Superforecasting: The Art and Science of Prediction by Philip Tetlock and Dan Gardner is a book that explores the methods and techniques used by individuals who excel at making accurate predictions. The authors conducted a study in which they asked individuals to predict the outcome of a variety of events, and found that some individuals consistently performed better than others. These individuals, who the authors call “superforecasters,” have specific characteristics and habits that enable them to make more accurate predictions.
The book is divided into three main sections. The first section provides an overview of forecasting and the study conducted by the authors. The second section delves into the characteristics and habits of superforecasters, while the third section focuses on how to become a better forecaster.
In the first section, the authors explain the concept of forecasting and how it is used in a variety of fields, such as politics, finance, and weather prediction. They also introduce the concept of the “fox” and the “hedgehog.” The fox is someone who is curious and open-minded, and who is willing to consider a variety of perspectives. The hedgehog, on the other hand, has a single, strong belief or theory that they use to interpret the world. The authors argue that superforecasters are more like foxes than hedgehogs.
The authors then describe the study they conducted, which involved asking individuals to predict the outcomes of a variety of events over a period of several years. The events included political elections, economic trends, and geopolitical conflicts. The authors found that some individuals consistently performed better than others, and that these individuals had certain characteristics and habits in common.
In the second section, the authors describe the characteristics and habits of superforecasters. These include being intellectually curious, having a growth mindset, being comfortable with probability and uncertainty, being able to break down complex problems into smaller parts, and being able to update their beliefs based on new information. The authors also discuss the importance of teamwork and diversity of perspectives in forecasting.
The authors then describe the techniques used by superforecasters. These include using base rates (historical data) to inform predictions, using multiple models and considering multiple scenarios, avoiding overconfidence and hindsight bias, and using external sources to gather information.
In the third section, the authors provide advice on how to become a better forecaster. They suggest practicing active open-mindedness, which involves being willing to consider alternative viewpoints and to revise your beliefs based on new information. They also suggest developing a “fermi estimate,” which involves making rough, ballpark estimates of quantities that are difficult to measure precisely. Additionally, they suggest practicing “counterfactual thinking,” which involves imagining different scenarios and outcomes.
The authors conclude the book superforecasting by emphasizing the importance of humility and recognizing the limits of our knowledge. They argue that while forecasting is an important tool, it is not a crystal ball, and that we must always be open to the possibility of being wrong.
Overall, Superforecasting is an insightful and engaging book that provides a wealth of information on the art and science of prediction. The authors’ approach is grounded in data and research, but is also practical and accessible. Whether you are a professional forecaster or simply interested in improving your ability to make predictions, this book is an excellent resource.