There’s a time for linguistics, and there’s a time for grabbing the general public by the shoulders and shouting “It lies! The computer lies to you! Don’t trust anything it says!”
Generated code is rather a lot like fast fashion: it looks all right at first glance but it doesn’t hold up over time, and when you look closer it’s full of holes. Just like fast fashion, it’s often ripped off other people’s designs. And it’s a scourge on the environment.
This is depressing.
The hard part of computer programming isn’t expressing what we want the machine to do in code. The hard part is turning human thinking – with all its wooliness and ambiguity and contradictions – into computational thinking that is logically precise and unambiguous, and that can then be expressed formally in the syntax of a programming language.
That was the hard part when programmers were punching holes in cards. It was the hard part when they were typing COBOL code. It was the hard part when they were bringing Visual Basic GUIs to life (presumably to track the killer’s IP address). And it’s the hard part when they’re prompting language models to predict plausible-looking Python.
The hard part has always been – and likely will continue to be for many years to come – knowing exactly what to ask for.
I love the small web, the clean web. I hate tech bloat.
And LLMs are the ultimate bloat.
So much truth in one story:
They built a machine to gentrify the English language.
They have built a machine that weaponizes mediocrity and sells it as perfection.
They are strip-mining your confidence to sell you back a synthetic version of it.
I suppose it’s not clear to me what a ‘good’ window into unreliable, systemically toxic systems accomplishes, or how it changes anything that matters for the better, or what that idea even means at all. I don’t understand how “ethical AI” isn’t just “clean coal” or “natural gas.” The power of normalization as four generations are raised breathing low doses of aerosolized neurotoxins; the alternative was called “unleaded”, but the poison was called “regular gas”.
There’s a real technology here, somewhere. Stochastic pattern recognition seems like a powerful tool for solving some problems. But solving a problem starts at the problem, not working backwards from the tools.
Wake me up when we get to the plateau of productivity.
Large language models are big messy brushes, not scalpels.
A large language model is as neutral as an AK-47.
Whether you’re generating slop or code, underneath it’s the same shoggoth with a smiley face.
The best of the web is under continuous attack from the technology that powers your generative “AI” tools.