Feature Bias Audit

مسودة ترجمة بمساعدة آلية (Arabic) for "Feature Bias Audit": Feature Bias Audit is a ml review process that looks for uneven model behavior across groups or segments for input signals used by a machine learning model. It uses slice metrics, representative data, and reviewer notes so teams can surface fairness risks while keeping evidence, reliability, and public-safe operational boundaries clear.

“مسودة مثال: The machine learning team used Feature Bias Audit when a feature distribution shifted, so the team could surface fairness risks before the model moved into evaluation.”