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You cannot reliably prove a passage was written by AI from style alone. Treat unusual patterns as reasons to check claims and context—not as proof of authorship. AI detectors are also fallible: their results vary by system, text type, and task.
Start with clues, not conclusions
Writing may seem generic, unusually uniform, repetitive, over-formal, or short on specific experience. Those impressions can prompt closer reading, but none is a dependable “AI tell”: human writing can share the same traits.
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A 2025 study of frequent LLM users found that annotators considered lexical clues and broader qualities such as formality, originality, and clarity. That describes how those participants reasoned; it does not validate a checklist that can identify AI writing in every genre or situation. The study by Russell, Karpinska, and Iyyer examined 300 English nonfiction articles. In that specific study, the majority vote of five frequent LLM writing users misclassified one article. That result is not a promised accuracy rate for ordinary readers, other languages or genres, or newer models.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsCheck verifiable details
Follow citations, names, dates, quotations, and numerical claims back to their original sources. Check whether the source exists and actually supports the statement. A fabricated or mismatched citation is a concrete factual problem, whatever the author’s process; it is not, by itself, proof that AI wrote the surrounding passage.
- Open the cited source rather than relying on a search snippet or another article’s summary.
- Check that a quotation appears there and that its wording and context have not been changed.
- Verify dates, figures, and names against a primary source where possible.
- Separate a factual error from an authorship judgment: people make errors too.
Compare the work with relevant context
If authorship matters, look for context that can help explain how the text was produced: the writer’s earlier work, drafts, revision history, or account of their process. Compare like with like where possible. A change in topic, genre, editing, or writing conditions can alter someone’s style, so a difference is a question to discuss, not a verdict.
Use AI detectors cautiously
Detector output is a lead to investigate, not a reliable authorship certificate. Results vary between systems and tasks. NIST’s 2025 overview of its 2024 text-to-text pilot reports significant differences in performance by generator and discriminator: some generators deceived most discriminators, while some discriminators detected text from nearly all generators. The findings describe that evaluation, not a universal result for every detector or passage.
A detector percentage is not the share of text proved to be AI-written
Interpret a score according to the specific tool that produced it. Turnitin explains that its percentage refers to qualifying text its model identifies as likely AI-generated or AI-altered; it is not a literal measurement of the portion certainly authored by AI. Turnitin also says false-positive incidence is higher in its 0–19% range and that current reports show an asterisk instead of a percentage below its 20% threshold. Those details apply to Turnitin, not to every detector, and product guidance may change.
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Turnitin describes its model as targeting qualifying long-form prose. It says it does not reliably detect formats including poetry, scripts, code, bullet points, tables, or annotated bibliographies. A result from a tool should therefore be considered alongside the format and conditions of the text—not detached from them. Other detectors may define their coverage differently.
Do not ask ChatGPT to certify its own authorship
OpenAI’s Help Center says ChatGPT cannot reliably know whether it generated a particular passage and may invent an answer when asked. Its response to “did you write this?” is not evidence of authorship.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Match the evidence to the stakes
For casual curiosity, stylistic impressions may be enough to prompt a question. If a conclusion could affect someone’s education, work, or reputation, require stronger evidence and a fair process. Seek an explanation and relevant context, and follow the applicable policy or editorial procedure.
Rank #4
Turnitin warns that its model may misidentify human-written, AI-generated, and AI-paraphrased text and should not be the sole basis for adverse action against a student. That is vendor guidance specific to its tool, but it reinforces the broader point: a score or stylistic impression alone is not a sound basis for a consequential accusation.
Quick Recap
A practical checklist
- Notice patterns. Record what seems unusual, but do not treat generic phrasing, repetition, uniformity, or formality as proof.
- Verify the claims. Trace citations, quotations, dates, names, and figures to reliable sources.
- Consider context. If relevant and available, compare drafts or prior work while accounting for differences in topic, genre, and editing.
- Read detector output narrowly. Identify the tool, its stated coverage, and what its score means; do not translate a percentage into certainty.
- Ask before accusing. For high-stakes decisions, seek additional evidence and follow a fair process rather than relying on a single signal.
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