What Is AI Detection and How Does It Work? A Plain-English Explainer

The Core Idea: Predictability

Every AI detection tool — GPTZero, Turnitin, Copyleaks, Originality.AI — is built on the same fundamental insight: AI-generated text is more predictable than human-written text.

Language models like ChatGPT work by predicting the most probable next word, over and over again. This makes them extremely fluent — sentences always make sense, transitions are smooth, vocabulary is appropriate. But that predictability leaves a statistical fingerprint.

Human writers, by contrast, are unpredictable. We reach for unusual words. We break rules for emphasis. We write short fragments. We make odd structural choices. We go on tangents. We contradict ourselves. All of this unpredictability is actually what detectors are looking for.

Perplexity: The Main Signal

The technical term for predictability in language modeling is perplexity. Low perplexity = the text was very predictable = likely AI. High perplexity = the text surprised the model frequently = likely human.

AI detectors measure perplexity by running your text through their own language model and asking: "How surprised was I, word by word?" AI-generated text consistently produces low surprise scores. Human text produces higher, more variable scores.

Burstiness: The Second Signal

Burstiness measures how much sentence length varies throughout a document. Human writers naturally alternate between short punchy sentences and long explanatory ones. AI models produce sentences of remarkably similar length — consistently medium-long, consistently well-structured.

A document where every sentence is between 18 and 24 words is almost certainly AI-generated. A document that bounces between 4-word sentences and 45-word sentences is almost certainly human.

Other Signals Detectors Use

• Lexical diversity — AI models reuse similar vocabulary; humans range more widely
• Formality consistency — AI text maintains uniform formality; human text drifts naturally
• Transition phrase frequency — "Furthermore," "Moreover," "It is worth noting" appear at unnaturally high rates in AI text
• Structural uniformity — AI paragraphs tend to be the same length and follow the same topic-support-transition pattern

Why Detectors Aren't Perfect

AI detectors measure statistical patterns — they don't actually know whether a human or a machine wrote a piece of text. This means two things: (1) they can produce false positives on highly structured human writing (technical reports, legal briefs), and (2) they can be fooled by sufficiently good humanization that changes the statistical profile of the text.

The best approach: if you're using AI writing assistance, humanize the output before submission or publication. It reduces both the actual AI signal and the risk of false positive flags on your genuinely human-edited work.

How WriteHumanly's Detector Works

WriteHumanly includes a 7-signal AI detector that scores your text across perplexity, consistency, repetition, diversity, formality, burstiness, and stylometry. Run it before and after humanization to see exactly which signals improved and by how much. It's the fastest way to know whether your text will pass before you submit or publish.