Does My Writing Sound Like AI? A Self-Check

You wrote it. Every sentence, over four evenings, with the sources open on the desk beside you. Then a checker returns a number, or a supervisor says the phrasing feels generated, and you read your own paragraph back three times and cannot tell any more.

"Does my writing sound like AI?" is a fair question with a specific answer, and for most people asking it the answer is that the writing sounds organised. Competent, taught, edited academic prose shares a great deal of surface with machine output, because a language model was trained on competent, taught, edited prose. What follows is a self-check: what to look at in a draft you wrote yourself, what it means when you find it, and how much of it to leave exactly where it is.

Why Human Writing Sets Off the Same Signals

We have a language model that's learned on the writing that people say is good, published papers, edited journalism, textbooks, documentation. It spits out the average of that, which is pretty much what you learn in a writing course to do. First topic sentence. One idea per paragraph. Signposted transitions. Consistent register throughout. Each one of those is a marking criterion, each one of those reduces the statistical variation that the detector is measuring.

Two groups get caught by this more than anyone else. Writers working in English as a second or third language are taught the formal register as the safe register, and formal is the register a model defaults to. Careful revisers are caught for the opposite reason: revision removes variation, so the eighth draft of a chapter carries less of the roughness that reads as human than the second draft did. The mechanics behind all of it sit in the full guide to AI writing patterns, which is worth reading before you change a single sentence.

Does My Writing Sound Like AI? Run These Five Checks

Five checks, in order, on a draft you wrote yourself. Each takes a few minutes and none of them needs a tool or an account.

1. Sentence length spread. Count the words in ten consecutive sentences. If eight of them land between fifteen and twenty-five words, your range is narrow. Most human drafts carry at least one sentence under eight words somewhere in a page.
2. Paragraph opening shape. Read only the first sentence of every paragraph, in sequence. If each one announces the paragraph before delivering it, the shape is uniform even where the content is entirely yours.
3. Verb specificity. In your results or findings section, underline every main verb. Count how many name an operation you actually performed against how many are display verbs that could sit in any paper on any topic.
4. Formal vocabulary density. Take your three densest paragraphs and count the abstract formal words per hundred: underscores, showcases, multifaceted, comprehensive. Two doing real work is ordinary academic prose. Five doing none is the pattern.
5. The specificity test. Find every sentence that would still be true if you swapped your topic for a different one. Those sentences read as generated whoever typed them, and they are the reason a reader says a paragraph feels machine-written.

Check five matters most and no detector performs it. A sentence that survives having its subject swapped was carrying no information about your subject in the first place. That is the property a reader reacts to, and it is fixable in a way that sentence length is never going to be.

What to Change, and What to Leave Exactly as It Is

Most of what worries people about their own prose should be left alone. Organisation is not a defect and a clean surface is not evidence of anything. The table splits the common signals into the ones worth acting on and the ones to stop apologising for.

What you noticed	Why your own writing does it	Change it or leave it
Paragraphs are all a similar length	You drafted to a structure, then edited to a word limit	Leave it. Length should follow the argument, and sometimes the argument is even
Sentences sit in a narrow length range	Journal house style and a word count both push you toward one clause per sentence	Change three or four. Join the pairs the logic already joins, and cut one down to six words
Formal Latinate verbs throughout	Thesis templates and language coursework teach the formal register as the safe one	Change the ones doing no work. Keep the terms your field defines
Heavy signposting: first, second, finally	Markers ask for signposting, so you put it in on purpose	Leave most of it. Cut the ones announcing a paragraph the reader can already see
No contractions anywhere	Academic register excludes them in most journals and most departments	Leave it. Contractions are wrong for the genre whatever a detector prefers
Three-part lists in several places	Three items fit a sentence, and rubrics reward the shape	Change one or two. Symmetry in every list says more than any single word does
No typos, no slips, nothing rough	You proofread it, more than once	Leave it. A clean surface is not a signal about authorship

The last row is the one people argue with. Nobody should be adding a typo to a thesis to look human, and any advice telling you to do that is asking you to damage a submission to satisfy a number.

The Two-Minute Read-Aloud Check

Read three paragraphs aloud at speaking pace. Two things surface that silent reading hides. The first is breath: prose with no short sentences in it leaves you nowhere to stop, and you hear that before you can see it. The second is emphasis. A paragraph written by someone who cares about the argument has one sentence carrying more weight than the rest, and you find yourself stressing it without deciding to. A paragraph with no such sentence is flat, and flatness is the thing people are actually detecting.

If it reads flat, the repair happens at the level of what the sentence says. Cut any sentence that could belong to another paper. Put the number back in. Where two sentences make one point, make it once. TextPulse's AI word cleaner will count the vocabulary density for you across a long chapter, and the flatness stays yours to fix.

If a Detector Has Already Flagged It

A detector score is a probability estimate over a piece of text. It isn't a finding of fact about who typed it. Writers who get flagged by detectors include two groups described above: second-language writers and heavy revisers. The best way to respond to flagged text is to rewrite the flagged paragraph after the fact. That is, change the evidence you were planning to rely on. Rewriting the flagged paragraph after the fact is the weakest response available, because it changes the evidence you'd otherwise be relying on.

Keep the process evidence instead: version history, dated notes, the reading list you worked from, the drafts that came before this one. What that looks like in practice, and what a department will actually accept, is set out in the piece on how to prove you did not use AI.

TextPulse's AI humanizer reports an estimated Human Score computed from the text, which is a reading of the prose rather than a verdict on its author, and no tool on this site claims to know what a given detector will say about a given page.

The specific vocabulary is listed separately, in a page on the words that give ChatGPT away, and the single verb that does most of the damage is explained on its own.

The question worth replacing this one with is sharper. Instead of asking whether a paragraph sounds like a machine, ask which sentence in it only you could have written. If the answer is none of them, that is the paragraph to work on, and it would have been worth working on in a year with no detectors in it at all.