What gives AI prose away: the word choice, the argument's shape, or what it leaves off the page?

This explores which features of the writing itself mark text as AI-generated, from word choice up to story structure and what's absent from the page. The short answer from the corpus is that the clearest signals sit at several layers at once. The surface layer is the most measurable and the least noticeable. The deeper layers are harder to fake, and some of them are about what AI text leaves out rather than what it puts in.

Start at the level of individual words. LLM text differs from human text in statistically robust ways across six dimensions of vocabulary: how many distinct words it uses, how often they repeat, how evenly they're spread, and how far apart in meaning they range Can human judges detect measurable differences in AI text?. The odd part is that trained linguists and NLP researchers still can't tell the difference by reading. Newer models make this worse: ChatGPT-4.5 and o4-mini drift *further* from human vocabulary patterns while becoming *harder* for people to spot Why do newer AI models diverge further from human writing patterns? Can humans detect AI text if machines can measure it?. The likely reason is that training rewards text people rate as good, not text that resembles how people actually write. Cheap, transparent measures can still catch it. Simple linguistic features plus argument-quality markers detect LLM-written Reddit counter-arguments with 99% accuracy, picking up tells like closely mirroring the prompt and polished "textbook" argument structure that real commenters rarely produce Can simple linguistic features detect AI-written arguments?.

One layer up is rhetoric. AI prose has mastered grammar and organization but avoids taking an evaluative stance. It leans on neutral nouns that describe *how* something is done, where human writers reach for nouns that signal status, evidence, and judgment. The result is coherent but argumentatively inert: well organized, committed to nothing Why does AI writing sound generic despite being grammatically correct?. This matches what experts mean by "slop", which breaks down into low information density, questionable quality, and repetitive, templated style What dimensions make text feel like AI slop?. There is a twist here, though. When AI *assists* a human writer, readers perceive the writer as *more* confident, extreme, and agreeable on all 29 traits measured Does AI writing assistance change how readers perceive the writer?. Writers edit those AI paragraphs only 23% of the time, and lightly when they do Do writers actually edit AI-generated text before publishing?. So mixed human-AI text has its own fingerprint, and it isn't the same as the neutral voice of purely AI text.

The deepest and most durable layer is structure. In fiction, AI stories can be told apart from human ones with 93% accuracy using *only* narrative choices: how much agency characters have, and whether events are told in time order. That method keeps 97% of its accuracy even after every stylistic cue is removed Can AI stories be detected without analyzing writing style?. This matters because "humanizer" tools edit surface style, and structure can only be changed by rewriting. A more theoretical line of work argues that some differences are absences rather than features. AI text lacks the writer's implicit appeal to the reader's attention, which may explain the "aloofness" readers report in AI social posts Does AI writing lack the internal appeal to attention that humans use?. It also lacks embodied authorship and a real speaker in a real context. That is why fake AI hotel reviews are detectable at over 80%: they describe experiences no one had Does AI-generated text lose core properties of human writing?.

The takeaway you might not have expected is that the features that separate AI from human writing mostly aren't the ones readers can see. We read the finished text with the same interpretive habits we use for any text, and those habits can't inspect where it came from or whether anyone stands behind it How can AI text disrupt structure yet feel normal to readers?. Machines catch AI text through word statistics and story structure. Humans miss it because what's missing is a person behind the words, and that absence doesn't show on the page.