Example Concept: Accountability in AI-driven decisions involves assigning responsibility across the AI lifecycle, from design and development to deployment and monitoring. Organizations should implement governance structures that define roles, responsibilities, and processes for identifying, mitigating, and reporting errors. This includes maintaining audit trails, conducting regular bias and fairness assessments, and ensuring transparency through documentation like model cards.