This book investigates the social and economic behaviors exhibited by artificial intelligence, with a focus on trust, cooperation, and incentives. The first chapter examines the critical role of AI in decision-making and why understanding social and economic behavior is vital for improving AI interactions in both structured and dynamic environments. Subsequent chapters explore how AI systems such as deep reinforcement learning models simulate behaviors like trust and cooperation, and how large language models capture and reproduce patterns of social behaviors and economic incentives. By emphasizing behavioral analysis, the book aims to offer a scientific perspective on the mechanisms underlying AI’s interactions with human-like elements in decision-making. This interdisciplinary approach bridges artificial intelligence, economics, and social psychology to provide a comprehensive understanding of AI’s behavioral dynamics.

Kay-Yut Chen is a Professor of Information Systems and Operations Management at the University of Texas, Arlington. His research specializes in behavioral economics, econometrics, operations management, and, more recently, the decision-making behavior of AI systems. Dr. Chen's career has spanned academic research and corporate roles, with notable contributions to behavioral economics at HP Labs and Yahoo Labs. He has received awards such as the Management Science 2014 Best Paper Award in Operations Management and has been featured in various popular publications such as Scientific American and Newsweek.