Skip to content
HN On Hacker News ↗

Why I Think You Should Almost Never Use AI to Write Anything Substantive

▲ 363 points • 177 comments • by erwald • 3w ago • HN discussion ↗

Pangram verdict · v3.3

We believe this text is mainly human-written, with some AI content.

3 %

AI likelihood · overall

Human
97% human-written 3% AI-generated
SEGMENTS · HUMAN 1 of 2
SEGMENTS · AI 1 of 2
WORD COUNT 1,023
PEAK AI % 92% · §2
Analyzed
Sep 19
backend: pangram/v3.3
Segments scanned
2 windows
avg 512 words each
Distribution
97 / 3%
human / AI fraction
Verdict
Human
Pangram v3.3

Article text · 1,023 words · 2 segments analyzed

Human AI-generated
§1 Human · 1%

I think you should almost never use AI to write -- that is, to do the thing you’re doing when you type words on a page -- whether for a blog post, a research report, a memo, a thoughtful email, a novel, or any other text aimed at conveying an idea, an argument, an analysis, or other substantive1 thoughts. I think this is the case even when you give the AI very detailed bullet points, dictated thoughts, or other context, and even when you edit the AI-written text.2I think so because (1) the writing process is an essential part of the thinking process, (2) AI writing is vague and wrong in hard-to-notice ways, and (3) writing with AI (and not labeling it as such) is rude and misleading. I’ll explain these points in more detail below, but first, a few throat clearings.As you may know, I’m not anti-AI. I think it makes a lot of sense to use AI for many other parts of the research and writing processes, such as transcribing audio, analyzing data, searching for information, brainstorming, and giving feedback on drafts. I also think using AI for line and copy editing, or for rewriting a passage to make it clearer or tighter, is fine, as long as all the edits are deliberately accepted or rejected by a human. It’s just using AI to write text that I’m against.3And yes, there are various advantages to using AI for writing. For example, it’s less effortful and much faster than writing yourself. So the disadvantages of using AI for writing need to be substantial for it to be bad overall. As you may have guessed by now, I think they are.And finally, I’m just making a claim about the AI models that exist now and that I expect to exist in the near future. There will likely exist models at some point that are good enough that it makes sense to delegate the writing to them (although at that point it might make more sense to delegate the entire research or writing process end-to-end, since in addition to the writing they will also need to be doing all or most of the thinking).The point of doing any kind of research is to form accurate beliefs about important questions, which you can then communicate to an audience. One of the best ways of doing that is in my opinion by writing.Paul Graham has written4 thatWriting about something, even something you know well, usually shows you that you didn’t know it as well as you thought. Putting ideas into words is a severe test. [...] Half the ideas that end up in an essay will be ones you thought of while you were writing it. Indeed, that’s why I write them.On an episode of Patrick McKenzie’s podcast, Clara Collier says thatWhen I am writing something, something substantive, there’s no part of that writing process in which I am not thinking and changing my mind. Everything from the outline to turning it into text to just the sentence. Often I’ll have an experience where I’m trying to turn an outline into a finished product, and I’m playing with a transition, and it’s not working, and I realize, oh, the reason this transition isn’t working is because actually these two points should not be juxtaposed. The thing that I’m trying to do here is wrong. And if I feed the outline into an LLM, it is not going to stop and consider maybe the outline is bad. [...]Patrick replies:I absolutely agree that the writing process is the thinking process, and I think we now have empirical demonstration of this, because you make a machine that does writing and thinking just pops out as a side effect.But when writing a multi-page piece, even if you have a strong thesis, the act of forcing yourself to write that down into sentences and paragraphs to structure the argument will show you where the holes are in the argument. It will show you where your research process has been inadequate. It will surface things like: oh, actually, there is something that is contradictory to the thing that I want to say. And, being a reasonably ethical person, I think I will acknowledge that there are counterarguments, or have to add that the full claimable conclusion is less than the one that I would, quote-unquote, “like to write”.I basically agree with these takes. When I write something, I must first know what I want to say, i.e., I must think about evidence and arguments and arrive at some beliefs. So writing forces me to do those things, which are necessary for any writing or research project. For any such project, someone has to have the entire thing in their head -- all the bits of evidence, considerations, arguments, and how these fit together. Writing with AI makes it easier to avoid the necessary thinking.When I write something, I make a lot of small decisions about specific wording and phrasing. Together, these small decisions contribute to the overall clarity and correctness of the text.For example, if I ask Claude Fable 5 to “write a short paragraph introducing the problem of AI chip smuggling”, a topic that’s been written about and reported on extensively, it outputs:Since October 2022, the United States has restricted exports of advanced AI chips to China, aiming to slow Chinese progress at the frontier of AI. But export controls are only as strong as their enforcement, and AI chips are compact, extraordinarily valuable, and sold through sprawling global supply chains — properties that make them attractive and feasible to smuggle.

§2 AI · 92%

Diversion networks route controlled GPUs through intermediaries in places like Singapore, Malaysia, and the UAE, using shell companies and falsified paperwork to move them into China. Estimates of the scale vary widely, from tens of thousands to perhaps more than a hundred thousand high-end chips per year, and even the lower end represents enough compute to matter for training and deploying capable AI systems. Meanwhile, the Bureau of Industry and Security, tasked with policing a multi-hundred-billion-dollar trade, operates with a budget and headcount better suited to a far smaller problem.