How AI detectors work
Most detectors are classifiers trained on large collections of human and AI text. They look for statistical patterns: how predictable the next word is (perplexity), how much sentence length varies (burstiness), and the frequency of certain phrases and structures. Some tools also check for watermarks or token patterns specific to a model.
When you paste text into a detector, it returns a probability score. A high score means "this looks like training examples labeled AI." It does not mean "a human definitely did not write this."
The false positive problem
Detectors regularly flag human writing — especially from non-native speakers, technical writers, and people trained to write clearly. Short, simple sentences and repeated structure look statistically similar to AI output even when a person wrote every word.
Studies from MIT, Stanford, and independent labs have shown false positive rates between 4% and 50% depending on the tool and the population. That range is too wide to rely on for high-stakes decisions.
The false negative problem
Edited AI text is much harder to catch. If someone runs AI output through a humanizer, mixes it with their own sentences, or simply prompts the model to write more casually, the statistical signals blur. A detector might report "human" even when most of the text came from a model.
How to use the Glint AI Detector
Glint AI's AI Detector gives a 0–100 "AI suspicion score" using local heuristics: burstiness, vocabulary diversity, and the density of common AI phrases. It runs entirely in your browser — no text is uploaded. Use it to:
- Spot drafts that feel too uniform before publishing.
- Compare different versions of the same paragraph.
- Train your own eye to recognize AI tells.
It is not a courtroom tool. It is an editing compass.
When detectors help — and when they fail
| Use case | Helpful? | Why |
|---|---|---|
| Editing your own draft | ✅ Yes | Catches over-smoothed passages worth rewriting. |
| Screening lots of submissions | ⚠️ Partially | Good triage, bad as a final filter. |
| Accusing someone of cheating | ❌ No | False positives are too common for proof. |
| Auditing your content workflow | ✅ Yes | Helps you see where human review is missing. |
What to do when a detector flags your text
First, don't panic. Second, break up long sentences, add a concrete example, swap a few AI-sounding words, and test again. If the score drops and the text reads better, you've improved the draft. If the score stays high but the writing is clearly yours, ignore the tool and trust your reader. For a faster rewrite, pair the detector with the AI humanizer guide.