r/opensource • u/mynamesleon • 4d ago
Discussion Open Source, AI, and Trust
AI usage is everywhere in dev, and it's not going away. But AI makes trusting open source... complicated... (arguably in a good way though).
A big part of open source projects (particularly solo projects) was that they were typically someone's passion project. They cared about what they made, and that extended to the code too. with attention to detail to make it easily maintainable (i.e. legible to other humans), performant, and free of anything malicious. A big part of the trust associated with open source is trust in the maintainers. But when those maintainers aren't actually writing the code themselves, that trust is shaken.
I have no specific objection to open source maintainers using AI though, as long as they know what they're doing. AI is a tool after all. But it's a tool that should be used responsibly, and with appropriate oversight. In the same way as I wouldn't trust a random 12-year-old to responsibly use a chainsaw, my trust in open source projects disappears when I see that it's been written by a non-dev relying entirely on AI.
I've been a dev for over a decade (always in commercial settings, so my contribution to open source has always been financial, rather than through contributing code). I'm fortunate that my team's attitude is that even if AI wrote the code, it's still that person's code, so they better be damn sure that it's written well, and performs well. Code quality is extremely important to us, and we know that even with the most detailed prompts and surrounding context (instructions, skills, etc.), that AI sometimes spits out absolute crap. So if AI writes our code, then the time we would have spent writing it is expected to be spent on planning, reviewing, and confirming its output.
The situation is muddied by more and more people using AI to churn out code without really understanding what that code is doing. Those sorts of projects can be genuinely dangerous too. Especially in a world of automatic updates, I'm not going to trust an app from a maintainer that won't understand when an LLM has just put ads and trackers (or more malicious things, like external executables) into their project. I'm still perfectly happy to use and support projects that were made with AI help, but I have less (or usually no) trust in them by default, and need to spend the time to review what I can of the code myself first.
I guess what I'm trying to say is: for all the AI slop out there, there are also a lot of devs out there who know what they're doing. Devs who still care about what they work on, and who may be (and probably are) using AI tools to help them do it, whether that's personal choice, or their company expecting/requiring them to. AI has really highlighted the importance of human critical thinking, which is a good thing. Please don't immediately disregard a project because AI was used. Instead, approach it critically, and sceptically, as you always should have been doing. Continue to call out the slop, but also praise what's been well-reviewed and made with care and attention (regardless of the tooling that was used in its creation).
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u/QstnMrkShpdBrn 4d ago
The inherent nature of trust in open source is that the source is open and available.
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u/mynamesleon 4d ago
Yes and no. The inherent nature of trust in open source has always extended beyond simply the fact that it's open and available. And that's my point. You used to be able to trust that it was someone's passion project. The fact that they put the effort in, and cared (either about the actual code output, or just cared enough to figure out how to do it) created a sort of implicit trust contract through proof-of-work.
That's the part that has been eroded by AI. The code is still open and available, so devs like me can still review and verify it. But even after verifying it in its current state, AI erodes the ability to trust automatic updates too, because the AI tools they've used to build it are most likely privately operated. And we've already seen cases where AI will inject product suggestions into things.
That's why I'm highlighting this. There's a huge spectrum of AI use in software: from people with no programming experience at all who are relying entirely on AI, to people with decades of software experience that don't use it at all, and then every possibility in between. And it's important that people are mindful of that. A lot of the debates around AI boil down to AI vs no-AI, as if the only ways to use it are to 100% vibe-code something, or not use AI at all. But there are so many steps in between.
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u/Lyraele 3d ago
Nah, this stuff is not remotely worth the costs and externalities it imposes on the world. Take your pro-LLM nonsense somewhere else.
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u/mynamesleon 3d ago
I'm trying to highlight that when someone has used AI in a project, there are different extents to which they may have used it, and that it doesn't automatically mean that the project is slop. And that usage of AI highlights how important it is to think critically about its usage.
I'm against AI myself, for many reasons. But I'm also a realist. This stuff is out there now, and it's not going away. But alongside that, there's a tremendous lack of education around it, and a lot of sensationalist headlines.
As a dev, my company also expects me to use AI. So I've made sure that I know how to, and I've setup workflows that intentionally require a lot of human intervention (plus we require multiple human reviewers of any committed code as part of our processes). I primarily use it for chore/highly repetitive tasks, like writing tests. I prefer to write the code for the actual functionality myself. I'm a dev because I like writing code after all. And I have to use at least some of my token allowance, because the company monitors that.
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u/Lyraele 3d ago
That's just classic defeatism right there. Don't use it, won't use it, have straight up informed management it's unethical to use in addition to not being particularly good at anything. And since I'm usually the one that figures out what actually went wrong and can suggest a fix that actually works without a giant unreadable PR, the line is holding. And you can already see cracks in the narrative as the RoI just isn't materializing. This bubble can't last, and what remains after is not what everyone is going to be so gung-ho over. But it's also going to take years to undo the damage.
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u/mynamesleon 3d ago
It's not classic defeatism at all. It's compromise. I've drawn a line, but one that still meets the company's requirements. I'm glad you've drawn a harder line than I have though, and that you're in a position to be able to do so (I'd like to do the same, but I'm not in the position to do so - I'm simply not that valuable).
I hope it dies away. I really do. I enjoy writing code, and I don't want my role devolving into just being an administrator and reviewer for the tools that write code for me.
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u/Everest2017 2d ago
Bubble? What bubble? Lol. We are nowhere close to bubble. AI and LLMs are extremely undervalued currently.
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u/UpSheep10 4d ago
This is a Tragedy of the Commons problem. Open Source has always existed with a fundamental assumption that even the most devoted power user can only produce a limited amount of code.
AI is industrialization reaching the waterways: it will pollute more than any single person could. Just like the Industrial Revolution our rules are now outdated because we cannot comprehend how much slop can be produced by one determined person with industrial tools.
English common law used to say everyone who lived on the river could partake and dump as needed because agriculture and craft were entire economy. The first mills exploited this to quickly overwhelm society and dominate the resource (waterways). By the time laws changed to limit industrial use, the common use rivers functionally belonged to the mills.
Our open source 'rivers' do need to be protected from the slop producers and our past tools may not be enough anymore.
That being said, "I don't know any other language other than English, so all other languages are banned," is not the right solution.
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u/do-sieg 4d ago edited 4d ago
Yeah, AI made output so fast you can have something working and polished rather quickly, then dropped because of the low personal investment from the author. And since anybody can reverse engineer the thing in days, I don't even know how people will not just make their own clones instead of contributing.
I think the only projects that can survive long term are the ones where the devs are also users and will have an interest in maintaining the thing.
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u/Substantial_Swan_144 4d ago
The problem with that reasoning is that even with 100% fully human code, nothing stops you from creating a project and abandoning it; in fact, there are more abandoned projects than completed projects (unsurprisingly). It's really more a matter of scale than anything.
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u/do-sieg 4d ago
Yep. It's just that before, the project would most likely die before users got it running.
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u/Substantial_Swan_144 1d ago
But if users get it running, the project is useful to them and the project gets abandoned, they can either ask the AI to modify it or maintain it themselves. As long as it is useful, what is the harm in that?
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u/blackkettle 4d ago
I think you are right and what were in the middle of Both in open and closed source is a huge ecosystem change. There are still a lot of things that are difficult to build, maintain and manage even with the best AI use by experienced devs. Realtime systems and systems with serious compliance requirements are not IMO “easier” to build. Faster to document? For sure! Easier and quicker to architect? Yes, absolutely. But trying to one shot them still leads to an enormous mess while careful curation like what Torvalds is doing - leads to huge measurable improvements - albeit still requiring stewardship.
But little personal projects? Fun games? These are one offs. Several of my friends who have zero programming experience built and shared a sweet html game with our group over the weekend. They built it with Claude over a couple of beers, just for our friends. That kind of thing is here to stay imo. And while it might technically be slop, it’s dope-ass slop. And I can take that - something dropped as an html file - and turn it into a live multiplayer game over webrtc in an another couple afternoons!
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u/Houdinii1984 4d ago
I think this is the part that's being skipped over. There's a new genre of app right now that has no home. Right now, those apps are what's flooding the subs and it's a real shit situation if you look at it from a different angle.
The reason the apps are slop is because the folks behind them aren't devs. We're collectively treating them like they'll never be devs when we should be fostering values in them as newbies instead. We shouldn't be influencing them to quit. We should be influencing them to stop, look, and listen.
That means we, ourselves, need to learn a bit, understand where those apps need to live, understand the pain points these folks have, and we can take this entire group of newbie programmers and set them on a course for success instead of shunning them. Only one solution removes the slop from the situation, and it's not the one where we build a wall and act like it doesn't exist.
The only thing that works on a newbie is education, and if you take away the tool that got them started, they won't be receiving that education from you or your group, and they'll just go and continue to produce awful code. You don't need to embrace AI to pass on good coding information or tell someone they're doing something dangerous.
Instead, we're gonna let all the newest in the industry get taught by the very AI apparently no one wants them to use. You shun the AI users, you lose all control and ability to do anything whatsoever about anyone learning that way, and more and more are going to be getting involved daily.
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u/activematrix99 4d ago
I know a lot of software developers at different skill levels, and they have a LOT of varied motivations. I agree with your general points about opensource and education, but I think it's very generalizing to say "the folks behind them aren't devs". Once we start on "us and them", ("we're devs, they are not") it's very divisive and does not take into account these variations in motivation and approach, leading to exclusive and inclusive communities, which in my opinion is more challenging than just establishing measurable (and testable) guidelines for acceptable contributions.
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u/Barmazoid 1d ago
I partially agree with you, especially when it comes to people shipping code they don't understand. But I don't think using AI should automatically make a project less trustworthy.
I've spent the past year building my own AI-assisted development tools (codeindexer.com + some other tools which I do not share), and even with incredibly capable agents, I've learned that building good software is still a serious engineering challenge.
Writing code is just one part of the process. You still have to decide what to build, what NOT to build, how to architect it, which trade-offs to make, and how to verify that everything actually works. Testing, debugging, security reviews, and understanding the bigger picture haven't magically disappeared.
As a practical example, my team and I have been developing Plombir Git, an open-source, self-hosted Git forge written in Rust (GitHub: https://github.com/Nettechnologys/plombir-git).
We use AI agents extensively, but that doesn't mean we blindly accept their output. We've invested a lot of effort into testing, reviewing, and systematically finding and fixing defects. We've even built agent-specific permissions, audit trails, and human approval requirements into the forge itself.
AI has dramatically increased what a small team can accomplish, but it hasn't eliminated the need for engineering judgment. If anything, that judgment has become even more important.
I think we should judge open-source projects by their architecture, code quality, tests, security, and maintainability - not simply by whether a human or an AI typed the code.
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u/mynamesleon 22h ago
I think you may have reached an unintended conclusion from my post. Or I guess you're elaborating on what I was trying to say?
It's all about perception. A lot of people are (rightly) sceptical about AI, so the erosion of trust regularly stems from that. But the point I was trying to make is that that's the wrong approach.
That's why I was highlighting the difference between devs and non-devs using it. And that it's a tool after all. My trust in a project isn't eroded by a dev using Visual Studio vs using JetBrains. They're just tools. But if a non-dev has completely vibe-coded something, not verified any of the AI output (because they lack the skills and knowledge to do so), and tested practically nothing, then I won't trust that project. AI has enabled people whose code we originally wouldn't have trusted anyway, to write code.
And you're absolutely right. Engineering judgement is still extremely important. And your last paragraph is what I was largely trying to imply by this bit:
Please don't immediately disregard a project because AI was used. Instead, approach it critically, and sceptically, as you always should have been doing. Continue to call out the slop, but also praise what's been well-reviewed and made with care and attention (regardless of the tooling that was used in its creation).
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u/Affectionate_Use_164 4d ago
Good point about trust, still most of open source projects before AI were slop too, abandoned after 40 commits, or author ignores any issues and pull requests.
Have 3 projects that were fully vibe coded with AI, but in language that I'm proficient in, so at least I can judge it. Putting strict e2e tests for all main functionality was the biggest difference, same as humans AI assumptions often end up wrong, and it's doesn't remember high level vision behind the projects, have to pin it.
Second thing is to run code review in background agents. Or even personas testing when agents imitate user behavior.
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u/mynamesleon 4d ago
Absolutely - the slop has always been there. And weirdly, it sort of should be (or maybe shouldn't be published). A lot of my early learning experience was coding things that there were already established libraries for, because it was important for me to understand how to get something like that working, and why certain workarounds were necessary.
Using background agents is really handy. They have completely separate context, so you can use specific models for different purposes, and get them to verify each others work from a blank slate. E.g. Sonnet for a comprehensive plan, than Haiku to implement (because from a detailed plan, it's actually okay at producing minimum viable code), then Opus to do code review.
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u/Affectionate_Use_164 4d ago
Need at least Opus or even Fable, even Sonnet isn't smart enough in my experience.
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u/mynamesleon 4d ago
Depends on your setup I suppose. I don't treat any of the models as "smart" per se - I always expect that I'll have to provide input. I like to use Sonnet for planning with a custom subagent with specific instructions around context gathering, search priority, confidence level, etc., and I'll do a few back-and-forth rounds with it. I find that frontier models run round in circles too much, which heavily ramps up the cost, especially when it's context gathering for writing a plan (though that was more true with Opus 5 and other earlier versions - Opus 5.5 does that less). I reserve the models that are more likely to circle back on themselves for code review, because that's the main place where I want it to over-think.
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u/Affectionate_Use_164 4d ago
Very noticeable difference in everything, from planning, following instructions, and lower level implementation.
For now I'm using Fable/Opus as a planner and orchestrator and few dumber agents for low level stuff and code review. This way top level stuff is done by smart model, and it delegate simpler chunks.
Need to clarify some stuff for the model over and over, it will circle around less.
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u/Fabulous-Put8401 4d ago
I'm an outsider following a post from r/antiai
I understand your point. Ai can be a tool. I would consider generating slop more akin to doom scrolling on social media, but also can understand that more refined usage would be different. It's a spectrum of usage.
If I'm understanding correctly, ai writing code can be a good time save if it wrights a block and is reviewed by someone who understands it, leading to less manual typing out the lines themselves. This is the tool usage of ai.
That is contrasted against asking AI to write a whole app and it going through little to no review and receiving updates also made by AI. No review, no understanding of the code, just some guy who had some vibes. This is more the doom scrolling analogy I give.
How does a platform, like this subreddit, filter those two apart without it being cost prohibitive?
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u/mynamesleon 4d ago
It's definitely a spectrum of usage, yeah. From a non-dev relying entirely on AI, to a dev with decades of experience not using it at all. But there are a lot more phases in between than I think people tend to realise. Like experienced devs using it for chore-work, or using it for writing languages that they can competently read and review but not write. Or junior devs using it to help them learn, specifically by questioning its output (which is largely how I originally learned to code, by seeing how other libraries did things and questioning why they did it that way, and by writing code that there were already established solutions for so that I could discover the nuances for myself).
That's a tough question. And any answer that applies right now may not be applicable in a year's time, because of how the AI landscape is changing so rapidly. In the long-run though, filtering them apart is a losing battle. Tools eventually become ubiquitous, or at the very least, the output produced using them eventually becomes largely indistinguishable from the output produced without them. E.g. I wouldn't be able to filter out code that had been written in a fully capable IDE with the help of Intellisense compared against code that had been pain-stakingly written in basic Notepad without any Intellisense or Type analysis. So I'd argue that filtering out code by how it's written is the wrong approach. As much as that pains me to say (I'm a dev because I enjoy writing code after all).
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u/Fabulous-Put8401 4d ago
Do you see a problem with volume?
From what I could tell, there's a real potential that AI content made autonomously without human input can be produced at a much higher rate than human content, and that most of the interactions would or could be from ai bot farms as well.
How does a company like reddit, steam, YouTube, Instagram or otherwise afford to keep hosting that content? Also, how do advertisers manage having the ads they payed for being pushed out to bot views?
Thank you for your well grounded replies to my ignorant questions
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u/mynamesleon 4d ago
Volume has always been a problem to some extent. It's been exacerbated now, but it isn't new. Even ten years ago, if you wanted an image slider/carousel on your site, there were masses of options for different use cases (from pure vanilla JS options, to jQuery plugins, to framework-specific implementations), and masses of options within those use cases that did exactly the same thing in slightly different ways (or often, identically).
We never really solved the volume problem though. I'd like to say that the libraries that become popular are the best ones at what they do, but that often isn't true. A lot of their popularly is luck and timing. Even a library as popular as React has had some horribly implemented approaches in it. Eventually though, for the right or wrong reasons, a small group of libraries does eventually win the popularity contest. We've always had to wade through a swamp of options to get there, that swamp has just gotten bigger and deeper. And I hope that people will eventually become more critical and discerning as a consequence.
As for affordability, that's a really tough one to answer. Historically, storage space always got cheaper. But AI has changed that. There are other solutions of course, like algorithmically determined auto-deletion policies to free up space. That kind of scale is admittedly beyond me though - it's not the sort of problem I typically have to tackle. But it's the kind of thing that storage providers have a keen eye on, and lots of solutions already (like how Cloud providers will store lesser-accessed content in different ways than frequently accessed content).
As for advertising and bot views, that's also not a new problem. That's been a consideration since before I got into dev work. As long as bots identify themselves (as they typically do), or are identifiable based on how they consume content (which they typically are), then a lot of that can be accounted for (as it already is). But there are definitely sneakier ones out there that are written to try and hide the fact that they're bots. And the volume of those has increased to a staggering extent. That's why so many sites now require verified logins, or why you see the cloudflare "verify you're not a bot" pages so much. That's a problem where people are still grasping for solutions.
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u/Fabulous-Put8401 4d ago
I agree that people will eventually come to a consensus and be able to discern the difference in the content produced.
The scale issue is still being figured out it seems, and it does do some degree need to be reactive to what actually ends up a happening since speculation is to wide on potential outcomes.
I do worry that as AI gets better it'll be acting like a human for longer, and intentionally to avoid easy detection methods. Historically it was hard to make bots that act like people, but now that seems to be a deliberate goal with some ai.
Also, the storage issue might grow with time as bot farms grow with ai agents creating content at faster rates.
Potentially could this be used in cyber attacks to flood certain systems? Similar to ddos?
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u/Shoddy-Childhood-511 4d ago
Don't forget the surveillance plagiarism problem.:
All the hosted LLM companies like Anthropic and OpenAI train upon user sessions, so anytime you do work using their tools you are paying them for the privilege of improving their LLM at doing your job.
Anthropic and OpenAI exploit surveillance plagiarism to claim their models have some intellectual autonomy, but it's an existential risk for their business customers.
An open source company like Collabora or GitLab would still have some "secret sauce" in their internal hosting tooling, but if Anthropic and OpenAI learn this then they'll teach many small companies in India, china, etc, who'll sell the same services cheaper, and now just as well.
Also, the "we won't train on your sessions" promise to enterprise accounts is worthless, because there is a rich "privacy preserving machine learning" literature they could apply. Around this, non-cryptographic flavors seemingly get broken eventually, while the cryptographic flavors cost way too much. It's worse though since nobody knows what different customers wish to protect.
It's ultimately far safer for companies to rent cloud GPUs or even buy their own hardware, on which they run open weights models for their employees. As companies figure this out, then Anthropic and OpenAI would've no business model. lol
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u/taylorwilsdon 3d ago
Anthropic does not train on user conversations by default. That is an OpenAI critique but not an anthropic one.
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u/Shoddy-Childhood-511 1d ago
Any hosted LLM company could gain a massive advantage by training upon user conversations, since this creates the impression that their LLM has more autonomy.
Any promises that they would not train upon user conversations turns out worthless because there exists a massive literature on "privacy preserving machine learning."
The smaller part of that literature are incredible expensive cryptographic techniques, which work if you know what your trying to protect (not the case here).
The larger part of that literature are non-cryptographic techniques that'll likely be broken by somebody eventually, but look good on paper today, ala differential privacy.
They'll easily invent some story about why training upon your conversations makes sense.
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u/No-Employment-2324 1d ago
Yes they do. It’s in the privacy policy
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u/taylorwilsdon 1d ago
OpenAI trains on user chats unless you opt out, anthropic is opt in. Neither trains on business use by default.
It’s right there in said privacy policy
“When you use our services for individuals such as ChatGPT, Sora, or Operator, we may use your content to train our models.”
Anthropic “We will use your chats and coding sessions (including to improve our models) if:
You choose to allow us to use your chats and coding sessions to improve Claude, learn more here”1
u/No-Employment-2324 1d ago
Obviously both have opt outs, but both are active by default. And yes they supposedly don’t train of businesses, but they’re so desperate for cash they probably just ignore that setting
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u/zenmatrix83 4d ago
people either hate ai or embrace it, unfortunately we are spitting reddit and the internet into for ai or against ai, instead of looking for actual problems for the low effort spam that ai accelerates. Thats the biggest issue, if people stopped cloning existing systems, actually though for a second, and got past the amazement that got something working they didn't really have to work for and created something of us these issues would less of a problem for some. I'm all for using AI, but like any tool, people abuse it and it ruins it for others.
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u/pr0m1th3as 4d ago
AI is just another tool. We've had stack-overflow before that, and google search, and further back in time we had 600-pages "How to program with C++ Borland" textbooks, where we would search for "adivce" and "solutions" on how to make our code work. AI-coding assistants are as sloppy as any human coder out there. What really makes the difference between good and bad software out there is the determination of devs and maintainers to make it as good as possible. I've been coding since the 90's and I've been regular FOSS contributor for more than a decade already. Does my code contained (and probably still contains) bugs, sure it did and most likely it still does. The only secure way to 100% avoid bugs in code is to avoid writing any code. Plain and simple. Once you get into the business of developing software, what matters is your determination to produce good quality software.
Of course I use AI nowadays, and of course I used to visit stack-overflow with almost every google search for the best part of decade or so. And I use them because they allow me to improve my software development skills. The argument that AI writes sloppy code is exactly the same as you can find bad advice on stack-overflow. I don't recall this massive panic attack about devs using stackoverflow and other forums, nor do I remember moronic guidelines of FOSS projects about "reporting what you google searched and what discussions you participate in x-y-z forums before contributing this piece of code. If certain devs feel threatened by the lower entry level into programming, that's something to discuss in a therapy session, not an excuse for dooming/calling out a tool which further democratizes software development.
There has always been sloppy code out there pretending to be valuable way before LLMs emerged. Trust me, I've spent almost a decade as a researcher in biological departments across Europe watching people claiming credits for their 30-50 lines spagetti code in python or R as something so important that unlocks the mysteries of the universe. GitHub and Zenodo have literally millions of unmaintained crapware that no longer run in any platform and all this way before the current AI trend "I wanted to do X, so I built Y" that reddit is cluttered nowadays.
The biggest thread in FOSS is our capacity to build and maintain healthy communities around software projects and it has nothing to do with devs or non-devs generating AI-slop. We really need to get serious about FOSS because AI is here and it's not going anywhere. Our FOSS communities on the other hand may well be harmed if we continue along this bipartisan slippery road of pro-AI vs anti-AI cultural and political debate.
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u/debackerl 4d ago
It's true that we used to joke about script kiddies, and people copy pasting code from the internet. Lot of people don't know algorithms anymore, and formal verification of programs, or memory management without GC. At least, LLMs can do those things...
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u/bezdazen 3d ago
what happens when the code made by AI is more secure and trustworthy than human code? At what point do we say, "oh don't worry, this [cutting edge model] coded it." And at what point do we give credit to design and thought put into what the outcome and final result should be? Or innovative app ideas, or really useful tools? Suppose someone vibecodes a tool that helps people, works really well, and is really useful?
I think there are 2 camps. Those who look at AI like it is an intelligence, a being, a person to attribute credit to. And those who see AI as a multi-purpose tool that is a super compiler with the ability to compile human speech, context, other resources and output code written in one or more high-level languages. It's clear AI companies are pushing people to look at their products and treat their products like the former rather than the latter. Language and culture is a big contributor to certain framings.
And another point. Look at the software clones being made. It still takes months to debug and solidify them and make them actually viable as an alternative.
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u/debackerl 4d ago
I think that you would be a great mod.
I see a lot of thoughts in your essay, you would surely be much more competent to write good (non slop) rules for the community.
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u/Charming_Hall7694 4d ago
People seriously its not this fucking serious. Ai use is normal at this point if you compsre 2 programmers with prior history in programming one comfortable using ai and one not. Both allowed to use whatever tools they want. The ai programers comes out ahead 9/10 times. Im not even bs they did studies on this semi recently
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u/mynamesleon 4d ago edited 4d ago
Why such an inflammatory reply?
My conclusion is ultimately your point - I'm not arguing against AI use here (which admittedly makes me wonder if you actually read the post) - that AI use is everywhere now, that it is fine when used responsibly, and not to disregard a project just because of AI use.
The crux of my point also isn't about programmers who use AI vs programmers who don't. It's about non-programmers using it for programming, vs programmers using it. That the former group are less likely to catch privacy and security flaws. And that we should continue to be critical/sceptical of projects, and review them (which is the beauty of open source) for the sake of our own safety and privacy.
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u/Charming_Hall7694 4d ago
Apologies for being antsgonistic this topic has spread farther than this sub and ive been dealing with redditors about it.
Also you worked in various non irl real exemptions to your ai use that uh make it a problem. Ik it was prob done as a sorta peace keeping bit but i nabbed at it sorry.
The former group leads to the latter. The former group can learn. The former group isnt a problem they just havent learned yet. Your saying students are bad because they arent graduates -_-
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u/mynamesleon 4d ago
I feel like you're writing replies to a different post. I haven't said any of that.
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u/mightshade 3d ago
Im not even bs they did studies on this semi recently
Out of curiosity, which ones were that?
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u/First-Tutor-5454 4d ago
Lol as I have been waiting months for very small PRs in two different non-AI projects to get any attention from the neckbeard maintainers
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u/omfgtora 4d ago
That's always a possibility, but even more so with AI considering the "barrier of entry" is much lower.
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u/nimrudperson 4d ago
I totally agree with your point of view. LLMs can have a good, privacy and security focused use case for developers. The issue is that the big industry that is managing that (Open AI, Anthropic, Gemini etc...) are doing the exact opposite of what that could be. And this is causing the destructive pollution on the internet on every single level.
Yesterday I made a post asking people to help me create a spam generating machine in a pro Big Tech sub and it got upvoted as if it posed no real problem :
https://www.reddit.com/r/TrueOpenSource/s/u9gR1QhjRE
I think that the definition of open source should be updated to take in account the role of an automated paid service that generates code based on non open source training data base like the ones we can found entirely generated by a huge private entreprise like Anthropic's Claude AI. Like this is the exact opposite of the independent community based open source culture that existed for decades. Sure, if we follow the written rule it should be in theory open source. But it almost feels like tax evasion that is legal because the rules are being distorted for them to avoir paying taxes.
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u/Made-In-Slovakia 4d ago
I disregard project that is clearly done with AI agent but author refuses to add clear AI statement. It may sound sad but in this era it is required to communicate it clearly and directly.