Abstract
This review thoroughly examines explainable artificial intelligence (XAI) and its importance in creating responsible AI. It covers AI's background, guiding principles, the distinction between interpretability and explainability, and various explanations. We emphasize the importance of transparency in explainable systems and its application in various high-stakes fields. We will also discuss the state of regulations and give a forecast for XAI research and regulation shortly.