Noise A Flaw in Human Judgment
by Cass R. Sunstein, Daniel Kahneman, Olivier Sibony
6.66 / 10 9.9K ratings
- Language
- English
- Published
- 2021
- Publisher
- Little, Brown Spark
- Pages
- 672
- ISBN
- 9780316322270
Subjects
- General
- Self-Help
- Health, Fitness & Dieting
- Management
- Science & Math
- Medical Books
- Mathematics
- Biological Sciences
- Biology
- Social Sciences
- Business & Economics
- Personal Growth
- Memory Improvement
- Psychology & Counseling
- Education
- Sociology
- Psychology
- Social Science
- Decision-Making & Problem Solving
- Research & Methodology
- Special Topics
- Cognitive Psychology & Cognition
- Cognitive Psychology
- Behavioral Sciences
- Social Psychology
- Motivational & Inspirational
- Applied Psychology
- Cognitive
- Strategic Planning
- Self-Management
- Cognitive Neuroscience & Cognitive Neuropsychology
- Decision making
- Social Theory
- Consumer Behavior
- Game Theory
Original edition
NoiseOriginally published in 2021 English Hachette
Other editions (16)
Listen to the summary Narrated summary
Imagine a world where the very same case, presented to different experts, yields wildly divergent outcomes. A patient with identical symptoms might receive one diagnosis from Dr. A and a completely different one from Dr. B. Two judges, reviewing the same crime and evidence, could hand down sentences that vary by years. An insurance underwriter might quote one premium, while a colleague, looking at the exact same risk profile, offers another. This pervasive, often invisible, inconsistency in human judgment is what lies at the heart of the matter: noise.
Noise is not the same as bias. Bias is a consistent deviation in judgment, a predictable lean in one direction, like a scale that always reads a few pounds heavy. Noise, however, is the unwanted variability, the scattershot of individual judgments around an average. It's the difference in readings when you step on the same scale multiple times, or the discrepancies between multiple scales. It manifests as both "within-person variability," where the same individual makes different judgments under slightly different circumstances, and "between-person variability," where different people judge the same situation differently. This randomness, often overlooked because it doesn't tell a neat story or isn't easily attributable to a single cause, significantly degrades the quality and fairness of decisions across countless domains.
The impact of this pervasive noise is far-reaching and often severe. In the judicial system, it can lead to gross injustices, with similar crimes receiving vastly different punishments depending on the specific judge assigned. In medicine, it can result in incorrect diagnoses or treatment plans, jeopardizing patient health. Businesses suffer economic costs from inconsistent performance evaluations, hiring decisions, and strategic choices. The unsettling truth is that wherever human judgment is involved, noise is present, and likely in greater measure than one might intuitively believe.
Part of the challenge in addressing noise is its elusive nature. We are often more attuned to detecting bias because it appears as a systematic error. Noise, being statistical and random, is harder to spot in individual instances; it only becomes visible when examining an ensemble of similar judgments. Furthermore, there's a natural human inclination to believe that others reason as we do, leading us to underestimate the extent of variability in judgment. We crave definitive answers and closure, often settling for convenient explanations that feel right, rather than confronting the messy reality of random error.
Recognizing the problem is the first step, but what can be done? The path to reducing noise lies in what is termed "decision hygiene." These are preventative strategies, much like washing hands to prevent the spread of germs, designed to bring more consistency to judgment processes. This can involve breaking down complex decisions into independent parts, using relative rather than absolute judgments, and aggregating multiple independent forecasts to average out individual errors. Structured approaches, such as the Mediating Assessment Protocol (MAP), guide decision-makers through a series of steps to ensure a more disciplined and uniform thought process.
While complete eradication of noise in human judgment may be impossible – as long as judgment is involved, some variability will remain – significant reduction is achievable. The goal isn't necessarily to eliminate human intuition, but to discipline and delay its influence until a thorough and diverse body of evidence has been carefully considered. Organizations, in particular, have a strong incentive to design decision-making processes that speak with "one voice," enhancing fairness, credibility, and accuracy. By making a conscious effort to identify and mitigate noise, we can foster a world where decisions are more consistent, equitable, and ultimately, better.
Noise is not the same as bias. Bias is a consistent deviation in judgment, a predictable lean in one direction, like a scale that always reads a few pounds heavy. Noise, however, is the unwanted variability, the scattershot of individual judgments around an average. It's the difference in readings when you step on the same scale multiple times, or the discrepancies between multiple scales. It manifests as both "within-person variability," where the same individual makes different judgments under slightly different circumstances, and "between-person variability," where different people judge the same situation differently. This randomness, often overlooked because it doesn't tell a neat story or isn't easily attributable to a single cause, significantly degrades the quality and fairness of decisions across countless domains.
The impact of this pervasive noise is far-reaching and often severe. In the judicial system, it can lead to gross injustices, with similar crimes receiving vastly different punishments depending on the specific judge assigned. In medicine, it can result in incorrect diagnoses or treatment plans, jeopardizing patient health. Businesses suffer economic costs from inconsistent performance evaluations, hiring decisions, and strategic choices. The unsettling truth is that wherever human judgment is involved, noise is present, and likely in greater measure than one might intuitively believe.
Part of the challenge in addressing noise is its elusive nature. We are often more attuned to detecting bias because it appears as a systematic error. Noise, being statistical and random, is harder to spot in individual instances; it only becomes visible when examining an ensemble of similar judgments. Furthermore, there's a natural human inclination to believe that others reason as we do, leading us to underestimate the extent of variability in judgment. We crave definitive answers and closure, often settling for convenient explanations that feel right, rather than confronting the messy reality of random error.
Recognizing the problem is the first step, but what can be done? The path to reducing noise lies in what is termed "decision hygiene." These are preventative strategies, much like washing hands to prevent the spread of germs, designed to bring more consistency to judgment processes. This can involve breaking down complex decisions into independent parts, using relative rather than absolute judgments, and aggregating multiple independent forecasts to average out individual errors. Structured approaches, such as the Mediating Assessment Protocol (MAP), guide decision-makers through a series of steps to ensure a more disciplined and uniform thought process.
While complete eradication of noise in human judgment may be impossible – as long as judgment is involved, some variability will remain – significant reduction is achievable. The goal isn't necessarily to eliminate human intuition, but to discipline and delay its influence until a thorough and diverse body of evidence has been carefully considered. Organizations, in particular, have a strong incentive to design decision-making processes that speak with "one voice," enhancing fairness, credibility, and accuracy. By making a conscious effort to identify and mitigate noise, we can foster a world where decisions are more consistent, equitable, and ultimately, better.
What other readers say
Liked
The book is widely praised for introducing and thoroughly exploring the concept of "noise" as a distinct flaw in human judgment, separate from bias. Readers appreciate its detailed examination of how unwanted variability affects decision-making across various professional domains, including medical diagnoses, legal sentencing, and hiring processes. Many reviewers found the practical strategies for identifying and reducing noise, such as decision hygiene and noise audits, to be valuable and thought-provoking. The systematic approach and numerous examples provided are considered insightful for understanding this often-unrecognized problem in judgment.
Disliked
However, a notable number of readers found the book to be overly repetitive and verbose, suggesting that its core arguments could have been presented more concisely. Some loyal followers of Daniel Kahneman's previous works, particularly "Thinking, Fast and Slow," expressed disappointment, feeling that "Noise" lacked the same groundbreaking originality, depth, or engaging writing style, and often reiterated concepts already covered elsewhere. Criticisms also include an inconsistent level of explanation, sometimes simplifying basic ideas excessively while introducing complex statistical tools without sufficient context, and a perceived overemphasis on algorithmic solutions without adequately addressing associated concerns.
In short
Overall, "Noise" offers a comprehensive investigation into the pervasive yet often-overlooked issue of inconsistency in human judgment. While some readers may find its extensive length and academic tone challenging, it provides valuable frameworks and practical insights for those seeking to improve decision accuracy and fairness. This book is best suited for professionals in fields that rely heavily on judgment, as well as readers new to the concept of noise and those interested in a detailed, systematic analysis of decision-making flaws within organizational and individual contexts.
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