How to compare conflicting AI detector results responsibly
Run the same paragraph through several AI detectors and you may get several different answers. One tool reports a high probability of AI-generated text, another calls it mostly human, and a third marks only a few sentences. The tempting response is to choose the score that confirms what you already believe. A better response is to treat the disagreement as a review problem. AI detector outputs are probabilistic signals. They can produce false positives and false negatives, and they do not prove who wrote a document. If the result could affect a student, employee, writer, or publication decision, the review process matters more than finding one authoritative-looking percentage. Here is a repeatable protocol for comparing results without turning them into a verdict. Disclosure: I used AI assistance while drafting this article and reviewed the final copy against the product workflow and source implementation. Start with one stable input A comparison is not meaningful if each detector sees...