Transparency and Accountability in Explainable AI: Best Practices

This chapter delves into the intricate dimensions of Transparency and Accountability in the context of Explainable AI (XAI). It defines transparency and accountability within AI systems, emphasizing their pivotal role in establishing trust, ensuring fairness, and addressing safety concerns. The chapter meticulously outlines best practices for transparency and accountability, covering aspects of data collection, algorithmic decision-making, model performance, user interface design, and legal compliance. By examining these practices, the chapter provides a comprehensive guide to fostering responsible and trustworthy AI systems.