Discipline that studies and implements measures to ensure AI systems operate safely, reliably, and aligned with intended goals. Covers model alignment, robustness against adversarial inputs, decision interpretability, uncertainty management, fail-safe mechanisms, behavioral monitoring, and prevention of harmful or unintended outputs in critical contexts.