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Format: 1 Online-Ressource (xiv, 286 Seiten) , Illustrationen

ISBN: 9783031525698

Content: This book serves as a guide to understanding the dynamics of AI in human contexts with a specific focus on the generation, sharing, and consumption of misinformation online. How do humans and AI interact? How is AI shaping our understanding of ourselves and our societies? What are the interaction mechanisms that govern how humans and algorithms contribute to misinformation online? And how do we bridge the gap between ethical considerations and practical realities to make responsible, reliable systems? Exploring these questions, the book empowers humans to make AI design choices that allow them meaningful control over AI and the online sphere. Calling for an interdisciplinary approach toward human-misinformation algorithmic interaction that focuses on building methods and tools that robustly deal with complex psychological/social phenomena, the book offers a compelling insight into the future of AI-based society. Dr. Shin is a Chair and Professor at the College of Media and Communication at Texas Tech University. He was the founding Chair of the Department of Interaction Science, an industry-academia research initiative sponsored by Samsung and the Ministry of Education in Korea. He was awarded an Endowed Distinguished Professorship by the Ministry of Education in Korea and a SKK Endowed Chair (2010-2016)

Note: Includes index , Part I: The Cognitive Science of Misinformation: Why We Are Vulnerable and How Misinformation Beliefs Are Formed/Maintained -- 1 Introduction: The Diffusion of Misinformation -- 2 Misinformation and Bias -- 3 Misinformation and Radicalization -- Part II: How People View and Process Misinformation: How People Respond to Corrections of Misinformation -- 4 Misinformation, Paradox, and Heuristics -- 5 Misinformation Processing Model -- Part III: How to Combat Misinformation Online Amid Growing Concerns and Build Trust -- 6 Misinformation and Diversity -- 7 Misinformation and Nudge -- Part IV: What Are the Implications of AI for Misinformation? The Challenges and Opportunities When Misinformation Meets AI -- 8 Misinformation and Inoculation -- 9 Misinformation and ChatGPT -- 10 Conclusion: Misinformation and AI.

Additional Edition: ISBN 9783031525681

Additional Edition: Erscheint auch als ISBN 303152568X

Additional Edition: ISBN 9783031525681

Language: English

URL: lizenzpflichtig

UID:

Format: XIV, 286 p. 21 illus. , online resource.

Edition: 1st ed. 2024.

ISBN: 9783031525698

Content: "This book discusses how misinformation is used to manipulate the public and deny empirically verified evidence and truths, why humans have become more and more susceptible to fake news, and how the spread of misinformation can be managed and controlled using technologies such as AI." -Frank Biocca, New Jersey Institute of Technology, Newark, NJ, US "Bringing the cognitive science of misinformation to AI, the book guides you through the focal points and possible pitfalls of artificial misinformation. Informed by years of research, the book provides insightful analytics on the misinformation dynamics that lie at the intersection of human minds and the double-edged sword of AI." -John Pavlik, Rutgers, the State University of New Jersey, New Brunswick, NJ, US This book serves as a guide to understanding the dynamics of AI in human contexts with a specific focus on the generation, sharing, and consumption of misinformation online. How do humans and AI interact? How is AI shaping our understanding of ourselves and our societies? What are the interaction mechanisms that govern how humans and algorithms contribute to misinformation online? And how do we bridge the gap between ethical considerations and practical realities to make responsible, reliable systems? Exploring these questions, the book empowers humans to make AI design choices that allow them meaningful control over AI and the online sphere. Calling for an interdisciplinary approach toward human-misinformation algorithmic interaction that focuses on building methods and tools that robustly deal with complex psychological/social phenomena, the book offers a compelling insight into the future of AI-based society. Dr. Shin is a Chair and Professor at the College of Media and Communication at Texas Tech University. He was the founding Chair of the Department of Interaction Science, an industry-academia research initiative sponsored by Samsung and the Ministry of Education in Korea. He was awarded an Endowed Distinguished Professorship by the Ministry of Education in Korea and a SKK Endowed Chair (2010-2016). .

Note: Part I: The Cognitive Science of Misinformation: Why We Are Vulnerable and How Misinformation Beliefs Are Formed/Maintained -- 1 Introduction: The Diffusion of Misinformation -- 2 Misinformation and Bias -- 3 Misinformation and Radicalization -- Part II: How People View and Process Misinformation: How People Respond to Corrections of Misinformation -- 4 Misinformation, Paradox, and Heuristics -- 5 Misinformation Processing Model -- Part III: How to Combat Misinformation Online Amid Growing Concerns and Build Trust -- 6 Misinformation and Diversity -- 7 Misinformation and Nudge -- Part IV: What Are the Implications of AI for Misinformation? The Challenges and Opportunities When Misinformation Meets AI -- 8 Misinformation and Inoculation -- 9 Misinformation and ChatGPT -- 10 Conclusion: Misinformation and AI.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031525681

Additional Edition: Printed edition: ISBN 9783031525704

Additional Edition: Printed edition: ISBN 9783031525711

Language: English

DOI: 10.1007/978-3-031-52569-8

URL: https://doi.org/10.1007/978-3-031-52569-8

UID:

Format: 1 online resource (289 pages)

Edition: First edition.

ISBN: 3-031-52569-8

Note: Intro -- Acknowledgments -- Contents -- About the Editor -- List of Figures -- List of Tables -- Part I: The Cognitive Science of Misinformation: Why We Are Vulnerable, and How Misinformation Beliefs Are Formed/Maintained -- Chapter 1: Introduction: The Epistemology of Misinformation-How Do We Know What We Know -- Diffusion of Misinformation -- Misinformation on Misinformation: The Misinformation Paradox -- Normal People Like Us Fall for Misinformation -- Sticky Misinformation and Self-enforcing Beliefs -- How to Counter Misinformation and Fight Against Infodemics -- References -- Chapter 2: Misinformation and Algorithmic Bias -- Why Do People Fall for Misinformation? -- Why and How Misinformation Spread Online -- Why Is AI Vulnerable to Bias? -- Types of Algorithmic Bias -- Negative Feedback Loop and Bias -- Misinformation and AI: Inherent Biases -- Why Is the Human Role the Most Important in Misinformation? -- How to Stop the Spread of Misinformation -- Responsible AI -- Fairness and Transparency in Corporate Data Responsibility -- What Does Future Work on Misinformation Need to Consider? -- Human-Misinformation Interaction -- Can AI Stop Misinformation? -- Can AI Stop Fake News? -- References -- Chapter 3: Misinformation, Extremism, and Conspiracies: Amplification and Polarization by Algorithms -- Introduction: Why People Fall for Radicalization -- Literature Review: TikTok's Algorithm for Radicalization -- TikTok and For You Page: The Dark Side of the FYP -- The Growth of Radicalization Loops: Why People Fall into Extreme News -- The Loop Effect and TikTok -- Misinformation Spirals and Insular Social Groups -- Hypothesis and Research Questions -- Methods: Finding the Link Between Misinformation and Radicalization -- Longitudinal Methods -- Thematic Analysis -- How Algorithmic Recommendations Promote Radicalizations -- FYP and Radicalization. , Addictive Engagement -- Polarization Scores -- The Loop Effect -- Positive Feedback Loop -- Discussion: The Role of Misinformation in Fueling Extremism Online -- What Social Media Platforms Should Do About Radicalization -- Conclusion: Misinformation-Algorithmic Radicalization Nexus -- Limitations and Future Research -- References -- Part II: How People View and Process Misinformation: How People Respond to Corrections of Misinformation -- Chapter 4: Misinformation, Paradox, and Heuristics: An Algorithmic Nudge to Counter Misinformation -- Introduction: Understand the Human Psyche Behind Misinformation -- Literature Review: How Effective Are Accuracy Nudge Interventions for Misinformation? -- News Recommender Systems and Misinformation -- Nudging Away from Misinformation -- Research Questions -- Hypothesis Development -- Accuracy Nudge Effects: Nudges Away from Falsehood -- Algorithmic Source Effects: Algorithmic Sources Versus Legacy News Sources -- Trust Effects -- Methods -- Data Collection and Sample -- Procedures -- Stimuli -- Measures -- Analyses -- Discussion -- Algorithmic Source Effect -- Trust Moderation -- Implications -- Conclusion -- Appendix: Experimental Stimuli -- References -- Chapter 5: Misinformation Processing Model: How Users Process Misinformation When Using Recommender Algorithms -- Introduction -- Literature Review: Information Misbehavior -- Effects of Misinformation on User Behavior -- Heuristic-Systematic Misinformation Processing -- Research Questions -- Cognitive Account of Misinformation Evaluation -- Heuristic Processing -- Systematic Processing -- Moderating Effect of Explainability -- Methods -- Collection of Data and Samples -- Scales and Measurements -- Measurement Instrument -- Structural Model Testing -- Moderating Effects of Explainability -- Discussion: Algorithmic Misinformation. , Theoretical Implications: Algorithmic Effects on Misinformation -- Practical Implications -- Limitations and Future Research -- References -- Part III: How to Combat Misinformation Online Amid Growing Concerns and Build Trust -- Chapter 6: Misinformation and Diversity: Nudging Away from Misinformation Nudging Toward Diversity -- Diversity in AI -- Diversity-Aware AI -- Nudge Theory -- Literature Review -- Algorithmic Nudges and Behavior Modifications -- Nudging Toward Inclusion and News Diversity -- Hypothesis Development -- Nudges of Explainability and Humanness -- Nudging News Consumption Behavior with Anthropomorphic Cues -- Normative Belief and Trust -- The Personalization Paradox: Personalization and News Diversity -- Methods -- Scales and Measurements -- Results -- Structural Model Testing -- Discussion -- The Personalization Paradox -- Implications -- Diversity-Aware Recommendation Systems -- Conclusion -- Appendix -- References -- Chapter 7: Misinformation, Paradox, and Nudge: Combating Misinformation Through Nudging -- The Misinformation Paradox: Why Nudging Is Needed in Misinformation? -- Human Decision-Making and the Diffusion and Consumption of Misinformation -- Does Algorithmic Nudging Make a Better Judgment of Misinformation? -- Nudges and Algorithmic Affordance: From Black Box AI to Transparent Affordances -- Algorithmic Social Managing: Algorithmic Behavior Modification -- Concerns over Algorithm-Driven Nudges -- Algorithm Un-Nudge: Algorithm Aversion and Resistance to Algorithms -- Algorithm Nudges with Meaningful Control and Algorithm Audit -- References -- Part IV: What Are the Implications of AI for Misinformation? The Challenges and Opportunities When Misinformation Meets AI -- Chapter 8: Misinformation and Inoculation: Algorithmic Inoculation Against Misinformation Resistance -- Introduction. , Literature Review: Inoculating Misinformation -- Inoculation Theory -- HS Inoculation Processing -- Inoculation Messages Against Misinformation in AI Chatbots -- Research Questions: A Conceptual Characterization of Inoculation in AI -- Underlying the Cognitive Process of Inoculation -- Main Effects -- Heuristic Reasoning -- Affect Heuristics -- Fairness Heuristics -- Transparency Heuristics -- Systematic Processing -- Accuracy of Inoculation Messages -- Credibility of Inoculation Messages -- Cognitive Immunity: How Users Form Their Efficacy and Vaccination Belief -- Moderating Effects -- Message Type Effect: Forewarning Versus Refutational Preemption -- Algorithmic Source Effect: AI-Powered Chatbot Versus Legacy Sources -- Methods -- Experimental Design -- Manipulations -- Procedure -- All messages were inoculation information that comprised dual items, one forewarning paragraph and one pretreatment paragraph, except for the control group, which did not receive any inoculation message. The message information was presented on a single -- Scales and Measurements -- Measurement Instrument -- Fit Indices -- Analyses -- Discussion: How to Build Psychological Vaccines Against Misinformation -- Theoretical Implications: Inoculating Users Against Misinformation -- Practical Implications: Mental Antibodies -- Limitations and Suggestions for Future Research -- Conclusion -- References -- Chapter 9: Misinformation and Generative AI: How Users Construe Their Sense of Diagnostic Misinformation -- ChatGPT: The Illusion of Truth and the Dangers of Artificial Misinformation -- Literature Review: The Sensemaking of Generative Misinformation -- Heuristic-Systematic Misinformation Processing -- GenAI and Misinformation: Is ChatGPT a Misinformation Generator? -- Research Questions: A Conceptual Characterization of Generative Misinformation. , Underlying Cognitive Process of Misinformation Evaluation -- Heuristic Processing -- Fairness Heuristics -- Accountability Heuristics -- Transparency Heuristics -- Diagnosticity -- Systematic Processing -- Accuracy -- Credibility -- Explanatory Cues as an Intervention: Moderating Effect of Explainability -- Methods -- Collection of Data and Samples -- Data Analyses -- Scales and Measurements -- Measurement Instrument -- Fit Indices -- Structural Model Testing -- Neural Network Analysis -- The Impact of Explanatory Heuristics on Systematic Evaluation -- Discussion: Algorithmic Misinformation -- Theoretical Implications: Algorithmic Effects on Misinformation -- Practical Implications: Is GenAI Credible Chatbot or a Misinformation Generator? -- Limitations and Future Research -- References -- Chapter 10: Conclusion: Misinformation and AI-How Algorithms Generate and Manipulate Misinformation -- AI Makes Misinformation Much More Toxic -- Generate Adversarial Network: The Dawn of Artificial Misinformation -- Synthetic Media and Disinformation -- The Liar's Dividend and Deepfakes: Echoes of Fakes -- The Darker Side of Deepfakes -- Deepfake Research -- Implications and Recommendations -- Conclusion -- References -- Epilogue -- Index.

Additional Edition: ISBN 3-031-52568-X

Language: English