Why Human Writing Gets Flagged as AI (and How to Fix It)
Detectors flag human writing all the time. Here's why it happens, who it happens to most, and how to keep your own prose from tripping the classifier.
Every semester there's a story: a student writes their own essay, submits it, and gets flagged as AI. Sometimes they can prove they wrote it — version history, handwritten notes, a Google Doc timestamp. Sometimes they can't. Here is why detectors get it wrong, who it happens to most, and what you can do about your own writing before you submit.
The two things detectors actually measure
Almost every AI detector scores two features under different names: how predictable the text is (perplexity), and how varied the sentences are (burstiness). LLMs default to low perplexity and low burstiness. Unfortunately, so does a lot of legitimate human writing: formal academic tone, non-native English, technical documentation, or a student writing carefully because English is not their first language.
Who gets flagged most
Independent research from Stanford and elsewhere has repeatedly shown that non-native English writers are false-positive-flagged at 2 to 5 times the rate of native writers. Their vocabulary is more restricted, their sentences more uniform, their idioms less idiosyncratic — all of which reads as "AI" to a classifier trained on native prose. High-school students who learned the five-paragraph essay structure by rote get flagged for similar reasons.
The vocabulary trap
Careful writers over-use certain words: "however", "therefore", "in addition", "furthermore", "ultimately", "significantly". Every one of these is a top flag word in detector training data because LLMs over-use them too. If you were taught to write formally, you probably use them by habit. Cut them.
How to pre-check your own writing
Before you submit, run your draft through at least two detectors (GPTZero and ZeroGPT both have free tiers). If a paragraph flags high on both, rewrite it — not to hide AI use, but because your own prose is triggering the same signals. Common fixes:
- Split one long sentence per paragraph into a shorter one
- Delete one connector word per paragraph
- Add one concrete example, name, or number per section
- Vary sentence openers — don't start three sentences in a row with the same word
What to do if you get flagged unfairly
Ask for the raw score, not the summary. Ask which detector was used. Ask what threshold the professor treats as evidence. Provide your version history from Google Docs or your word processor. Most schools have appeals processes precisely because false positives are well-documented.
Related: Can professors prove you used ChatGPT? and GPTZero vs Turnitin vs Copyleaks.