Noise, by Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein, is about how to improve the judgments that affect some of the most important aspects of our lives, including our justice system, medical care, education, and business decisions. As the title suggests, the book focuses on noise, which the authors define as unexpected and unwanted variance in human judgments. The authors argue that if we can understand what noise is, then we can reduce it—and thereby drastically reduce unfairness, loss of money, and even loss of life.
Noise draws on the authors’ expertise across multiple fields. Kahneman is a Nobel...
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Before we can tackle the problem of noise, we have to understand what noise is, where it comes from, and why it’s a problem worth solving. This section begins by looking at how noise introduces error into judgments and how these errors lead to unfairness, financial loss, and physical harm. Then, we’ll look at how noise arises as a result of the way our minds work.
The authors define noise as one of the two main errors in human judgment (the other being bias). To understand noise, we must first define judgment.
A judgment is an attempt to mentally assign a value to something in order to choose a course of action. The authors break judgments down into predictions and evaluations.
Predictions aim to come as close as possible to some correct value or answer. The authors point out that insurance underwriters make predictions when they prepare quotes, and they’re aiming at a theoretical goldilocks number (just right). If the premium is too low, the company loses money. If the premium is too high, the company loses customers. (Shortform note: A similar predictive calculation comes into play in any field that, like insurance,...
Now that we understand what noise is and where it comes from, we can look at steps to reduce or eliminate noise from judgments. The authors of Noise offer a few solutions, including mechanical judgment tools (models and algorithms) that can replace or augment human judgment as well as a set of suggestions for reducing noise in human decision making.
Typically, the first step in reducing noise is figuring out how much noise there is in the first place. This step is necessary because administrators tend to believe that their organizations make judgments consistently, and until they can see the problem firsthand, they may be resistant to change.
To determine how much noise is present in a company, organization, or system, the authors outline a noise audit process they use when consulting with businesses. The book includes an appendix with detailed guidelines for conducting a noise audit. The general gist is that an organization would give a set of sample cases to all of its members whose job it is to make judgments about such cases. For example, an insurance company would give a set of sample claims to all of its adjusters. The...
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We’re all affected by the judgment errors that noise leads to. These errors can reduce the quality and consistency of our legal system, educational institutions, workplaces, and more.
Think of a time you relied on a judgment made by an institution of some sort. Describe the situation. What was the context? What was the judgment?
Let’s explore how you might apply the ideas in Noise to improve the quality of your judgments.
Think of a situation where you make judgments with important stakes. Maybe it’s your job to make professional judgments. If not, you might think of a major personal decision involving a prediction or an evaluation, like how to invest your money, or where to live. Describe the judgment and its context.
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