Looking at LLM usage and promotion as a cultural phenomenon, it has all of the markings of a status game. The material gains from the LLM (which are usually quite marginal) really aren’t why people are doing it: they’re doing it because in many spaces, using ChatGPT and being very optimistic about AI being the “future” raises their social status. It’s important not only to be using it, but to be seen using it and be seen supporting it and telling people who don’t use it that they’re stupid luddites who’ll inevitably be left behind by technology.
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.
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.
AI has the Jeopardy Phenomenon too.
If you use it to generate code that is outside your expertise, you are likely to think it’s all well and good, especially if it seems to work at first pop. But if you’re intimately familiar with the technology or the code around the code it’s generating, there is a good chance you’ll be like hey! that’s not quite right!
Not just code. I’m astounded by the cognitive dissonance displayed by people who say “I asked an LLM about {topic I’m familiar with}, and here’s all the things it got wrong” who then proceed to say “It was really useful when I asked an LLM for advice on {topic I’m not familiar with, hence why I’m asking an LLM for advice}.”
Like, if you know that the results are super dodgy for your own area of expertise, why would you think they’d be any better for, I don’t know, restaurant recommendations in a city you’ve never been to?
Wake me up when we get to the plateau of productivity.
Language matters.
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.