Example Concept: Organizations must establish processes for bias detection and mitigation, such as regularly auditing AI models for disparate impact across different demographic groups. This includes using fairness metrics to assess model outputs and implementing corrective actions when biases are detected. Transparency in model decision-making and stakeholder engagement are also crucial to maintaining accountability and trust.