Coming November 2, 2026
Wiley Publishing
Data, AI, and Noise: The Search for Truth in Information and Algorithms examines how information authority, trust, and decision-making are being reshaped as we move away from traditional newsrooms, academic institutions, and vetted media sources toward AI and algorithm-driven information ecosystems.
Social media platforms that are infused with generative AI images and videos are a growing source of information. But what can we trust when there is an ungated amount of misinformation? The platforms we use daily can reach audiences at a scale far beyond traditional information sources and are optimized for engagement rather than accuracy or civic value. Trust is in peril.
Data professionals and industry leaders of corporate strategy, education, and public policy need to understand how AI is subtly influencing judgement, and increasingly displacing human accountability. Consumers need to be aware of how companies are using AI and the potential pitfalls in a largely unregulated AI world.
This book explores the implications of these shifts for governance, academic research, and organizational decision-making, and outlines why reinforcing transparency, information literacy, and human oversight has become a leadership imperative in the AI era.
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