There is no reliable phrase, punctuation mark, or polished writing style that proves a passage was written by AI. You can notice signs that text feels generic or formulaic, but treat them as reasons to ask questions—not as evidence for accusing someone. AI detectors also make mistakes, and a chatbot cannot reliably certify whether it wrote a passage.
What signs can make writing seem AI-generated?
Readers may notice prose that feels generic, formulaic, or unlike the author’s usual voice. Those impressions can be useful starting points for closer reading, but no single stylistic trait establishes who wrote a text. A tidy structure, smooth transitions, polished sentences, or a particular word choice is not proof of AI authorship.
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Researchers can measure patterns in writing. A 2025 study of Japanese-language text examined phrase patterns, part-of-speech bigrams, and function-word use. Its online survey involved 403 participants and found human ability to distinguish AI-written from human-written text was limited in that study’s setting. The result is bounded by its language, sample, models, and task; it does not establish a universal checklist for identifying AI writing. Read the study.
Can AI detectors tell who wrote a passage?
Detectors classify text based on patterns or other signals; their results are not proof of authorship. They can produce both false positives—labeling human writing as AI-generated—and false negatives—missing AI-generated text. The consequences matter: a mistaken score can unfairly cast suspicion on a human writer, while a missed signal does not show that text was human-written.
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OpenAI reported that its 2023 classifier identified 26% of AI-written text as “likely AI-written” and incorrectly labeled 9% of human-written text as AI-written on its English challenge set. The 26% figure is the share of AI-written samples identified in that test, not overall accuracy. OpenAI discontinued the classifier on July 20, 2023, citing low accuracy. These are historical results for that specific tool and evaluation—not a current score for all detectors. OpenAI said the classifier “should not be used as a primary decision-making tool” and described it as a possible complement to other methods. OpenAI’s classifier announcement.
OpenAI’s educator guidance likewise cautions against relying on detectors to determine whether text was written by AI. Read OpenAI’s guidance for educators.
Why can edited or short passages be difficult to assess?
Text length and how it was produced affect what a detector can assess. OpenAI’s documentation describes limitations for short, constrained, edited, translated, or unsupported text. A passage may also combine human and AI contributions, making a simple either-or label a poor fit.
OpenAI’s textGrain watermark evaluations illustrate both the potential and the limits of a provenance signal. In controlled evaluations of watermarked English answers about psychology, it identified about 80% of 200-token passages and about 95% of 400-token passages at a target 1% false-positive rate. In the same 400-token evaluation, replacing 10% of words reduced detection from about 92% to 66%; replacing 25% reduced it to 17%. These figures describe specific controlled tests, not a guarantee for everyday writing. OpenAI’s text provenance announcement.
What does a text watermark actually show?
A watermark is a provenance signal, not an authorship certificate. OpenAI says textGrain can indicate that an OpenAI system generated or processed text. It does not identify the user, measure how much a person contributed, establish who is responsible for the final wording, or verify that the text is accurate. OpenAI also states: “The absence of a detected watermark does not prove human authorship.” The signal therefore cannot settle who wrote a passage or how it was created.
Should you ask ChatGPT whether it wrote something?
No. OpenAI says ChatGPT may make up an answer when asked whether it wrote a passage; its answer has no factual basis. A chatbot’s claim about authorship is not reliable evidence. OpenAI’s explanation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you investigate a concern about authorship?
If authorship matters, focus on evidence beyond a detector score or stylistic impression. Consider the stakes before acting: a screening signal may be a reason to review a situation, but it should not be the sole basis for a consequential accusation. OpenAI has cautioned against using its classifier as a primary decision tool, and its text detector access is initially restricted to approved researchers and expert organizations. The available sources do not establish an independent, current comparison that would support recommending a particular commercial detector.
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- Ask about the writing process and any permitted tools, rather than treating a detector result as a verdict.
- Check whether the text is long enough and suitable for the tool’s stated scope, and whether it has been edited, translated, or combined with other writing.
- For high-stakes decisions, use a fair review process and multiple relevant forms of evidence; do not make an accusation from a single score or surface clue.
Studies and systems are bounded by the languages, text types, models, and conditions they evaluate. A 2025 ACL Anthology paper examines whether frequent ChatGPT users can detect outputs from GPT-4o, Claude, and o1, but its available summary does not support a reliable percentage or a portable visual checklist. View the paper.
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