Policy-Conditioned AI-Use Detection: An Evidentiary Framework for Academic Publishing
Major venues now publish detailed rules about how authors, reviewers, and area chairs may use AI, and those rules differ by role, by task, and by what must be disclosed. AI detection, the instrument usually proposed to enforce them, estimates something else: whether an AI model wrote the text. We argue that this target is misaligned with the decisions conferences and journals face, and propose policy-conditioned AI-use detection, an evidentiary framework for assessing whether a human--AI workflow complied with a stated rule. Policy makes the governing rule an explicit input. Inference reports hypotheses, evidence, calibration regime, and uncertainty in place of verdicts such as "AI detect...
| Authors | Jairo Diaz-Rodriguez, Mumin Jia |
|---|---|
| Primary category | cs.CL |
| Published | 29 September 2026 |
| Last updated at source | 13 October 2026 |
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