The Debian project is engaging in a debate and vote on whether large language model (LLM) tools may be used in the development of Debian, its distribution-specific code, and the project’s website. The general resolution is currently being discussed leading into a vote on the subject.
“just one more dpkg bro I swear we are going to get pulseaudio and systemd working this time bro just one more data lane, you have to do this or you are going to fall behind bro trust me”
I’m all for Argument 1. Also, it’s been scientifically proven that any sort of extended use to AU lowers your intelligence, and that would be the last thing we need for a distro that needs to remain a bastion of Stable.
@lambalicious @valar
Scientifically proven? Any sort of AI usage? Just genereal intelligence?
There are definitely some initial studies out already that point in that direction, but I think your wording is a bit overly broad and definitive. It will be a while until we understand all the factors involved and what is going on there exactly.
One of the most dangerous things about modern LLMs is that they rarely mess up in obvious ways.
They are incredibly good at making very subtle mistakes that look correct to non-experts.
That, combined with how drastically they lower the barrier of entry to creating functional software, creates the ultimate Dunning-Kruger scenario.
The amount of effort it takes to properly vet LLM-produced code is an order of magnitude more than the effort it takes to produce, which makes maintainers’ work basically untenable. The “solution” proposed by AI shills is for the maintainers to do the same thing, but obviously that suffers from the exact same problem.
It’s better to be broadly right than precisely wrong, and LLMs are fantastic at the latter.
I think we’re in the middle of another wave similar to the “code bootcamp” era. The market is getting flooded with a bunch of people who want to make software engineer salaries without having to put in the effort to learn proper software engineering skills or computer science theory.
We’re constantly hearing a more extreme version of the coding bootcamp propaganda, “Why go into debt $60k-$100k and spend four years of your life getting a Comp Sci degree, when you could spend just $15k-$25k and 6-12 months getting our cert to land the same jobs?” Now it’s, “Why spend all the time and effort learning how to write & understand code, when you could just prompt an LLM to build all your software for you?”
But in the end, people will learn that there actually is value in having a deep, technical understanding of the theory and practices of software engineering. They’ll learn that you can’t just vibecode the next AWS, Linux kernel, SAP, hypervisor platform, or firewall appliance. They’ll learn that it’s not enough to just tell a swarm of agents to maintain your code base forever.
But it’s going to be a very painful lesson for a lot of people, and when the AI bubble finally pops, it’s going to be a truly Biblical reckoning for the entire tech industry.
I’m not bothered that much: the results are observable empirically with how idiocracy people in general have become in the last 2 years (not that we as a species were a beacon of understanding before that).
That said, in terms of “just general intelligence?” I’d say it’s two intelligences that are hit the most: emotional intelligence and logical intelligence. Not necessarily in that order.