is hard to measure, at least it's still a fun way to work. I do not need to type everything but I want a very exact outcome nonetheless.

The only issue to beat in mind is that visual inspection is only about 85% accurate at its limit. I was responsible for incoming inspection at a medical device factory and visual inspection was the least reliable test for components that couldn’t be inspected for anything else. We always preferred to use machines (likes big CMM) where possible.

I also use LLM assistance, and I love it because it helps my ADHD brain get stuff done, but I definitely miss stuff that I wouldn’t miss by myself. It’s usually fairly simple mistakes to fix later but I still miss them initially.

I’ve been having luck with LLM reviewers though.

Similar story, albeit not so extreme. I have similar ergonomic issues that crop up from time to time. My programming is not so impacted (spend more time thinking than typing, etc), but things like email, documentation, etc can be brutal (a lot more computer usage vs programming).

My simple solution: I use Whisper to transcribe my text, and feed the output to an LLM for cleanup (custom prompt). It's fantastic. Way better than stuff like Dragon. Now I get frustrated with transcribing using Google's default mechanism on Android - so inaccurate!

But the ability to take notes, dictate emails, etc using Whisper + LLM is invaluable. I likely would refuse to work for a company that won't let me put IP into an LLM.

Similarly, I take a lot of notes on paper, and would have to type them up. Tedious and painful. I switched to reading my notes aloud and use the above system to transcribe. Still painful. I recently realized Gemini will do a great job just reading my notes. So now I simply convert my notes to a photo and send to Gemini.

I categorize all my expenses. I have receipts from grocery stores where I highlight items into categories. You can imagine it's painful to enter that into a financial SW. I'm going to play with getting Gemini to look at the photo of the receipt and categorize and add up the categories for me.

All of these are cool applications on their own, but when you realize they're also improving your health ... clear win.

> I'm going to play with getting Gemini to look at the photo of the receipt and categorize and add up the categories for me.

FWIW, I have a pet project for a family recipe book. I normalize all recipes to a steps/instructions/ingredients JSON object. A webapp lets me snap photos of my old recipes and AI reliably yields perfectly structured objects back. The only thing I've had to fix is odd punctuation. For production, use is low, so `gemini-2.5-flash` works great and the low rate limits are fine. For development the `gemma-3-27b-it` model has MUCH higher limits and still does suprisingly well.

I'd bet you can pull this off and be very happy with the result.

I maintain expense tracking software that I wrote a while ago (before ChatGPT) that sends receipts and some metadata about them into Google Sheets (previously Expensify). A few months ago, I used Claude to add a feature that does exactly what you describe, but using the data types and framework I built for receipt parsing. It works really well.

Honestly, you can probably build what I built entirely with Gemini or Claude, probably with a nice frontend to boot.

> I'd MUCH rather see a holistic embrace and integration of these tools into our ecosystems.

I understand that your use case is different, so AI may help handicapped people. Nothing wrong with that.

The problem is that the term AI encompasses many things, and a lot of AI led to quality decay. There is a reason why Microsoft is now called Microslop. Personally I'd much prefer for AI to go away. It won't go away, of course, but I still would like to see it gone, even if I agree that the use case you described is objectively useful and better for you (and others who are handicapped).

> 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.

That is the same for every technology though. You always have a trade-off. So I don't think the question is incorrect at all - it applies the same just as it is for any other technology, too. I also disagree that utilitarian arguments by their intrinsic nature lead to counter-intuitive results. Which result would be counter-intuitive when you analyse a technology for its pros and cons?

> There is a reason why Microsoft is now called Microslop.

Because young people repeat things they see on social media?

You mean Micro$lop or the classic M$?

I'm in a very similar situation: I have RSI and smarter-autocomplete style AI is a godsend. Unlike you I haven't found more complex AI (agent mode) particularly useful though for what I do (hard realtime C++ and Rust). So I avoid that. Plus it takes away the fun part of coding for me. (The journey matters more than the destination.)

The accessibility angle is really important here. What we need is a way to stop people who make contributions they don't understand and/or can not vouch they are the author for (the license question is very murky still, and no what the US supreme court said doesn't matter here in EU). This is difficult though.

If you sign off the code and put your expertise and reputation behind it, AI becomes just an advanced autocomplete tool and, as such, should not count in “no AI” rules. It’s ok to use it, if that enables you to work.

this sounds reasonable, but in practice people will simply sign off on anything without having thoroughly reviewed it.

I agree with you that there's a huge distinction between code that a person understands as thoroughly as if they wrote it, and vibecoded stuff that no person actually understands. but actually doing something practical with that distinction is a difficult problem to solve.

Unless the code is explicitly signed by AI as auto-commit, you cannot really tell if it was reviewed by human. So it essentially becomes a task of detecting specific AI code smell, which is barely noticeable in code reviewed by an experienced engineer. Very subjective, probably does not make sense at all.

this is equivalent to claiming that automation has no negative side effects at all.

we do often choose automation when possible (especially in computer realms), but there are endless examples in programing and other fields of not-so-surprising-in-retrospect failures due to how automation affects human behavior.

so it's clearly not true. what we're debating is the amount of harm, not if there is any.

> If you sign off the code and put your expertise and reputation behind it, AI becomes just an advanced autocomplete tool and, as such, should not count in “no AI” rules.

No, it's not that simple. AI generated code isn't owned by anyone, it can't be copyrighted, so it cannot be licensed.

This matters for open source projects that care about licensing. It should also matter for proprietary code bases, as anyone can copy and distribute "their" AI generated code for any purpose, including to compete with the "owner".

> No, it's not that simple. AI generated code isn't owned by anyone, it can't be copyrighted, so it cannot be licensed.

There is no way to reliably identify code as AI-generated, unless it is explicitly labelled so. Good code produced by AI is not different from the good code produced by software engineer, so copyright is the last thing I would be worried about. Especially given the fact that reviewing all pull requests is substantial curation work on the side of maintainers: even if submitted code is not copyrightable, the final product is.

At least with LLM providers, they have your prompts and output, and if they wanted to, they could identify what code was AI generated or not.

Maybe they can be subpoenaed, maybe they can sell the data to parties who care like legal teams, maybe they can make it service anyone can plug a GitHub repo into, etc.

Do you really think anyone is ready to spend money on legal to prove that some piece of code is public domain/has no author? That’s an expensive bet with uncertain outcome. And of course you can recover some information only if logs exist, which might not be the case, especially if local inference was used.

Jokes on you - I run LLMs only locally, and besides the most widely deployed code generating tool AFAIR is JetBrain tiny ~200M LLM, builtin into their IDE.

Care to explain? I see that statement in this thread, but I am not sure where this is grounded in fact.

This is very interesting, because there must be a line here that AI is crossing, and the line is not clearly determined yet.

Is linting code crossing the line?

Is re-factoring code with automated tools like bicycle repair man crossing the line ?

Is AI doing a code review and suggesting the code crossing the line ?

Is writing code with a specific prompt and sample code crossing the line?

Is producing a high level spec and let the AI design details and code the whole thing crossing the line ?

So, where exactly is this line ?

The next interesting question is how this could even be enforced. It's going to be hard to prove AI use when using strictly local models. Maybe they could embed some watermark like thing, but I am not sure this can't be circumvented.

Would really like to see some legal opinions on this ( unlikely to happen :)

The best I found is here: https://copyrightlately.com/thaler-is-dead-ai-copyright-ques...

Here's what a Red Hat/IBM IP lawyer said about the chardet situation: https://github.com/chardet/chardet/issues/334#issuecomment-4...

Here's what the US Copyright Office says: https://newsroom.loc.gov/news/copyright-office-releases-part...

Yeah, that's what the link I posted also discusses (but then goes into much detail, but then offers no actual resolution).

I guess we will have to wait for cases to be brought and resolved at the courts. Not a great recipe to be the leader in AI, it must be said.

An updated copyright bill from legislature, or even positive regulatory action from the executive branch would speed things up and give much planning certainty to actors here in the US.

The rest of the world won't be waiting though -- maybe Europe, but Europe sadly doesn't really matter that much anymore :(

> AI generated code isn't owned by anyone, it can't be copyrighted, so it cannot be licensed.

Translation: AI generated code is in the public domain in the US (until and unless something changes).

You can freely incorporate public domain code into any other codebase. You can relicense it as you see fit. Public domain material is not viral the way the GPL is.

Furthermore, if you make changes to public domain code the derivative product is subject to copyright.

Big tech employees better be quick then!

You can "relicense" it as you see fit, but anyone can just copy it and ignore your license and its terms entirely, it's not your property to put a license on.

See also Red Hat IP lawyer's opinion on trying to license the chardet "rewrite": https://github.com/chardet/chardet/issues/334#issuecomment-4...

From a copyright office report [0] linked in that issue section:

> in many circumstances these outputs will be copyrightable in whole or in part—where AI is used as a tool, and where a human has been able to determine the expressive elements they contain. Prompts alone, however, at this stage are unlikely to satisfy those requirements

I'll just note that "unlikely" doesn't mean "not possible".

It's an interesting question but it's perplexing to me that an IP lawyer of all people would be suggesting to remove a license that might or might not apply in practice. Removing it could have legal consequences if it turns out to be copyrightable. Whereas leaving the notice there wouldn't be expected to have any consequences in the event that it turns out not to apply. Particularly the notice for a permissive OSI license.

To begin with the project is MIT licensed which amounts to public domain with extra steps. So it's the same thing at the end of the day regardless of how the law turns out.

On top of that, even if we suppose the LLM output to be public domain as soon as you later make modifications to the file the license in the header would come into force. It's functionally no different than copy-pasting a piece of public domain code and then editing it a bit.

[0] https://www.copyright.gov/ai/Copyright-and-Artificial-Intell...

For projects, it's also a licensing issue. You don't own the copyright on AI generated code, no one does, so it can't be licensed.

This isn't an issue of "nobody can use this" but an "everyone can use this", i.e. projects can use AI generated code just fine and they own the copyright to any modifications they do to it.

Think of it like random noise in an image editor: you do own the random pixels since they're generated by the computer, but you can still use them as part of making your art - you do not lose copyright to your art because you used a random noise filter.

Only if the generated text has no inherited copyright from the source data.

Which it might. And needs to be judged on a case-by-case basis, under current copyright law.

That is only true for trivial projects that require no human creativity. For such simple projects not having copyright for it is not a big deal.

It's great that LLMs helped you but do you recognize that they are trained on thousands, perhaps millions of lifetimes of human work without the consent of the original authors and often quite explicitly against their will and their chosen license?

These people (myself included) made their work available free of charge under some very friendly conditions such as being credited or sharing work built upon theirs under the same license. Now we are being shit on because obscenely rich people think we are no longer relevant and that they can get away with it.

What happens to you if, say 2 years down the line, "AI" or AI has absorbed all your knowledge and can do all of your work instead of you better and faster? Do you imagine you'll keep paying for AI and having it work for you or can you also imagine a future where AI companies decide to cut out the middle-man (you) and take over your customers directly?

Accessibility is an angle that rarely comes up in these debates and it's a strong one

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

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

A few years ago I was in a place where I couldn't type on a computer keyboard for more than a few minutes without significant pain, and I fortunately had shifted into a role where I could oversee a bunch of junior engineers mostly via text chat (phone keyboard didn't hurt my hands as much) and occasional video/voice chat.

I'm much better now after tons of rehab work (no surgery, thankfully), but I don't have the stamina to type as much as I used to. I was always a heavy IDE user and a very fast coder, but I've moved platforms too many times and lost my muscle memory. A year ago I found the AI tools to be basically time-wasters, but now I can be as productive as before without incurring significant pain.

>Personally, I love the "hallucinations" as they help me fine-tune my prompts, base instructions, and reinforce intentionality

This reads almost like satire of an AI power user. Why would you like it when an LLM makes things up? Because you get to write more prompts? Wouldn't it be better if it just didn't do that?

It's like saying "I love getting stuck in traffic because I get to drive longer!"

Sorry but that one sentence really stuck out to me

I appreciate the feedback.

I like it because I have no expectation of perfection-- out of others, myself, and especially not AI. I expect "good enough" and work upwards from there, and with (most) things, I find AI to be better than good enough.

You worked with people before haven't you? Sometimes they make stuff up, or misremember stuff. Sometimes people who do this are brilliant and you end up learning a lot from them.

Yeah, if RSI is an issue why would you want to be forced to type more?

I can’t say what the OP finds specifically useful but as an example if you’re aiming to make sure you’ve accurately and clearly documented / explained your intent, the misunderstandings and tangents AIs can go down are useful in the same way that putting your theoretically perfect UI into the hands of real users is also useful. It helps you want places where you assumed knowledge or understanding that someone else might not have.

Building up style guidelines for AI tools has been an eye opening experience in realizing how many stylistic choices we make that aren’t embedded in the linter, and aren’t documented anywhere else either. The resulting files have actually been a really good resource not just for the AI but for new developers on the project too.

It all depends on what your specific goal is.

Fwiw, I try to make sure we have an accessibility focused talk every year (if possible) at the Carolina Code Conference. Call for Speakers is open right now if you'd be interested in submitting something on your story.

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.

Wish you the best.

Putting aside the specifics for a second, I'm sorry to hear about your injury and glad you've found workarounds. I also think high-quality voice transcription might end up being a big thing for my health (there's no way typing as much as I do, in the positions I do, is good).

Much appreciated. I find is that referencing code in conversation is hard -- e.g. "underscore foo bar" vs `_fooBar`, "this dot Ls" vs `this.els`, etc happens often. Lower-powered models especially struggle with this, and make some frustrating assumptions. Premium models do way better, and at times are shockingly good. They just aren't remotely economically viable for me.

My solution so far is to use my instructions to call out the fact that my comments are transcribed and full of errors. I also focus more on "plan + apply" flows that guide agents to search out and identify code changes before anything is edited to ensure the relevant context (and any tricky references) are clearly established in the chat context.

It's kinda like learning vim (or emacs, if you prefer). First it was all about learning shortcuts and best practices to make efficient use of the tool. Then it was about creating a good .vimrc file to further reduce the overhead of coding sessions. Then it was about distributing that .vimrc across machines (and I did a LOT of ssh-based work) for consistency. Once that was done, it became unimaginable to code any other way.

It has been even more true here: agent-based workflows are useless without significant investment in creating and maintaining good project documentation, agent instructions, and finding ways to replicate that across repos (more microservice hell! :D) for consistency. There is also some conflict, especially in corporate environments, with where this information needs to live to be properly maintained.

Best of luck!

maybe you've done this already, but my first thought would be to make a preparser script that would take your likely voice inputs like "underscore foo bar" and translate to "_fooBar" which you would then pass on as input. i do something similar for a local TTS generator which often stumbles on certain words or weird characters

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

> without a battle of ego.

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.

Please don't anthropomorphize LLMs even further by assigning them gendered pronouns. LLMs are always "it"s. They're not alive, they're just really complicated linear algebra expressions. Prematurely anthropomorphizing them, even subtly like this, will come back to bite us if we keep doing it.

Can you defend that though? Does living mean needing cells? Does it mean possessing the ability to think and reason? Is Claude thinking and reasoning?

I just think that if I treat my AI GF like that she'll just pout and end up giving me the silent treatment and I'll have to reboot her.

Why not? Claude is a male name, and the model behaves close enough to a human that I think it's fine to refer to it as a he or a she. Also note that some languages don't have neutral pronouns and it's perfectly fine to say a mosquito is a "he", and a spider a "she" for instance. Are they more humans than a LLM?

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 think you have a good point

for some reason that hasn't happned to me yet. im only in my 50ies, but I have been on a split keyboard for a long time...

I think a good routine matters a lot. I played a lot of video games in my youth and got carpal tunnel from there, and haven't been able to recover 100% since.

Yeah good point. I work really hard at taking breaks and moving around. where you using a controler/joystick a lot? I was mostly a keyboard warrior.

I was playing rhythm games on a keyboard, so basically button mashing. The real killer was that I was pushing myself beyond what I was actually able to play. There's a certain technique to button-based rhythm games, and once you aren't able to read what is happening on the screen any more you tend to naturally transition to just brute force button mashing with high force, which tends to be very straining. I believe this was the problem for me.

If I had been a bit more intelligent at how I was learning, and focused on improving reading skill instead of simply wanting to play whatever music I liked, I would have probably never had problems. Rhythm games in general boil down to training your brain to read moving patterns and convert them to scheduled movements in your body (but mostly your hands). Once you get to an intermediate level you get these "flow states" where you realize you were basically unconscious for most of the song, not a single thought, just internally observing your body's reactions to the screen. Almost a type of meditation.

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.

Glad to see this response, I was wondering the other day how the affected accessibility. I remember reading a thread a few years back of visually challenged developers and their work flow and was kinda surprised there has been such little discussion around developer accessibility with the advent of ai agents and coding routines.

This is a bit of a straw man. The harms of AI in OSS are not from people needing accessibility tooling.

It's absolutely not a straw man, because OP and people like OP will be affected by any policy which limits or bans LLMs. Whether or not the policy writer intended it. So he deserves a voice.

He doesn't think others deserve a voice, so why should I consider his?

The fact that you are engaging in this thread shows me you have considered my opinions, even if you reject them. I think thats great, even in the face of being told I advocate for the collapse of civilization and that I want others to shut up and not be heard.

It is a bit insulting, but I get that these issues are important and people feel like the stakes are sky-high: job loss, misallocation of resources, enshitification, increased social stratification, abrogation of personal responsibility, runaway corporate irresponsibility, amplification of bad actors, and just maybe that `p(doom)` is way higher than AI-optimists are willing to consider. Especially as AI makes advances into warfare, justice, and surveillance.

Even if you think AI is great, it's easy to acknowledge that all it may take is zealotry and the rot within politics to turn it into a disaster. You're absolutely right to identify that there are some eerie similarities to the "gun's don't kill people, people kill people" line of thinking.

There IS a lot to grapple with. However, I disagree with these conclusions (so far) and especially that AI is a unique danger to humanity. I also disagree that AI in any form is our salvation and going to elevate humanity to unfathomable heights (or anything close to that).

But, to bring it back to this specific topic, I think OSS projects stand to benefit (increasingly so as improvements continue) from AI and should avoid taking hardline stances against it.

Sure. I don't necessarily think your opinion is radical. But it's also important to consider biases within oneself, especially when making use of text as a medium where the nuance of body language is lost.

The main thing that put me off on the comment was the outright dismissal of other opinions. That's rarely a recipe for a productive conversation.

>However, I disagree with these conclusions (so far) and especially that AI is a unique danger to humanity. I

I don't think it's unique. It's simply a catalyst. In good times with a system that looks out for its people, AI could do great things and accelerate productivity. It could even create jobs. None of that is out of reach, in theory.

But part of understanding the negative sentiment is understanding that we aren't in that high trust society with systems working for the citizen. So any bouts of productivity will only be used to accelerate that distrust. Looking at the marketing of AI these past few years confirms this. So why would anyone trust it this time?

Rampant layoffs, vague hand waves of "UBI will help" despite no structures in place for that, more than a dozen high profile kerfuffles that can only be described as a grift that made millions anyway, and persistent lobbying to try and make it illegal to regulate AI. These aren't the actions of people who have the best interests of the public masses in mind. It's modern day robber barons.

>I think OSS projects stand to benefit (increasingly so as improvements continue) from AI and should avoid taking hardline stances against it.

I don't have a hard line stance on how organizations handle AI. But from my end I hear that Ai has mostly lead to being a stressor on contributors trying to weed out the flood of low quality submissions. Ai or not (again, Ai is a catalyst. Not the root cause), that's a problem for what's ultimately a volunteer position that requires highly specialized skills.

If the choice comes between banning Ai submissions, restricting submissions altogether with a different system, or burning out talent trying to review all this slop: I don't think most orgs will choose the latter.

I disagree. I've done nothing to argue that the harm isn't real, downplayed it, nor misrepresented it.

I do agree that at large, the theoretical upsides of accessibility are almost certainly completely overshadowed by obvious downsides of AI. At least, for now anyway. Accessibility is a single instance of the general argument that "of course there are major upsides to using AI", and there a good chance the future only gets brighter.

My point, essentially, is that I think this is (yet another) area in life where you can't solve the problem by saying "don't do it", and enforcing it is cost-prohibitive. Saying "no AI!" isn't going to stop PR spam. It's not going to stop slop code. What is it going to stop (see edit)? "Bad" people won't care, and "good" people (who use/depend-on AI) will contribute less.

Thus I think we need to focus on developing robust systems around integrating AI. Certainly I'd love to see people adopt responsible disclosure policies as a starting point.

[edit] -- To answer some of my own question, there are obvious legal concerns that frequently come up. I have my opinions, but as in many legal matters, especially around IP, the water is murky and opinions are strongly held at both extremes and all to often having to fight a legal battle at all* is immediately a loss regardless of outcome.

> I've done nothing to argue that the harm isn't real, downplayed it, nor misrepresented it.

You're literally saying that the upsides of hallucinanigenic gifts are worth the downside of collapsing society. I'd say that that is downplaying and misrepreting the issue. You even go so far to say

>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.

These aren't balanced arguments taking both sides into considerations. It's a decision that your mindset is the only right one and anyone else is a opposing progress.

> are worth the downside of collapsing society.

At least in the US, society has been well on it's way to collapse before the LLM came out. "Fake news" is a great example of this.

>It's a decision that your mindset is the only right one and anyone else is a opposing progress.

So pretty much every religious group that's ever existed for any amount of time. Fundamentalism is totally unproblematic, right?

Sure. I always said Ai was a catalyst. It could have made society build up faster and accelerate progress, definitely.

But as modern society is, it is simply accelerating the low trust factors of it and collapsing jobs (even if it can't do them yet), because that's what was already happening. But hey, assets also accelerated up. For now.

>So pretty much every religious group that's ever existed for any amount of time. Fundamentalism is totally unproblematic, right?

Religion is a very interesting factor. I have many thoughts on it, but for now I'll just say that a good 95% of religious devouts utterly fail at following what their relevant scriptures say to do. We can extrapolate the meaning of that in so many ways from there.

> At least in the US, society has been well on it's way to collapse before the LLM came out. "Fake news" is a great example of this.

IMO you can blame this on ML and the ability to microtarget[1] constituencies with propaganda that's been optimized, workshopped, focus grouped, etc to death.

Proto-AI got us there, LLMs are an accelerator in the same direction.

[1] https://en.wikipedia.org/wiki/Microtargeting

welp, flip another one from the "they definitely could do this and might be" pile to the "they've already been doing this for a long time" pile

>You're literally saying that the upsides of hallucinanigenic gifts are worth the downside of collapsing society.

No, literally, he didn't.

Yes, I literally quoted it.

You quoted him and then put words into his mouth based on your own strongly held beliefs. Words he neither said nor implied.

>I love the "hallucinations"

Sorry, the rest of your comment could have the recipe for fat free deep fried blowjobs that cure cancer and I wouldn't read past that.

Fantastic point. I do think there was a bit of an over correction toward AI hostility because capitalism, and for good reason, but it did almost make it taboo to talk about legitimate use cases that are not related to bad AI use cases like instigating nuclear wars in war game simulations.

I think the ugly unspoken truth whether Mozilla or Debian or someone else, is that there are going to be plausible and valuable use cases and that AI as a paradigm is going to be a hard problem the same way that presiding over, say, a justice system is a hard problem (stay with me). What I mean is it can have a legitimate purpose but be prone to abuse and it's a matter of building in institutional safeguards and winning people's trust while never fully being able to eliminate risk.

It's easy for someone to roll their eyes at the idea that there's utility but accessibility is perfect and clear-eyed use case, that makes it harder to simply default to hedonic skepticism against any and all AI applications. I actually think it could have huge implications for leveling the playing field in the browser wars for my particular pet issue.

I think generating slop and having others review it is bad even if you are disabled. I say this as a disabled person myself.

The premise LLM are "AI" is false, but are good at problems like context search, and isomorphic plagiarism.

Given the liabilities of relying on public and chat users markdown data to sell to other users without compensation raises a number of issues:

1. Copyright: LLM generated content can't be assigned copyright (USA), and thus may contaminate licensing agreements. It is likely public-domain, but also may conflict with GPL/LGPL when stolen IP bleeds through weak obfuscation. The risk has zero precedent cases so far (the Disney case slightly differs), but is likely a legal liability waiting to surface eventually.

2. Workmanship: All software is terrible, but some of it is useful. People that don't care about black-box obfuscated generated content, are also a maintenance and security liability. Seriously, folks should just retire if they can't be arsed to improve readable source tree structure.

3. Repeatability: As the models started consuming other LLM content, the behavioral vectors often also change the content output. Humans know when they don't know something, but an LLM will inject utter random nonsense every time. More importantly, the energy cost to get that error rate lower balloons exponentially.

4. Psychology: People do not think critically when something seems right 80% of the time. The LLM accuracy depends mostly on stealing content, but it stops working when there is nothing left to commit theft of service on. The web is now >53% slop and growing. Only the human user chat data is worth stealing now.

5. Manipulation: The frequency of bad bots AstroTurf forums with poisoned discourse is biasing the delusional. Some react emotionally instead of engaging the community in good faith, or shill hard for their cult of choice.

6. Sustainability: FOSS like all ecosystems is vulnerable to peer review exhaustion like the recent xz CVE fiasco. The LLM hidden hostile agent problem is currently impossible to solve, and thus cannot be trusted in hostile environments.

7. Ethics: Every LLM ruined town economic simulations, nuked humanity 94% of the time in every war game, and encouraged the delusional to kill IRL

While I am all for assistive technologies like better voice recognition, TTS, and individuals computer-user interfaces. Most will draw a line at slop code, and branch to a less chaotic source tree to work on.

I think it is hilarious some LLM proponents immediately assume everyone also has no clue how these models are implemented. =3

"A Day in the Life of an Ensh*ttificator "

https://www.youtube.com/watch?v=T4Upf_B9RLQ

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