This book provides a comprehensive exploration of human-in-the-loop artificial intelligence (AI), covering topics that range from its fundamental concepts to data quality control, learning methods, explainability, incentive design, fairness, and ultimately human–AI collaboration.The first half of the book organizes the theoretical foundations of human-in-the-loop and the design principles that support them, while the second half discusses how these ideas can be applied in real-world systems and applications, as well as the broader social implications of human-in-the-loop AI. Each chapter is self-contained and can be read independently, depending on the reader’s interests and needs.This book is suitable for researchers, practitioners, and students who are working on a wide variety of topics in AI.
