Hub · AI detection & flagxiety
Flagged as AI? Start here.
A detector score is a statistical guess, not a finding of fact — and the error rate lands hardest on non-native English writers. This page is the complete playbook: what to do right now, the research to cite, guides for every major detector, and how to have proof of authorship before anyone asks for it.
What to do right now — five steps
- Do not send a defensive reply yet. Nothing you write in the first hour helps. Acknowledge receipt if required, and ask for time to prepare a response. Panic emails become part of the record.
- Request the full detection report. Not the score — the report. Which passages were flagged, which tool, which version, what threshold. A score without a report is not evidence anyone can examine.
- Ask about the threshold and policy. What score triggers review? Is a detector score alone sufficient for a finding under your institution's policy? At most institutions it is not — their own rules require more.
- Gather your process evidence. Version history (Google Docs, Word autosave), earlier drafts, outlines, notes, search history, messages discussing the work. The goal is showing the document grew over time.
- Submit a written appeal and ask for human review. Present the evidence calmly, cite the false-positive research below, and request review under the formal academic-integrity procedure — not an informal chat.
The long version with templates: how to appeal a false AI accusation.
Why detectors misfire — especially on non-native writers
Detectors estimate whether text is machine-like by measuring statistical uniformity: how predictable the word choices are (perplexity) and how much sentence rhythm varies (burstiness). Careful formal writing has low variety by design — and writing produced between two languages carries translationese, which looks statistically similar to machine output. Nobody is «detected»; a resemblance is scored. The constant low-grade fear this creates has a name: flagxiety.
The research — cite this in your appeal
Every entry below is a verifiable, named source. This section is maintained as new research and rulings land.
- AI detectors falsely flagged 61% of TOEFL essays written by non-native English speakers.
— Liang et al., «GPT detectors are biased against non-native English writers», Patterns (Cell Press), 2023 - Across 14 detection tools tested on human, machine, and lightly edited text, researchers concluded the tools are «neither accurate nor reliable», with accuracy dropping sharply on paraphrased content.
— Weber-Wulff et al., «Testing of detection tools for AI-generated text», International Journal for Educational Integrity, 2023 - OpenAI retired its own AI-text classifier six months after launch, citing its «low rate of accuracy».
— OpenAI, AI classifier sunset notice, July 2023 - Vanderbilt University disabled Turnitin's AI-detection feature, writing that the tool's false positives and opacity made it unsuitable for misconduct decisions.
— Vanderbilt University, Brightspace announcement, August 2023 - Synonym-spinner paraphrasing produces detectable «tortured phrases» («counterfeit consciousness» for «artificial intelligence») that have led to journal retractions — a separate failure mode from AI detection, often conflated with it.
— Cabanac, Labbé & Magazinov, «Tortured phrases» research, 2021 - Litigation over AI-detection accusations has reached US courts, beginning with a Massachusetts case over a high-school AI-cheating finding.
— RNH v. Hingham Public Schools, filed 2024 — see our lawsuits tracker for the current cycle
Per-detector and situation guides
- Turnitin AI detection — how accurate is it?
- Turnitin similarity score — what's actually safe?
- Copyleaks flagged you — what to do
- GPTZero vs Turnitin vs Originality — accuracy compared
- How common are false positives?
- How to appeal, step by step
- Accused of using AI on work you wrote
- The lawsuits: what ESL writers should know
- Detectors and neurodivergent writers
- Patchwriting — the other reason ESL writers get flagged
The stronger position: proof that exists before the accusation
Everything above is defense after the fact. The structural fix is evidence that accumulates while you write: version history at minimum — or, for work where the stakes are real, the Diglot Authorship Certificate: an append-only, cryptographically signed record of your writing process, verifiable by anyone you share it with. An accusation against a documented process usually ends the conversation, not starts it.
Flagged as AI — questions
Can a detector score alone prove I used AI?
No. An AI-detection score is a statistical estimate that your text resembles machine-generated patterns — it identifies no source, no tool, and no act. Most institutional policies require more than a score to sustain a misconduct finding, and vendors themselves caution against using scores as sole evidence.
Why was my writing flagged when I wrote every word myself?
Detectors flag statistical uniformity: predictable word choices and even sentence rhythms. Careful, formal writing — especially by non-native speakers who learned English through study — has exactly those properties. A Stanford study found 61% of human-written TOEFL essays were falsely flagged. Your writing being flagged says more about the method than about you.
Should I run my essay through detectors before submitting?
It can lower anxiety, but treat results loosely: detectors disagree with each other, scores change between versions, and «passing» one tool does not mean passing the one your institution uses. Better long-term protection is process evidence — drafts, version history, or a cryptographic record like the Authorship Certificate.
What evidence actually wins appeals?
Process evidence. Version history showing the document growing over hours and days, earlier drafts with your own corrections, notes and outlines, search history. Committees find a documented writing process far more persuasive than any counter-score from another detector.
How do I protect myself before anyone accuses me?
Write where history is kept (Google Docs, Word with autosave, or Diglot), keep outlines and notes, and for high-stakes work use the Authorship Certificate — an append-only, cryptographically signed record of how the document was written that exists before anyone asks.
Diglot is a bilingual writing editor with authorship proof built in — start for free, no credit card required.
