Minds, Machines, and Misinformation

Decoding Bias, Algorithms, and Trust

Don Donghee Shin

• Publisher: Elsevier
• Year: 2025
• eBook ISBN: 9780443161056
• Edition: 0
• Topic: Computer Science
• Subtopic: Computer Science General
• Index: Computer Science

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

Table of contents

• Title of Book
• Introduction
• Chapter 1 Unraveling susceptibility: the psychological drivers of belief and action on misinformation
• Chapter 2 The diffusion of misinformation: how and why does misinformation spread?
• Chapter 3 Human–misinformation interaction
• Chapter 4 AI-fueled deception: mechanics of machine-driven manipulation
• Chapter 5 Immunizing intelligence: toward bias-aware algorithmic systems
• Chapter 6 Privacy-preserving AI: strategies and ethical imperatives
• Chapter 7 Artificial general intelligence and misinformation: balancing innovation and ethical challenges
• Glossary
• Appendix A. Tools and resources
• Appendix B. Case studies
• Appendix C. Ethical guidelines for AI development
• Author Index
• Subject Index