Developing Explainable AI (XAI)

As Artificial Intelligence (AI) becomes integrated into high-risk domains like healthcare, finance, and criminal justice, it is critical that those responsible for building these systems think outside the black box and develop systems that are not only accurate, but also transparent and trustworthy. This course provides a comprehensive introduction to Explainable AI (XAI), empowering you to develop AI solutions that are aligned with responsible AI principles. Through discussions, case studies,

• Define key Explainable AI terminology and their relationships to each other
• Describe commonly used interpretable and explainable approaches and their trade-offs
• Evaluate considerations for developing XAI systems, including XAI evaluation approach, robustness, privacy, and integration with decision-making