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From the Nobel Prize-winning author of Thinking, Fast and Slow and the coauthor of Nudge, a revolutionary exploration of why people make bad judgments and how to make better ones—"a tour de force” (New York Times).
Imagine that two doctors in the same city give different diagnoses to identical patients—or that two judges in the same courthouse give markedly different sentences to people who have committed the same crime. Suppose that different interviewers at the same firm make different decisions about indistinguishable job applicants—or that when a company is handling customer complaints, the resolution depends on who happens to answer the phone. Now imagine that the same doctor, the same judge, the same interviewer, or the same customer service agent makes different decisions depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical.
In Noise, Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein show the detrimental effects of noise in many fields, including medicine, law, economic forecasting, forensic science, bail, child protection, strategy, performance reviews, and personnel selection. Wherever there is judgment, there is noise. Yet, most of the time, individuals and organizations alike are unaware of it. They neglect noise. With a few simple remedies, people can reduce both noise and bias, and so make far better decisions.
Packed with original ideas, and offering the same kinds of research-based insights that made Thinking, Fast and Slow and Nudge groundbreaking New York Times bestsellers, Noise explains how and why humans are so susceptible to noise in judgment—and what we can do about it.
Psychology professor Kahneman (Thinking, Fast and Slow), business professor Sibony (You're About to Make a Terrible Mistake!), and legal scholar Sunstein (Too Much Information) team up for this fascinating exploration of the bias and "noise" that cause errors in human judgment. Noise, they write, is "variability in judgments that should be identical" that, when combined with one's own biases conscious or not can cause human error. The authors offer no shortage of noise-reduction strategies: "decision hygiene," for example, involves sequencing information to cut back on the possibility of confirmation bias, a technique used in forensic science analyses, where examiners get "only the information they need when they need it." The authors also suggest breaking down complex decisions into "multiple fact-based assessments"; avoiding group discussions, which increase noise, instead collecting individual opinions beforehand; and appointing a "decision observer" to identify bias. Though the writing can be jargon-heavy, readers will find plenty of insight and useful exercises. The result is dense and complex, but those who stay the course will be rewarded with an intricate examination of decision-making and sound judgment.