Explainable AI for Big Data Control

Digital transformation of the world has become automated scenarios in our daily lives and made our lives easy and smart. The data collection, storage and maintenance have turned into big data. Big data in the digital industry has brought some problems from storage structure to data extraction. Big data analysis uses statistical, algebraic, probability, and artificial intelligence (AI) concepts. Explained AI (XAI) is a process to explain the reason for the output predictions or results. XAI concepts are used to build automated applications and self-reason for the steps taken and justify the next sequence. AI algorithms are black box approaches and XAI are white box approaches and transparent in decision-making and interpretation of the results. Big data control requires a specific reason for insights generated using AI from a huge database. This chapter insights knowledge about the explainable AI and big data control challenges. Detailed surveys on the XAI applications and XAI techniques and case studies are discussed.