Example Concept: Organizations should establish a bias mitigation framework that includes regular bias audits, stakeholder engagement, and transparency measures. This framework should guide the development and deployment of AI systems to ensure they do not perpetuate or exacerbate existing biases. By using tools like fairness dashboards and bias detection algorithms, organizations can monitor AI outputs and make necessary adjustments to reduce bias.