データ、ＡＩ、ノイズ：情報とアルゴリズムの中で真実を求めて Data, AI, and Noise : The Search for Truth in Information and Algorithms

著者名：Gibson, Derek W.

Wiley（2026/09/15発売）

• 言語：ENG
• ISBN：9781394424337
• eISBN：9781394424344

Description

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 truth
• Strategies to recognize and counter sophisticated misinformation from influencers, automated bots, and nation-state actors
• Analysis of how cognitive psychology principles explain vulnerability to misinformation and techniques to counteract bias
• Real-world examples showing how data professionals apply critical evaluation skills in workplace and personal contexts
• How deepfakes and synthetic media are outpacing detection tools, and what the AI arms race means for trust and responsible AI
• Why 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.

Table of Contents

Introduction ix

1 The Information Apocalypse 1
The Media Landscape—Decades in Decline 1
Communicating the Wisdom of Others 2
Libraries as a Source of Truth 4
Newspapers in America 7
To the Moon 9
The Internet (Obviously) 11
Trusted Institutions 14
Influencers, Your New Neighbors 15
The Noise of the Infodemic 20

2 The Negotiated Truth 23
What the Newspapers Left Out 25
The Whole Story 27
When Truth Needs a Referee 29
What Is Truth? 31
Is the Moon Real? Is the Earth Flat? 33
To the Moon 36
A Simpler Explanation 38
Alternative Facts 40
Negotiating Truth 43

3 Open Your Eyes 47
If You Can Dream It. . . 47
Natural-Born Instincts 49
Picture This 53
I Do Recall 57
Noise and Judgment 62

4 Can a Computer Know Your Vulnerability? 67
Emotional Algorithms 67
Concern or Legitimate Risk? 68
Signals 70
Personalization Engines 72
Exploitation Mechanism 79
The Scale Problem Solved 82

5 When Certainty Fails 87
You Are Not Helpless, and Neither Is the Truth 87
Anchors in an Ocean 90
Embrace Uncertainty 91
Source over Content 93
Recognize the Noise 94
Identifying the Rush 95
Compensation and Incentives 98
A Different Kind of Journalist 101

6 Empowering You 107
The Verification Moment 107
AI vs. AI: The Technology Arms Race 108
How Detection Works 111
Five Stages 113
Steering the Algorithms 116
Early Morning 117

7 You Are the Target 121
The Digital Twin You Never Met 122
Finding Your Friends 123
Personalized Reality Machine 127
Invisible Feedback Loops 128
A Newsstand of Information 130
Data Ecosystem Beyond the Feed 131
A Different Worldview 134

8 Community and Collective Intelligence 139
Our Shared Reality 139
The Limits of Centralized Control 142
Promise and Hope in Crowdsourced Verification 147
When Collective Intelligence Fails 154

9 Global Scramble for AI Rules 159
The Brussels Effect 159
The Power of AI 160
Three Global Models, No Consensus 166
The Exploits of Regulation 170
Self-Regulation by Default 176

10 Living in the Noise 183
In the Room 183
This Is Not Normal 187
The Weight of It All 189
Truth, Eventually 192

Acknowledgments 197
About the Author 201
Index 203