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The growing divide between AI hype and software engineering reality
It is widely accepted that there is an AI bubble in the financial markets at the moment. The moderate opinion is however that LLMs are constantly improving and will eventually take over more and more tasks from humans and increase productivity. But are LLMs actually getting smarter, or just better at fooling us?
There is a growing faction of technical experts that argue that LLMs are actually so bad for real progress, that they are banning their use and requiring human-only work to ensure quality and efficient use of humans’ time. A recent review of AI policies of 120 open source projects by Rakshit Yadav shows that 37 chose to have a total AI ban. In the Linux kernel AI-assisted contributions are allowed, but the LLM used needs to be attributed for transparency, while projects like GCC, QEMU, SDL, Gentoo, Zig and Ghostty have adopted policies to reject all AI-assisted contributions. There are also development platforms such as Codeberg and Sourcehut and app stores like Flathub that have banned AI use to generate software, documentation, bug reports, review comments and basically anything that is intended for humans to read. The projects that allow AI use typically still require that there must be a human-in-the-loop and the submitter must have read and filtered everything the LLM spits out before another human is exposed to it, in an effort to contain the spread of AI slop.
Right now, the Linux distribution Debian is having a vote among its developers on whether AI should be allowed or banned for use to contribute to Debian. One of the proposals on the ballot is a total ban of AI for code, documentation, translations, bug reports and more. The initial reaction from most people is astonishment — why don’t these techies want to use the latest and greatest technology mankind has produced so far? Is it that they don’t want Debian to improve faster with the help of AI? Or is it actually so that LLMs are a scam and incapable of being truly useful for Debian? These people are distinguished experts in their own field, and certainly not stupid, so it is worth pausing to understand why they are proposing AI banning policies.
Also, keep in mind that the AI datacenters themselves run on Debian or other Linux-based systems. All the open source software in the world has been fed to LLMs and software development is one of the main use cases for AI currently. So why is it that the maintainers of many open source projects don’t want to receive LLM-assisted contributions, despite the LLMs basically all running on top of those same software stacks and having been trained on how to do software development using the very same open source software codebases?
The output of an LLM often looks very compelling, professional and correct. Humans have evolved to trust or distrust new information based on easy to detect secondary factors like what authority the speaker holds, or how confidently and eloquently the message is conveyed. Humans are however very bad at fact-checking and cross-referencing new information, as it requires a lot of effort, and humans like saving energy and being as lazy as possible.
The less you know about something, the easier it is to fool you on that topic. Nobel prizes in economics have been given in for research on how information asymmetry distorts markets and leads to suboptimal outcomes. In the field of software engineering we have now witnessed a flood of aspiring software developers using AI to create software that looks like it might work, but that is actually full of flaws. These people are well-intended, but they simply lack the expertise to understand what they are actually doing, and don’t possess the necessary judgement to decide when an LLM spits out something truly useful and when it is creating mostly garbage. This asymmetry in expertise I think explains the majority of the conflict currently witnessed in open source projects — the senior developers are flooded with requests to review code that is bad and a