Exactly. If it's substantially the writer's own thoughts and/or words, who cares if they collaborated with an LLM, or autocomplete, or a spelling/grammar-checker, or a friend, or a coworker, or someone from Fiverr? This is just looking for arbitrary reasons to be upset.
If it's not substantially their own writing or ideas, then sure, they shouldn't pass it off as such and claim individual authorship. That's a different issue entirely. However, if someone just wanted to share, "I'm 50 prompts deep exploring this niche topic with GPT-5 and learned something interesting; quoted below is a response with sources that I've fact-checked against" or "I posted on /r/AskHistorians and received this fascinating response from /u/jerryseinfeld", I could respect that.
In any case, if someone is posting low-quality content, blame the author, not the tools they happened to use. OOP may as well say they only want to read blog posts written with vim and emacs users should stay off the internet.
I just don't see the point in gatekeeping. If someone has something valuable to share, they should feel free to use whatever resources they have available to maximize the value provided. If using AI makes the difference between a rambling draft riddled with grammatical and factual errors, and a more readable and information-dense post at half the length with fewer inaccuracies, use AI.
In my experience if the ai voice was immediately noticeable the writing provided nothing new and most of the time is actively wrong or trying to make itself seem important and sell me on something the owner has a stake in.
Not sure if this is true for other people but it's basically always a sign of something I end up wishing I hadn't wasted my time reading.
It isn't inherently bad by any means but it turns out it's a useful quality metric in my personal experience.
That was essentially my takeaway. The problem isn't when AI was used. It's when readers can accurately deduce that AI was used. When someone uses AI skillfully, you'll never know unless they tell you.
i feel like i've seen this comparison made before, but LLMs, when used, are best applied like autotune. 99% of vocal recordings released on major (and even indie) labels have some degree of autotune applied. when done correctly, you can't tell (unless you're a grizzled engineer who can hear 1dB of compression or slight EQ changes). it's only when it's cranked up or used lazily that it can detract from the overall product.