A permitting ethics board oversees AI-assisted findings on applications. Which accountability control best fits contested outcomes?

Requiring appeal paths when applicants contest AI-assisted permitting findings is the accountability control that fits contested civic outcomes: if automation influenced a finding, applicants need a workable channel to challenge facts, process, or discretion—not a dead end. The correct control works because redress converts AI-assisted decisions from opaque outputs into reviewable administrative actions, supports due-process expectations, and creates feedback that can reveal model or procedure errors. Publishing accuracy summaries when applicants contest AI-assisted findings fails conceptually because aggregate accuracy summaries do not give an individual applicant a workable channel to challenge a specific contested finding. Logging model versions when applicants contest AI-assisted findings fails because a logging trail that applicants cannot invoke is not itself a real redress control for contested outcomes. Providing plain-language explanations for contested AI-assisted findings fails as a standalone accountability control because explaining a decision is not the same as offering a path to challenge it when the outcome is contested. Exam caveat: appeal rights do not mean every contested finding must reverse the AI suggestion; they mean a human process can affirm, modify, or overturn with reasons on the record. Operational check: publish appeal instructions on permitting notices that used AI assistance, define timelines and decision-makers, prohibit punitive appeal fees, and track appeal outcomes as quality signals for the AI-assisted findings process.