AI Detector – Check if Text is AI-Generated or Human-Written
About the AI Detector
The AI Detector analyzes a piece of text and estimates whether it was written by a person or generated by a language model. You get a clear label — Human, AI, or Mixed — alongside a Human Score, an AI Score, and a separate Confidence Level that tells you how much weight the result deserves.
Detection works by measuring statistical properties of the writing rather than understanding what it says. Two of these matter most. Perplexity measures how predictable each word is given the words before it: human writing tends to make surprising choices, while model output gravitates toward the likeliest next word. Burstiness measures variation in sentence length and structure across a passage — people write a long winding sentence, then a short one, then a fragment, while generated text tends toward uniform rhythm. Low perplexity plus low burstiness is the signature that pushes a score toward AI.
That is also why no detector, including this one, can be treated as proof. The signals are probabilistic, not forensic. Polished corporate writing, technical documentation, and text by people writing in a second language all tend to score as more AI-like, because clear, conventional, evenly structured prose looks statistically similar to model output. In the other direction, lightly editing AI text — varying sentence lengths, swapping predictable words — moves the score toward human without changing who wrote it. Treat a result as a signal worth investigating, not as evidence, and never as the sole basis for an accusation about a student or a writer.
The Confidence Level exists precisely for this. A 70% AI Score at 40% confidence is close to noise; the same score at 90% confidence means the text has consistent, strong markers throughout. Short passages produce low confidence almost by definition, since there is not enough material to establish a pattern, which is why a minimum length is enforced.
Our editorial team at BigToolSite ran this detector against text we wrote ourselves, raw model output from several assistants, and hybrid drafts where AI-generated paragraphs were rewritten by hand, mapping how the Human and AI scores shift as edits accumulate and where the Mixed label starts appearing.
If a check flags your own draft and you want it to read less mechanically, the AI Humanizer reworks phrasing and sentence rhythm toward a more natural pattern.
Because detection needs enough material to be meaningful, checking length first is worthwhile, and the Word Counter gives you the exact figure along with a reading-time estimate.
When you want to see precisely what changed between an original and a revised version, the Text Diff Checker highlights every difference line by line.
How to Use the AI Detector
- Paste your text into the Text to Analyze box.
- Watch the word counter above the box. Text must clear the minimum length and stay under the maximum shown there.
- Complete the security verification below the text box. This keeps the tool available by blocking automated abuse.
- Click Detect AI Content.
- Read the result label first: Human, AI, or Mixed.
- Check the Human Score and AI Score bars for the percentage split between the two.
- Read the Confidence Level before drawing any conclusion. A high score at low confidence is not a finding.
- For a long document, check several sections separately rather than pasting everything at once. Mixed authorship shows up far more clearly that way.
Example Usage
Input: a paragraph from a blog draft — “Our team spent the weekend testing three different coffee makers, and honestly, the results surprised us…”
Output:
- Result: Human
- Human Score: 82.40%
- AI Score: 17.60%
- Confidence Level: 88.10%
The conversational aside, the varied sentence lengths, and the first-person specificity all push this toward human. A high Human Score paired with high confidence is the clearest reading you can get.
Scores clustered near 50/50 usually return Mixed, which most often means AI-drafted text that a person then edited, or human writing that was tidied up by a model. It can also mean the passage was simply too short or too plain to classify with any conviction — check the Confidence Level to tell those two situations apart.
A useful exercise before relying on any detector: run three or four samples of your own known writing through it. If your own work scores as partly AI, that tells you how the tool reads your particular style, and it recalibrates how much weight you should give a result on someone else’s text.
Frequently Asked Questions
It gives a solid estimate from statistical patterns, but no detector is reliable enough to be treated as proof. Read the Confidence Level alongside the scores, and treat a result as a prompt to look closer rather than a conclusion.
They measure how predictable the writing is and how much sentence length and structure vary. Generated text tends to favor likely word choices and even rhythm, while human writing is more irregular. The scores reflect those measurements, not any understanding of meaning.
The text shows characteristics of both. In practice this usually means an AI draft that someone edited, or human writing a model has polished. Very short or unusually plain passages can also land here simply because there is not enough signal.
Yes, and this is its most important limitation. Formal, technical, and heavily edited prose scores as more AI-like, as does writing by people composing in a second language. Never treat a flag as evidence of misconduct on its own.
Often, yes. Editing generated text to vary sentence lengths and replace predictable phrasing moves the score toward human without changing its origin. Detection is a moving target, not a settled problem.
Short passages do not contain enough sentences to establish a pattern, so any result would be close to guesswork. Longer text gives the analysis something consistent to measure.
Yes. The minimum and maximum are both shown above the text box. For longer documents, checking section by section gives more useful results than one large paste anyway.
A set number per visitor, displayed above the text box. The allowance resets 24 hours after your first check of the day.
It blocks automated scripts from consuming the service, which keeps the tool responsive and available for everyone.
It can flag work worth a conversation, but it should never be the basis of an accusation. False positives disproportionately affect careful writers and non-native English speakers. Draft history, in-person discussion, and knowledge of the student’s usual voice are far more dependable.
Google’s stated position is that it rewards helpful, original content regardless of how it was produced, and targets low-value content produced at scale rather than AI use itself. The practical concern is quality and usefulness, not authorship method.
The text is submitted for analysis and not retained afterward. It is not saved to a profile or used for any other purpose.
