Find truth in the noise of AI-driven misinformation and data deception Data, AI, and Noise: The Search for Truth in Information and Algorithms is a thought-provoking look at how generative AI and algorithmic platforms are shaping how we find, evaluate and ultimately trust information in the AI era. Written by Derek W. Gibson, former Executive Director, VP of Analytics at Wells Fargo and adjunct professor at Wake Forest University School of Business, this book draws on digital forensics, psychology, and organizational leadership to ask the hard questions about AI. Through real-life anecdotes, sharp analysis, and engaging storytelling, Gibson examines how AI technologies controlled by a small number of organizations shape individual decision-making and public perception. The book explores solutions for building a personal AI defense, covering techniques to evaluate information sources, identify deepfakes, recognize cognitive biases exploited by misinformation campaigns, and navigate with greater confidence in daily media consumption. Data, AI, and Noise is a call to action for data leaders, AI developers, Social Media platform strategists, policymakers, and anyone navigating a world where information authority has shifted from institutions to algorithms. The debate we are not having about the influence of AI inside organizations and across governments is one this book insists we start. Readers will explore: How recommendation algorithms are engines that create individualized realities optimized for engagement, not the truthStrategies to recognize and counter sophisticated misinformation from influencers, automated bots, and nation-state actorsAnalysis of how cognitive psychology principles explain vulnerability to misinformation and techniques to counteract biasReal-world examples showing how data professionals apply critical evaluation skills in workplace and personal contextsHow deepfakes and synthetic media are outpacing detection tools, and what the AI arms race means for trust and responsible AIWhy AI governance has become both a leadership and geopolitical question, not just a technical one and what coexistence actually means. Data, AI, and Noise serves data professionals, data scientists, business analysts, AI developers, corporate strategists, educators, and policymakers who need to understand not just how AI misinformation works, but also what responsible AI leadership now requires. It equips general readers and technology enthusiasts with structured methods for questioning AI-generated content, recognizing manipulation, and making better-informed decisions across their professional and personal lives.
