As an occasional writer, I'm more sensitive to LLM-generated articles; I'm also more bothered by them than the average reader. At this point, I see this kind of content daily on HN and in my social media feed.
At the same time, I think there's a lot of witch-hunting going on. It's important to realize is that LLM writing doesn't differ from human writing *per se*. Rather, it's that if you go to chatgpt.com and ask it to write an essay, you always get the same writer persona by default. That persona has distinctive quirks, just like any author would.
The quirks include basic formatting (e.g., a preference for book-style capitalization of section headings), a range of stylistic cliches (vague appeals to significance, negative parallelisms, explicit summary sections), and so on. Contrary to some nerd lore, these statistical patterns can be detected with automated tools; if originality.ai flags something as LLM output, it's a signal you shouldn't just ignore.
That said, there are two problems with relying on these indicators. First, there's a small but non-zero percentage of people who write the same way. Second, if you're clever, you can prompt an LLM to use a different voice. Tell it to write as a grizzled sailor - a man of few words who's still grieving the loss of his wife and only child - and it's going to generate something quite distinct.
Because of this, I find it useful to lean on three additional, higher-level heuristics:
1) Does the text exhibit any non-stereotypical writing traits, and do they appear consistently in this person's writing? Almost everyone has some. Preference for overly long sentences, overuse or complete avoidance of semicolons, unusual metaphors or idioms, etc. If you don't see any of that, it should give you a pause.
2) Is there a discernible reason why this text exists in the first place, and why this person is writing it? Long-form writing takes time and effort, so we only do it when we think it's important or useful. If there's no discernible personal perspective in the writing, that's a red flag.
3) My favorite: if you prompt an LLM to write an article on this topic for this particular publication, is it going to produce something functionally similar?
This brings me to my final point: as an author, I have some misgivings about the tech, but I recognize it can be used for good. My beef isn't with people using it; it's with people who use it to crank out slop. If your article fails these three tests, then something went wrong even if you didn't use any automated tools.