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Full Description
The rapid advancement of Generative AI (GenAI) is revolutionizing and transforming a wide range of fields, with a notable impact on digital media and information dissemination. Digital platforms, including social media networks, have already grappled with the widespread proliferation of fake news at an increasing intensity are now facing an even bigger threat from machine-generated and machine-boosted fake news. With the increasing growth and sophistication of GenAI models for malicious ends, fake news is spreading rapidly, finding a fertile ground in digital media for largely unchecked dissemination of incorrect and misleading information. The scalability and diversity of current and emerging GenAI techniques present both opportunities and challenges in the field of fake news. On one hand, the ability to create highly realistic and persuasive content in large quantities with minimal effort, in real-time, makes GenAI a potent tool for spreading fake news and misinformation. On the other hand, those same capabilities can be harnessed to employ GenAI models to detect fake news and therefore hinder the spread. In this context, this book examines how GenAI techniques are contributing to combat fake news in digital media. A particular major challenge in combating fake news with GenAI is the explainability of the models: why a specific piece of news is determined to be fake or genuine. Tracing the origins of a specific piece of generated content—whether it stems from accurate or misleading data—requires extracting, interpreting, and representing in a legible manner vast parameter spaces and training data sources. This complexity of GenAI explainability makes it difficult to hold creators of fake news accountable and to ensure transparency in the content creation process. In this book, the authors focus on the positive potential of Generative AI and provide an overview of how it can be leveraged to combat fake news across diverse digital media platforms.
The book is structured around the following key topics:
• An overview of Generative AI and its relationship with fake news
• How Generative AI can be utilized to fight the spread of fake news
• Ensuring that the news we encounter on digital media platforms are not misleading or false
• Methods for verifying the authenticity of news sources and tracing the origins of information to ensure its credibility
• Practical insights into technological advancements and solutions related to the detection and analysis of fake news.
Finally, this book serves as a platform for the community to share innovative research on the use of Generative AI in detecting and mitigating the impact of false information across digital platforms. Readers will explore how Generative AI can revolutionize fact-checking, automate the identification of misleading content, and provide adaptive solutions to prevent the spread of fake news.
Contents
Part I. Misinformation in the Age of GenAI: State-of-the-Art. Chapter 1 Social Awareness, Disinformation, and Reputational Management in the Age of Artificial Intelligence. Chapter 2 Aligning Generative AI with Educational Values: An Ethical Response to Digital Misinformation. Part II. Large Language Models (LLMS) for Misinformation Detection. Chapter 3 AI-Driven Threats and Countermeasures: Securing the Information Space Against Synthetic Media and Deepfakes. Chapter 4 Zero Trust Architectures and Cybersecurity Frameworks for Mitigating AI-Enabled Misinformation Campaigns. Chapter 5 Decentralizing Truth: A Blockchain-Based Framework for Trustworthy Information in the GenAI Era. Chapter 6 An AI-Augmented Human-in-the-Loop (HITL) Approach for Misinformation Prevention in the Digital Age. Part III. Case Studies and Practical Solutions. Chapter 7 Factors Influencing Misinformation in the Context of GenAI: The Case of Vietnam. Chapter 8 Analysis for Usage of ChatGPT by Students in Academic Contexts. Chapter 9 Mapping the Economics of Water Misinformation in the Generative AI-Driven Era: Modeling Insights on Education, Policy, and Smart Detection. Chapter 10 Quantifying the Economic Implications of AI-Driven Misinformation: Evidence from ESG, Global Trade, Logistics, Education, and Innovation for Sustainable Development. Part IV. Ethical Challenges and Future Trends. Chapter 11 Role of Data Protection Law in Combating Generative AI Misinformation: A Visible Threat to Privacy. Chapter 12 Emerging Trends and Challenges in Generative Artificial Intelligence (GenAI) and Misinformation: HR Perspectives. Chapter 13 Future Trends in AI-Driven Misinformation Detection and Prevention.
