AI writing carries measurable traces in its word choice that human judges can't reliably notice, but machines can measure them.

This explores what actually sets AI-written prose apart from human writing, and which differences survive scrutiny. The corpus points to a layered answer. The differences run from word choice up to how a text treats its reader, and the deeper the layer, the harder it is to disguise. There's also a catch running through all of it: machines can measure these differences much more reliably than people can notice them.

Start with vocabulary. Across six measures of lexical diversity (how many distinct words appear, how evenly they're spread, how varied they are), LLM text differs from human text in statistically clear ways Can human judges detect measurable differences in AI text?. Newer models drift further from human patterns, not closer, while getting harder to spot Can humans detect AI text if machines can measure it?. One layer up is rhetoric. LLMs have mastered grammar and organization but tend to avoid taking an evaluative stance. They reach for neutral, descriptive nouns where human writers use words that signal judgment, certainty, or evidence. The result is prose that is coherent but argues for nothing Why does AI writing sound generic despite being grammatically correct?. In argumentative writing, models leave tells: they mirror the prompt closely and reach for textbook argument markers. Simple, transparent features catch LLM counter-arguments on r/ChangeMyView with 99% accuracy Can simple linguistic features detect AI-written arguments?. Experts asked to define 'slop' land on related ground: repetition and templated phrasing, plus low information density What dimensions make text feel like AI slop?.

The most durable signals sit above style altogether. In fiction, AI stories can be told apart with 93% accuracy using only narrative choices, such as how much agency characters have and how the timeline is ordered. Performance barely drops when every stylistic cue is removed. These choices resist 'humanizing' tools because changing them means rewriting the story, not polishing sentences Can AI stories be detected without analyzing writing style?. Some researchers go further and argue that what's missing is not a feature but a relationship. Human writing comes from a body, a situation, and an ongoing exchange with a reader. AI text structurally lacks these, which is why fake AI hotel reviews give themselves away: they claim experiences no one had Does AI-generated text lose core properties of human writing?. A related argument holds that human posts quietly ask for the reader's attention. AI posts don't perform that appeal, and readers pick this up as a kind of aloofness Does AI writing lack the internal appeal to attention that humans use?.

Here's the twist. None of this means people can spot AI text. A review of 30 studies finds human detection hovers around chance across text, images, and voice Can people reliably spot content made by AI?, and even trained linguists fail Can humans detect AI text if machines can measure it?. Readers don't seem to mind, either. Machine-generated Reddit comments carry a recognizable assistant-style warmth, yet they draw as much engagement as human ones, sometimes more Does machine-generated text get penalized in online engagement?.

That matters because the features don't stay in pure AI text. Writers using AI assistance edited the suggested paragraphs only 23% of the time, and lightly when they did Do writers actually edit AI-generated text before publishing?. Readers then perceived those writers as more confident, more extreme, more agreeable, and more privileged, shifting across all 29 traits measured Does AI writing assistance change how readers perceive the writer?. So the real question may be less 'how do I spot a machine?' and more 'how is the machine's voice quietly reshaping how people sound to one another?'