Explainable AI

Explainable AI (XAI) refers to the transparency, interpretability, and accountability of artificial intelligence (AI) systems, enabling users to understand how AI algorithms make decisions and predictions. It addresses the black-box nature of many AI models by providing explanations, visualizations, and reasoning capabilities for model outputs and predictions. Readers can explore XAI techniques, frameworks, and applications for enhancing trust, fairness, and ethical AI deployment in critical domains such as healthcare, finance, and criminal justice.