Noise audiobook cover - A Flaw in Human Judgment

Noise

A Flaw in Human Judgment

Daniel Kahneman, Olivier Sibony and Cass R. Sunstein

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Quiz — Test Your Understanding

Question 1 of 8
According to the text, what is 'occasion noise'?
  • A. When a system produces scattershot, inconsistent judgments across different experts.
  • B. When a person repeatedly confronts substantially the same situation yet makes different judgments due to irrelevant factors.
  • C. When cognitive mechanisms skew our judgments toward a desired outcome.
  • D. When algorithms fail to predict future outcomes because of incomplete data.
Question 2 of 8
How does the book distinguish between 'noise' and 'bias' using the analogy of a shooting arcade?
  • A. Bias is a scattershot pattern of misses, while noise is a cluster of shots consistently off the bullseye.
  • B. Bias only affects human judgments, while noise only affects algorithmic predictions.
  • C. Bias is a systematic deviation in one direction, while noise consists of random, scattershot errors.
  • D. Bias is caused by external factors like weather, while noise is caused by internal cognitive prejudices.
Question 3 of 8
Why do rudimentary algorithms often outperform human experts in making predictions, such as setting bail?
  • A. Algorithms have access to complete information about the future, eliminating objective ignorance.
  • B. Algorithms are immune to system bias and can understand human narratives better than judges.
  • C. Algorithms are free from emotional rewards, internal signals, and perceptions that cause noise in human judgment.
  • D. Algorithms automatically adjust their predictions based on the daily weather and other environmental factors.
Question 4 of 8
Why is 'noise' often ignored or unnoticed by people compared to 'bias'?
  • A. Noise resists narrative and lacks causal force, making it difficult for the story-seeking human mind to grasp.
  • B. Noise only occurs in highly complex systems, whereas bias happens in everyday life.
  • C. Noise has a much smaller financial and social impact than bias.
  • D. Noise is easily corrected by individual experts without the need for systemic changes.
Question 5 of 8
Which of the following is a crucial caveat for the 'wisdom-of-crowds' effect to successfully reduce noise?
  • A. The individuals in the crowd must discuss the problem together before making a judgment.
  • B. The crowd must be asked different, related questions to cover all angles of the problem.
  • C. The judgments must be completely independent, and the crowd must not share a systematic bias.
  • D. The crowd must consist of experts who have formal training in statistical analysis.
Question 6 of 8
What is the primary purpose of conducting a 'noise audit' in an institution?
  • A. To identify and fire the lowest-performing employees.
  • B. To make the random variability in expert judgments visible and quantifiable.
  • C. To replace human judges and executives with rudimentary algorithms.
  • D. To prove that bias is the sole cause of unjust decisions in a system.
Question 7 of 8
What does the concept of taking the 'outside view' in decision hygiene entail?
  • A. Trusting your intuition and gut feelings about a specific case.
  • B. Hiring an external consultant to make the final decision.
  • C. Framing a case in reference to a statistical body of other, similar cases.
  • D. Focusing deeply on the unique narrative and specific details of the individual case.
Question 8 of 8
Why did the noise reduction achieved by the Sentencing Reform Act ultimately fail to stick in the long run?
  • A. The algorithms used to calculate sentences were found to be highly biased against minorities.
  • B. The judges did not buy into the system because they believed the goal of judgment should allow for personal discretion rather than rigid accuracy.
  • C. Congress realized the act was too expensive to maintain and repealed it.
  • D. The rules created a 'three strikes' system that led to an unacceptable rise in crime rates.

Noise — Full Chapter Overview

Noise Summary & Overview

Noise (2021) is an exploration into the chaotic and costly role that randomness plays in human judgment. By uncovering the mechanisms behind how our minds and societies work, the authors show how noise – unwanted variability in decisions – is both inescapable and elusive. We can, however, with a few solid strategies, make our judgments less noisy and our world fairer.

Who Should Listen to Noise?

  • Behavioral economists, psychologists, CEOs, and students
  • Anyone interested in how we make judgments and how those judgments shape society
  • Anyone who cares about accuracy and fairness

About the Author: Daniel Kahneman, Olivier Sibony and Cass R. Sunstein

Daniel Kahneman is an economist and psychologist and the author of the groundbreaking Thinking, Fast and Slow. Kahneman’s work earned him a Nobel Prize in Economics in 2002 and the Presidential Medal of Freedom in 2013. He’s currently a professor emeritus at Princeton University.

Cass R. Sunstein is a legal scholar and the author and coauthor of several books including Nudge which he coauthored with Richard Thaler. Sunstein served as a top administrator in the Obama White House and is the founder and director of the Program on Behavioral Economics and Public Policy at Harvard University.

Olivier Sibony is a fellow at Oxford University, a former senior partner at McKinsey & Company, and the author of You’re About to Make a Terrible Mistake!

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