Explainable AI (XAI) encompasses techniques and methods to make the decisions and predictions of AI models transparent and understandable to humans. It addresses the "black box" problem by providing insights into how AI systems reach their conclusions.

NYD Application: Essential for client trust and debugging - helps us understand why our AI tools make specific recommendations for code improvements or design choices.

Example: "Our XAI dashboard shows clients exactly why the AI recommended specific security improvements to their codebase."