Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions-How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world. - Provides a comprehensive examination of the technical foundations and social effects of algorithmic processes and how they are used to purvey and combat misinformation - Includes deep technical models for AI and ML algorithm developers who seek to alleviate the impacts of misinformation, including credibility assessment models, trust heuristics, and Information Processing Theory - Provides detailed technical understanding of computational approaches to combat misinformation such as automated deception detectors, clickbait detectors, satirical fake detectors, rumor debunkers, and computational fact-checking tools - Focuses on the human aspects of AI and misinformation, and the multidisciplinary study of trends, problems, and algorithmic functions

Autorentext

Dr. Don Donghee Shin is a Full Professor of Digital Media at the College of Communication and Media Sciences at Zayed University and a Distinguished Endowed Professor by the Korean Ministry of Education in the Department of Interactive Media at Sungkyukywan (Samsung) University, Seoul, South Korea. His research explores the impact of algorithmic platforms, combining topics in ethics, algorithms, human-computer interaction, and media studies. In his current research, he has researched mechanisms to investigate users' behavior around opaque algorithmic systems, redesign these systems to communicate opaque algorithmic processes to users, and provide them with a more informed, satisfying, and engaging interaction. His research is supported by the public sector and the private sector. Dr. Shin has been ranked among the top 2% of most-cited scientists in the world by Stanford University