Are AI Detectors Accurate? What an AI Score Really Means

The short answer

No AI detector is accurate enough to prove who wrote a piece of text. Detectors look for statistical patterns, and ordinary human writing can share them, so false positives happen. OpenAI withdrew its own AI text classifier in July 2023 because of its low accuracy. Treat any AI score, including the one from Lazyblink's AI Content Detector, as a prompt to look more closely, never as evidence on its own.

This guide explains what the Lazyblink score measures, why formal writing can score high, and what to do if your work is flagged.

What the evidence says about AI detectors

Two well-documented findings are worth knowing:

• OpenAI's own classifier was withdrawn. OpenAI launched a tool to distinguish AI-written text in January 2023. In July 2023 it added a note to the announcement saying the classifier was no longer available "due to its low rate of accuracy".
• Detectors can be biased against non-native writers. A 2023 study led by Stanford researchers ("GPT detectors are biased against non-native English writers", Liang et al.) ran seven popular detectors on 91 TOEFL essays written by people. On average, the detectors labelled 61.22% of those human essays as AI-generated. On essays by US eighth-grade students, the misclassification rate was much lower.

The reason is simple. Many detectors rely on measures of how predictable the wording is, and the Stanford-led study linked the false positives to this: text with common, predictable word choices is more likely to be flagged. Writers working in a second language, students following a strict template, and anyone writing technical or legal text often use plainer, more predictable phrasing. That makes their genuine writing look machine-like to a pattern detector.

What the Lazyblink AI score actually measures

The Lazyblink detector is a simple, transparent heuristic. It runs in your browser and does not call any AI model or compare your text with a database. When you click Detect AI Content, it does the following:

Splits the text into sentences at full stops, question marks and exclamation marks.

Measures sentence uniformity. It works out the average sentence length in characters, then counts what share of sentences are within 30% of that average. This becomes the "Sentence uniformity" percentage.

Checks for contractions. It looks for any of these: don't, won't, can't, isn't, aren't, I'm, it's.

Combines the two. The score is 60% weighted on uniformity, plus 40 points if none of those contractions appear.

Labels the result. A score above 65% shows a warning that the text "shows patterns consistent with AI-generated content"; 65% or lower says it "appears to be human-written".

The result also lists the sentence count and average sentence length, followed by a note that the analysis is indicative, not definitive.

What that means in practice

Because of how the score is built, a few things follow directly:

• Any text containing one of the listed contractions can score at most 60%, so it will always be labelled human-written, even if an AI wrote it.
• Formal text with even sentences and no contractions can reach 100%, even if a person wrote every word. Four short, factual sentences of similar length, the kind found in a textbook summary or a lab report, score 100% in testing.
• Short texts are unreliable. With two or three sentences, one sentence more or less changes the uniformity figure dramatically.
• The text needs sentence punctuation. If nothing ends in a full stop, question mark or exclamation mark, there are no sentences to measure and the score cannot be calculated. Add punctuation before checking.

In other words, the score describes writing style. It is useful for spotting monotonous rhythm in your own drafts. It is not a test of authorship.

Using the checker to improve your own writing

The two signals the tool measures are also two common weaknesses in stiff writing, whoever wrote it:

Paste your draft into the AI Content Detector and run it.

Look at Sentence uniformity. A very high figure means most sentences are about the same length. Readers find that monotonous. Combine two short sentences, or split a long one, where it helps the meaning.

Check Contractions used. In formal reports, avoiding contractions is correct, so ignore this signal. In emails, blog posts and conversational writing, natural contractions usually read better.

Run Word Frequency to find words you repeat too often.

Change the writing because it reads better, not to move a score. A score that drops from 80% to 40% after edits shows the rhythm changed, nothing more.

If your work is flagged as AI

Being accused on the basis of a detector score is stressful, but you can usually show your process.

• Keep your drafts. Version history in Google Docs or Microsoft Word shows the text being written over time. Save outlines, notes and earlier versions.
• Ask which tool was used and what it reported. A score without an explanation is hard to challenge; a named tool lets you point to its documented limits.
• Point to the evidence on false positives. The withdrawal of OpenAI's classifier and the Stanford-led TOEFL study are both public.
• Offer to explain your work. Talking through how you researched and structured a piece is strong evidence that you understand and wrote it.
• Check your institution's policy. Many universities and employers publish rules on AI use and on how detector results may be used.

If you are the one checking someone else's work

Teachers, editors and clients have good reasons to care about AI use. A responsible approach:

• Never rely on a single score. Different detectors can give different results for the same text.
• Compare with the person's earlier writing and ask about their process.
• Look for problems a score cannot see, such as invented sources, facts that do not check out, or text that ignores the actual brief.
• Be especially careful with writers working in a second language, for the reasons above.

What detectors cannot tell you

• Whether a person used AI for ideas but wrote the words themselves.
• Whether AI-generated text was heavily edited by a person.
• Whether a text is accurate, original or plagiarised. For plagiarism you need a tool that compares against published sources.

Summary

AI detectors estimate; they do not prove. The Lazyblink checker is open about what it measures: sentence-length uniformity and the absence of a few common contractions. Use it as a style check on your own drafts, keep your writing history in case questions arise, and never treat any detector score as the final word. If you want to make AI-assisted drafts read more naturally, the guide to making AI text sound human covers editing techniques.