This article proposes a statistical framework and two core rules for monitoring AI models and agents post-deployment. It frames monitoring as a sequential decision system, identifying four types of changes that can occur. The framework suggests treating thresholds as budgetary constraints and emphasizes that alerts should not alter the observed outcomes. AI
IMPACT Provides a conceptual framework for managing AI systems post-deployment, potentially improving reliability and operational efficiency.
RANK_REASON The item is an opinion piece discussing a framework for monitoring AI models, not a release or research paper.
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