Model misalignment occurs when an AI system's behavior diverges from its intended goals or human values, often producing harmful or unpredictable outputs. Researchers use it to study safety failures, alignment techniques, and training gaps. Beneficiaries include AI developers, policymakers, and users seeking reliable, ethical systems.
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