How accurate are AI detectors?
What AI detector accuracy claims mean, why false-positive rate matters more than a headline percentage, and how IA Checker publishes its run.
Straight answers about AI detection: accuracy, false positives, schools, hiring and what a score is allowed to mean.
How the detector works, what is free, and what happens to your text.
Accusations, classrooms, hiring and what a score does not prove.
Questions people ask about other detectors and the category as a whole.
What AI detector accuracy claims mean, why false-positive rate matters more than a headline percentage, and how IA Checker publishes its run.
What you can run for free on IA Checker, and what document upload and Ultra require.
How IA Checker treats submitted text, and why you should read each vendor's privacy page before pasting sensitive writing.
How to read an AI percentage and verdict tier: lean of measured patterns, not the odds that someone cheated.
Why a detection score cannot prove ChatGPT use or authorship, and what to do with flagged text instead.
Common reasons human writing scores as AI: ESL, formal register, editing tools, short samples — and what to check next.
Documented bias of AI detectors against non-native English writing, and why scores must not stand alone in academic or hiring decisions.
What happens when generated text is paraphrased or humanized, and why "beating" a detector is the wrong frame.
How to think about ZeroGPT accuracy claims, free-tier limits, and where a sourced comparison helps.
What institutions should know about Turnitin AI writing detection: access limits, paraphrasing, and process around scores.
Whether AI detectors catch Claude output, and why model-specific certainty is usually overstated.
Legal and fairness basics for schools using AI detection: policy, privacy, and due process around scores.