The AI content detector on this page does something most detection tools won't admit to: it tells you upfront that it cannot actually detect AI. What it can do is measure a handful of writing patterns — sentence-length variation, cliché density, vocabulary repetition, and paragraph uniformity — that tend to differ between typical AI output and typical human output, then combine them into a single "likelihood" number you can use as a starting point for your own judgment, not as a final answer.
We built this after watching the broader AI-detection space make a mess of things — teachers flagging honest students, freelancers losing gigs over a false positive, and editors trusting a percentage score more than their own eyes. Arb Digital works with content teams every day, and the honest take is simple: no tool, including the paid enterprise ones, can reliably tell you whether a specific piece of text was written by a person or a model. This page exists to show you the signals underneath the guesswork, so you can make an informed call instead of outsourcing it to a black box.
What This AI Content Detector Does
Paste in a sample of text and the tool runs four measurements against it. First, it calculates burstiness — the variance in sentence length across the passage. Human writers naturally swing between a short punchy sentence and a long, winding one; language models tend to settle into a narrower, more even rhythm. Second, it scans for a curated list of words and phrases that show up disproportionately often in AI-generated marketing and blog copy — words like "delve," "tapestry," "moreover," "furthermore," "in conclusion," "navigate the landscape," "unleash," "testament to," "realm," and "seamless." Third, it computes the average sentence length across the whole sample. Fourth, it measures how uniform your paragraph lengths are, since AI writers often produce suspiciously even paragraph blocks compared to the choppier structure people tend to write in.
Those four numbers get combined into a single 0–100 AI-likelihood score, along with a plain-English verdict like "Likely AI-assisted," "Likely human," or "Mixed signals." That's it — no server call, no third-party API, no data leaving your browser. Everything runs client-side in JavaScript the moment you click Analyze.
How to Use It
- Paste your text. Drop in at least a paragraph — three or four sentences minimum, though 150+ words gives the burstiness and cliché signals more to work with.
- Click Analyze Text. The tool scores the sample instantly and fills in the four metric tiles.
- Read the signals, not just the score. A high cliché count with low burstiness is a stronger pattern than either signal alone. A single "delve" in an otherwise varied, punchy paragraph means very little.
- Use it to edit, not accuse. If you wrote the piece yourself and it scores "likely AI," that's useful information about your sentence rhythm and word choices — not proof you didn't write it.
The Honest Truth: Why AI Detectors Can't Be Trusted
This is the part every detector should lead with and almost none do. AI-detection tools — free or paid, including the well-known commercial ones — work by estimating statistical patterns in text and comparing them against a trained baseline of "what AI writing tends to look like." That's a probability estimate, not a fingerprint. There is no cryptographic watermark on most AI-generated text that a browser-based (or even server-based) tool can read. It is pattern-matching on style, and style is a moving target.
Two failure modes matter here. The first is false positives: formulaic, plain, or highly structured human writing — the kind produced by non-native English speakers, technical writers, students following a rigid essay template, or anyone writing quickly under time pressure — often scores as "AI" because it shares the same evenness that models produce. Multiple studies and reporting, including coverage of OpenAI quietly retiring its own AI text classifier for unreliability, have documented this problem in academic settings, where students have been wrongly accused based on detector scores alone. The second is false negatives: lightly edited AI text — where a person changes a few words, breaks up a couple of sentences, or runs it through a paraphrasing pass — routinely slips past detectors entirely, because the underlying statistical signature shifts enough to fool the classifier.
Put together, that means a detector score is neither a reliable "gotcha" nor a reliable "all clear." Anthropic's own guidance on responsible AI use and OpenAI's published research on classifier limitations both acknowledge that current detection methods are not accurate enough to be used as a sole basis for high-stakes decisions. If you're an educator, an editor, or a hiring manager, treat any AI-detection score — including this one — as a single weak signal among many, never as evidence on its own. OpenAI's own writeup on why it discontinued its classifier is worth reading before you trust any tool that claims certainty.
How the Signals Are Calculated
Burstiness is computed as the statistical variance of sentence lengths (measured in words) across the sample, normalized so short samples don't get an unfairly extreme score. A tight cluster of similarly-sized sentences produces a low burstiness number; a mix of short fragments and long compound sentences produces a high one. The cliché scan runs a case-insensitive match against a list of roughly two dozen words and phrases that show up constantly in AI-generated marketing copy — terms like "delve into," "in today's world," "it's important to note," and "unlock the power of." Average sentence length is a straightforward word count divided by sentence count, using periods, question marks, and exclamation points as sentence boundaries. Paragraph uniformity compares the standard deviation of paragraph lengths against their average, so a document made of near-identical blocks scores as more "uniform" than one with varied section lengths.
None of these signals is unique to AI. A skilled human copywriter can absolutely write in short, even sentences on purpose for stylistic effect, and a chatbot prompted to "write like a human, vary your sentence length" will happily comply. That's exactly why this tool reports the raw signals instead of pretending they add up to certainty.
What a Good Score Actually Means
Think of the AI-likelihood number as a smoke detector for a chemistry lab, not a lie detector in a courtroom. It's tuned to be sensitive, which means it will occasionally flag things that aren't a fire. If your own writing scores "likely AI," the useful response isn't panic — it's to look at which signal drove the score. High cliché count? Swap in more specific, concrete language. Low burstiness? Read your paragraph out loud; you'll usually hear where a long sentence needs to be split or two short ones need to be joined. High paragraph uniformity? Break up a wall of same-length paragraphs with a one-line aside or a short list.
If you're evaluating someone else's writing — a student's essay, a freelancer's draft, a candidate's writing sample — the responsible move is to use the score as a prompt for a conversation, not a punishment. Ask the person to walk you through their research or their drafting process. That tells you far more than any percentage a browser script can generate.
Arb Digital's content team writes and edits copy with real research, real examples, and the sentence variety that no detector score can fake. See how we approach content strategy and drafting.
Explore Our Services All Free ToolsCommon Mistakes to Avoid
- Treating any single score as proof. Whether it's this tool or a paid competitor, a percentage is a probability estimate on noisy signals, not a fact.
- Testing very short samples. A single sentence or two doesn't give burstiness or paragraph-uniformity calculations enough data to mean anything.
- Ignoring context. Legal disclaimers, technical documentation, and press releases are written by humans in a deliberately formulaic style — they will often score higher on "AI-likeness" than casual blog writing, and that's expected, not suspicious.
- Using detection to accuse without a conversation. Especially in academic or employment settings, a score alone is not sufficient grounds for a disciplinary decision — ask questions first.
- Assuming a low score clears heavily-edited AI text. A few rounds of human editing on top of an AI draft can push the burstiness and cliché numbers down without changing the underlying source of the ideas.
Related Free Tools From Arb Digital
Want the metrics behind this score without the verdict? Try the Perplexity and Burstiness Checker for a purely educational read on predictability and rhythm. If you're drafting with AI and want to edit out the obvious tells, use the AI Text Humanizer Checker. Comparing which model to use in the first place? See the AI Model Comparison and the LLM Cost Comparison tool, or estimate token counts with the ChatGPT Token Counter. Browse everything in our free online tools hub.
Frequently Asked Questions
No. No tool — free or paid — can reliably prove a specific piece of text was AI-generated. This tool measures stylistic signals that correlate loosely with AI writing patterns and reports a likelihood estimate, not a fact.
Formulaic, concise, or non-native-English writing often shares the low burstiness and even structure that language models also produce, which is a well-documented false-positive pattern across all AI detectors.
No. This is a free, transparent, client-side heuristic tool that shows you exactly which signals it measures. Commercial detectors use proprietary models and, per their own published research, are also not reliable enough for high-stakes accusations.
Burstiness measures how much your sentence lengths vary. Human writing tends to burst between short and long sentences, while AI writing often settles into a more even, predictable rhythm.
Use it only as a conversation starter, never as a sole basis for a decision. Pair any flagged result with a direct conversation about the person's process.
No. All analysis happens locally in your browser with JavaScript. Nothing you paste is transmitted, stored, or logged.
