Why are coders so desperate to replace themselves with ai? Like you rarely hear of actual artists or writers using ai in such large waves as coders do. Sure you'll get lots of people who have an idea for a story just have an llm do the work for them, but its less common to hear about established authors doing that. Just like how people who have an idea for a game will just have an llm write the code. Meanwhile professional coders seem thrilled to outsource their work to ai. Why???

Edit: is it bc they don't see their work as art like artists and writers do? Bc it is a form of art just like how mathematical formulas and stuff can be art

(Obligatory not all coders. I know there are many that hate ai and hate being required to use it at work, but its really starting to feel like they're in the minority)

Wasn't prepared for Graphene to break my heart this morning. That's what I get for having a feeling I guess.

Copied from discussion on c/Technology:

OSS projects have already started to recognize that LLM is just a tool and how you use that tool matters a lot more than whether you are using said tool at all.

This tool is however not neutral but has a lot of steering and bias built in. Like an advisor who optimizes heavily for personal gain. For example, it constantly tells you that it knows it all and also that your ideas are the best thing since sliced bread. A lot of stuff around them is engineered to increase engagement and make you dependent on them. Precisely like social media which is full of "brain hacks" - no, this isn't hyperbole, this is the name that engineers at Facebook gave to their creations. As social media, commercial LLMs are "addictive by design".

Lets bring StackOverflow for analogy: we didn't ban browsers for code development because one can navigate to StackOverflow and copy-paste some really crappy code.

Stack Overflow is a really good example. I am programming over 40 years, since 35 years as hired programmer, since 25 years on PhD level and I used Stack Overflow a lot to find interesting new angles on issues with seemingly obvious answers. Like "what is the most portable, clearest way to efficiently serialize message data in a C struct, given that type punning is only defined for some compilers and can lead to undefined behaviour".

Stack overflow has typically various opinionated commented answers here, which gives you different angles and you can decide what is best in your case. This is crucial since a lot - one could say, almost all - of software engineering is about trade-offs.

ChatGPT is the know-all of stack overflow responders: It gives you a single smart-allecky answer and is purposefully built so it tries to take decisions out of your hands. It currently also makes a ton of suggestions of which some have a point, some might apply in other cases but not yours, and some are bullshit. If you let it run free you will easily get ten times more code than needed. And ten times more code means ten times more bugs - this is well-established.

So grabbing LLM to get a sense of direction or shape is an OK use in general, but copy-pasting it's results blindly is silly and dangerous.

The thing is that commercial LLMs in practice are engineered to short-circuit your judgment and decision-making.

There's a second argument that AI is ruining OSS communities which I believe is true, but refusing to accept AI code is a self-defeating action. Why? Because AI training needs unadulterated source of knowledge, one not tainted with AI and OSS communities rejecting AI would be that source.

First: These companies will siphon off open source code anyway, be it legal or not. That is outside of the influence of single open source developers or projects. Maybe a matter of high courts and civil society lawsuits to decide. And these will have to fight an uphill battle against the current political climate around favouring large companies in general and that kind of exploitative AI in particular.

But what projects do have influence over is the quality of their code base and what ingresses into it.

Further, it is to expected that the quality of commercial code bases continues to degrade at a rapid pace and also that companies will depend even more on open source infrastructure and libraries - and FOSS developers training the LLMs they use on anything that is new. Because the average commercial project or github project just will turn to shit. Companies will soon wistfully remember old times where Sturgeon's law was a thing and when only 90% of all public code was shit, and not 99.999% . (Congratulations to that future five nines!).

There is an asymmetry between open source code and proprietary software: Open source code is protected by copyright law. Which GenAI vendor companies practically do ignore. Proprietary software is usually protected by copyright law, and also obfuscation by it being binary or behind server APIs. Currently, this works in favour of companies: They get to use GPL-proteced public code, but are not exposing their own, uh, creations. (And of course, LLM vendors will make the solemn pinky promise that they never ever will publish commercial code their customers are working on as LLM output (ask top-notch mathematicians how that worked out).)

But will this stay like this? Because another issue is that the same methods can be used to decompile binary code, and LLMs can also be trained on decompiled proprietary code. Which will, for example, make its many hidden security issues much more acute. (Another thing is I think one can transform decompiled control structures in binary code to control flow graphs, and then use standard graph search algorithms and graph databases in order to find out which GPL'd open-source code some proprietary product has included, including which potentially vulnerable versions. So-to-speak a software-bill-of-materials by code inspection.)

It's unclear what would be accomplished by banning AI for a tiny portion of the code while continuing to use Linux, AOSP, Chromium and hundreds of other projects heavily using it.

AI or not, this is such shit attitude. Call it peer pressure, or appeal to authority, or whatever, but think for yourself. Especially for a project like GrapheneOS.

It's GrapheneOS. They always sail their own path regardless of flak.

I think the anger is justified as there is a precedent for LLMs being used badly and how unethically the training data is collected (open source has been hurt deeply by scraping attacks for years). How quickly people can be driven off the deep end and form deranged relationships with chatbot style LLM assistants. The fear and anger are very valid, if they couldn't foresee a hostile reaction to a beloved project starting to utilize the same tech that has caused harm in huge ways...Well, that's called not reading the room, hun. I wasn't going to fly off the handle about it. But I am deeply disappointed about it. I don't really trust the usage of LLMs in any project as by design these are things constructed to channel skill into the hands of those with wealth, while denying those with skill access to wealth. It is mighty hard to trust anyone to use these things that are built on outright manipulation, theft, and a multitude of harms.

I have been dropping projects left and right for it, it insures that I will never touch GrapheneOS. Begrudgingly, I am still using Linux (despite the LLM usage on the Kernel). There is no real safety hatch to escape into yet. Unless, I just want to retreat into the woods and never interact with modern society ever again. Which I am mighty tempted to do, despite it meaning a gradual and uncomfortable death.

how can it be secure if there's code that nobody wrote?

I already had my doubts in the capabilities of the GrapheneOS leadership and these doubts where renewed after the recent kerfuffle about hardware memory tagging on the Pixel 11. With these new revelations it might be time to start to look out for an alternative. Maybe its for the better. They never where able to handle criticism gracefully no matter how carefully formulated.

Very unsurprising.