Gary Smith

Gary Smith is a professor of economics at Pomona College and an author known for his work analyzing statistical errors, data misuse, and artificial intelligence limitations. His research and writing focus on exposing flawed data analysis in academic research and popular media. Smith has written several books examining how statistics can be misinterpreted or manipulated, including "Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics" and "The AI Delusion." His work emphasizes the importance of human judgment and critical thinking when evaluating statistical claims and artificial intelligence capabilities. As a frequent contributor to academic journals and media outlets, Smith has written extensively about statistical and mathematical misconceptions in fields ranging from sports analytics to financial markets. His writing style combines technical expertise with accessible explanations aimed at helping general readers understand complex statistical concepts. Smith holds a Ph.D. in Economics from Yale University and has taught at Pomona College since 1981, where he has served as chair of the Department of Economics. His research has been cited in numerous academic publications and media sources including The Wall Street Journal, The New York Times, and The Economist.

Readers appreciate Smith's ability to explain complex statistical concepts in clear, understandable terms. Many note his use of relevant examples from sports, finance, and everyday life to illustrate statistical fallacies. Multiple Amazon reviewers highlight his measured approach to AI criticism, avoiding both alarmism and excessive optimism. Readers specifically value: - Real-world applications of statistical principles - Clear explanations of technical concepts - Balance between depth and accessibility - Practical advice for evaluating data claims Common criticisms: - Some sections become repetitive - Examples occasionally oversimplified - Technical readers want more mathematical detail - Writing style can be dry Ratings across platforms: Amazon: "Standard Deviations" 4.3/5 (180 reviews) "The AI Delusion" 4.4/5 (165 reviews) Goodreads: "Standard Deviations" 3.8/5 (450 ratings) "The AI Delusion" 3.9/5 (380 ratings) One frequent Amazon reviewer comment: "Smith helps readers develop critical thinking skills about statistics without requiring advanced math knowledge."

Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics An examination of how statistics can be misused to draw false conclusions in business, academia, and everyday life.

What the Luck? The Surprising Role of Chance in Our Everyday Lives An analysis of how randomness and probability affect outcomes in sports, investing, and personal decisions.

The AI Delusion A critical assessment of artificial intelligence's capabilities and limitations, exploring common misconceptions about machine learning.

Money Machine: The Surprisingly Simple Power of Value Investing An explanation of value investing principles and methods for evaluating company fundamentals.

The Phantom Pattern Problem: The Mirage of Big Data An investigation into how the human tendency to see patterns can lead to false conclusions when analyzing large datasets.

Numbers and The Making of Us: Counting and the Course of Human Cultures A study of how number systems developed across different civilizations and their impact on human progress.

The Warren Buffett Problem: When Good Companies Turn Bad An analysis of investment failures and the challenges of maintaining successful long-term investment strategies.

Distrust: Big Data, Data-Torturing, and the Assault on Science An examination of how data manipulation and misinterpretation can undermine scientific research and public trust.

Daniel Kahneman writes about cognitive biases and decision-making errors, similar to Smith's focus on statistical mistakes and faulty reasoning. His work bridges psychology and economics while examining how humans make choices under uncertainty.

Nassim Nicholas Taleb analyzes randomness, probability and human error in financial markets and everyday life. His books challenge conventional wisdom about risk and uncertainty, paralleling Smith's scrutiny of flawed statistical thinking.

Philip Tetlock researches forecasting, judgment and decision making through empirical studies. He examines why experts make prediction errors and how to improve forecasting accuracy, themes that align with Smith's analysis of statistical misuse.

Charles Wheelan explains statistics and data analysis for general audiences with real-world examples. He focuses on common mathematical misconceptions and proper interpretation of numbers, similar to Smith's approach to statistical literacy.

Tim Harford writes about economics and statistics through case studies and real-world applications. His work examines how data and numbers can be misused or misinterpreted in business and policy decisions.