What This Calculator Actually Does
Paste a passage and this tool estimates how 'AI-like' it reads on the surface. It is not a real detector and it does not phone a model — it applies a transparent heuristic in your browser, scoring signals such as low predictability, uniform sentence length, and repetitive phrasing. The output is a rough probability and a risk label, meant to help you understand what tips detectors off. Treat it as a mirror for your own draft, not a judgment about authorship.
The Signals It Reads: Perplexity, Burstiness, and Stock Phrases
Three plain ideas drive most AI detection. Perplexity is predictability: if nearly every word is the one a model would have guessed next, the text scores as 'AI-like,' because generators favor probable words. Burstiness is sentence-length variety — humans swing between short punches and long, winding sentences, while machine text often holds a steady mid-length beat. Consider 'It rained. The game stopped. Nobody minded.' next to 'The persistent rainfall eventually caused the organizers to postpone the scheduled afternoon match.' The first is bursty and less predictable; the second is smooth and even. The third signal is simple: recurring stock phrases like 'delve into,' 'in today's world,' and 'it is important to note' that generated drafts overuse.
Why You Should Not Trust the Number Too Much
Every signal here is a correlation, not proof. Careful, formulaic human writing — a cover letter, a lab report — can read as low-perplexity and low-burstiness and score high. Meanwhile a lightly edited AI draft can score like a person. Real commercial detectors have this same weakness: independent tests show false-positive rates around 5-15%, and research has found they flag non-native English writers far more often than native ones. Use the score to improve your own prose, and never to decide whether someone else cheated.
AI Detection Score Calculator
Paste your text below to estimate how likely AI detectors would flag it.
AI Detection Tool Accuracy Comparison
Independent testing results (2025-2026)
| Detector | AI Text Accuracy | Human Text Accuracy | False Positive Rate | Best Use |
|---|---|---|---|---|
| GPTZero | 82% | 88% | 12% | Academic screening |
| Originality.ai | 86% | 91% | 9% | Content marketing |
| Turnitin AI | 78% | 94% | 6% | University papers |
| Copyleaks | 80% | 89% | 11% | General purpose |
| Sapling AI | 74% | 86% | 14% | Quick checks |
| Winston AI | 83% | 90% | 10% | Publishing |
How to Use This Calculator
- Paste at least 50 words: Drop in a real passage of your own writing. Short snippets give the perplexity and burstiness signals too little to work with, so longer samples produce a steadier estimate.
- Pick the content type: Choose whether it's general, academic, business, creative, or technical. Formal and technical writing is naturally more uniform, so telling the tool the genre keeps the score in a fair range.
- Analyze the text: Press Analyze Text. Everything runs locally in your browser — your writing is never uploaded — and the breakdown appears immediately below.
- Read the signals, not just the number: Look past the headline probability to the sentence-variance, vocabulary-diversity, and stock-phrase flags. They show you which patterns pulled the score up so you know what to rework. Remember the result is a rough signal, not proof of authorship.
How It Works
Paste a passage and this tool reads it the way a machine reader would — measuring how predictable each word is, how much your sentence lengths vary, and how often certain giveaway phrases show up. It then turns those readings into a single illustrative score. Think of it as a mirror that shows which surface patterns in your writing tend to trip AI detectors, not a verdict on who or what wrote the text.
The basic rule:
- AI text tends to have uniform sentence lengths — human writing varies more in rhythm and structure
- AI frequently uses certain phrases: 'delve into', 'it's important to note', 'in today's world', 'landscape', 'leverage'
- Low vocabulary diversity (many repeated common words) is a strong AI signal
- AI text tends toward medium-length sentences (15-25 words) and avoids very short or very long ones
Here is the honest part: these signals are correlations, not proof. Plenty of careful human writing scores high, and edited AI text scores low. Real detectors carry false-positive rates in the 5-15% range, and studies have shown they flag writing from non-native English speakers far more often than native writing. Treat any score here as a conversation starter about your own draft — never as evidence about someone else's.
Tips & Considerations
- Read your draft aloud — the spots where you stumble or hear a flat, even rhythm are usually the same low-burstiness stretches that push the score up.
- Vary your sentence lengths on purpose: follow a long, winding sentence with a short, blunt one to break the steady machine-like beat.
- Delete stock phrases like 'delve into,' 'it is important to note,' and 'in today's world' — swapping them for plain, specific wording lowers the score and reads better.
- Add something only you could write: a real example, a concrete number, a small opinion. Specific detail raises perplexity in the human direction.
- If this tool or a real detector flags your writing, treat it as feedback on your draft — not as evidence, and never as grounds to accuse anyone else.
Frequently Asked Questions
What is perplexity in AI detection?
Perplexity measures how surprised a language model is by the next word. If almost every word is the one a model would have predicted, perplexity is low — and low perplexity is a classic 'AI-like' signal, because generators tend to reach for the most probable word. Human writing is bumpier: we drop in odd word choices, tangents, and turns of phrase a model would not have guessed, which pushes perplexity up. The catch is that clear, formulaic human writing (a polished cover letter, a textbook paragraph) is also low-perplexity, which is one reason these signals misfire.
What is burstiness and why does it matter?
Burstiness describes how much your sentence lengths vary. Human writing tends to be bursty — a nine-word sentence, then a rambling twenty-eight-word one, then a three-word fragment. Machine text often settles into a steady rhythm of similar mid-length sentences. Compare 'The results were clear. Everyone agreed. Then the argument started.' with 'The results were fairly clear and most of the participants agreed with the overall conclusion of the study.' The first is bursty; the second is smooth. Low burstiness nudges a detection score up, but it is a stylistic tell, not evidence of anything.
Are AI detectors accurate?
No — not accurate enough to rely on. Vendors advertise high numbers, but independent testing repeatedly finds false-positive rates around 5-15%, meaning genuine human writing gets flagged. OpenAI even retired its own detector in 2023 for low accuracy. Detectors do worst on short passages, edited or paraphrased text, and writing from non-native English speakers, whose simpler vocabulary reads as 'predictable.' A score is a rough signal, never a fact.
Can this prove a piece of text was written by AI?
No, and neither can any commercial detector. This tool only measures surface patterns — predictability, sentence variety, stock phrases — that happen to correlate with AI output. Correlation is not proof. A human can write low-perplexity, low-burstiness prose, and a careful AI edit can score like a person. Please do not use this or any detector to accuse a student, employee, or writer of cheating; a false accusation does real harm, and the underlying signals simply cannot bear that weight.
Why do AI detectors flag non-native English writers so often?
Detectors reward vocabulary variety and unpredictable phrasing. Writers working in a second language often use a smaller, more common set of words and steadier sentence structures — the same features a detector reads as 'machine-like.' A widely cited Stanford study found detectors flagged the majority of essays by non-native speakers as AI while rarely flagging native writers. That built-in bias is a core reason detection scores should never drive consequences for a real person.
How should I actually use this score?
As a curiosity check on your own draft. If your writing scores high and that surprises you, read it aloud and notice where it feels flat — uniform sentences, hedge words, phrases like 'it is important to note.' Then rewrite for your own voice: real examples, varied rhythm, specific detail. The goal is clearer, more human writing, not gaming a detector. And if you are on the receiving end of a detector result, treat it as a prompt to have a conversation, never as a confession.