Why You Should Almost Never Use AI to Write Anything Substantive
I argue that using AI to write substantive texts—blog posts, reports, memos, novels—is almost always a bad idea, even with detailed outlines and editing. The writing process is the thinking process; delegating it skips essential reasoning. AI output is also vague and subtly wrong in ways that are hard to catch, as a Claude-generated paragraph on AI chip smuggling illustrates. Finally, passing off AI writing as your own is rude and misleading. I'm not anti-AI: transcription, data analysis, brainstorming, and feedback are fine.
When I am writing something, something substantive, there’s no part of that writing process in which I am not thinking and changing my mind.
- patrickmay
From TFA: "Eric Schwitzgebel writes that . . . There’s a huge cognitive difference between nodding along while reading something and actually productively generating a text. Two reasons: First, once the text is on the page, it’s easy to passively let the approximate word suffice, rather than thinking about word choice in the same effortful, active way we do when generating prose de novo. Second, as I suggested above, I doubt that human beings, even experts, have a good sense of all the factors that shape word choice -- everything they’re being sensitive to. You would have phrased it slightly differently, and even if you don’t know that, or why, a different signal is sent and received."
This is the best articulation I've seen of why simply reviewing and copy-editing does not provide remotely the same value as writing from scratch. I spent a considerable amount of time over the past two weeks reviewing and improving a work document that was the output of an LLM. Given the number of people involved and the final level of effort, I'm firmly convinced that writing it manually would have been faster and resulted in a higher quality product. Getting the wording right matters.
- grogers
Is editing really any less 'thinking' than writing the original copy? I don't use LLMs to generate prose but I can compare to writing code. Let's say I use an LLM to write code to some specification. After it meets the spec I go over everything with a fine-toothed comb - tweaking things to a style I like better, rewriting pieces or interfaces that I think would be better a different way, etc. Is the final work product any different than if I wrote it from scratch without absolutely any LLM use? Personally I would say no, if I do enough editing to be perfectly satisfied with it then it's the exact same output in the end.
- jameshart
Use AI to write things for you to read that you wish someone else had written. ‘Give me a summary of the research on this topic’; ‘Write a report on this data to help me make a decision’. ‘Take this transcript of a meeting and write me the email it could have been’.
Don’t use AI to write things that you are producing for someone else to consume.
- foobarbecue
It blows my mind that anyone would ever use an LLM to write, if communication is their goal.
LLM writing takes your prompt and adds stuff you didn't write, burying your meaning and making it harder for the reader to get your message.
Way more effective to just publish the prompt.
Of course, it's great if you're just trying to fill space or satisfy demands of a bullshit job.
- rectang
Instead of asking AI to write something substansive for you, ask it to critique your writing. Then use your own judgement as to which bits of advice to follow and which to ignore.
The LLM will always give you a full rewrite — don't use it. It always does too much, and persuading it to tone it down is a constant battle.
- alas44
"AI writing is vague and wrong in hard-to-notice ways"
This one felt to me, at work I lost a lot of time re-reading and correcting AI prose that was launched to "summarize" a collective white paper, and where subtlety and nuance disappeared in ways that harmed the initial ideas/arguments I was writing about, but in sneaky ways.
- vanschelven
I can't help but think that some of the arguments here apply equally well to writing _code_ as they to to other substantive writings.
Writing code is thinking, AI code is often vague and wrong in hard-to-notice ways, and the (human) reader of code is the one that pays the cost for this later.
The cost/benefit analysis may still work out differently for code though...
- dalemhurley
When I was a graduate 20 years ago, the partner would sit with a print out of every word I wrote and a red pen marking every change required, as the partner knew anything that was written in his name had to be exactly what he would have said.
Same needs to go for LLMs, leverage them for productivity both make sure you are owning their output.