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by Robin Sharma
A Flaw in Human Judgment
Noise by Daniel Kahneman, Cass R. Sunstein, and Olivier Sibony is a groundbreaking exploration of how random noise in decision-making processes can cause errors, waste resources, and undermine performance in every industry.
To get a better grasp on the random and strange nature of the kind of noise we’re talking about here, let’s imagine you’re a high school senior, and you and your best friend are self-professed academic nerds. You’ve both earned straight As, nailed the SATs, and landed admissions interviews at the same Ivy League university.
You go to your interview and everything goes swimmingly. Your high marks impress the admissions officer and you cross the campus back to your car feeling great, the sun on your face and a cool breeze at your back.
Your friend has her appointment with the same admissions officer on the following day. Just like for you, her interview is a smooth ride. But when she leaves, the rain clouds that have gathered all afternoon break open into a downpour.
Weeks pass, and you each receive a letter from the admissions office. Turns out, they’ve rejected you but accepted your friend. Your mind reels. Why? What does she have that you don’t?
Here’s the first key message: Unrelated and unpredictable factors can have an alarming impact on human judgment.
According to a 2003 paper evocatively titled “Clouds Make Nerds Look Good” by behavioral scientist Uri Simonsohn, the weather might have made the difference. Simonsohn discovered that on cloudier days, college admissions officers pay more attention to grades and scores.
On sunnier days, on the other hand, admissions officers are more sensitive to nonacademic qualities, meaning that on the day of your interview, the officer might have been more interested in athletics and artistic talent than straight As and SAT scores.
Then again, perhaps the admissions officer’s decision had nothing to do with the weather at all, and more to do with the interviewees that preceded you. Perhaps those students were great candidates, and the admission officer just didn’t want to go on an acceptance streak.
But wait. Other irrelevant factors may also have influenced the decision. The admissions officer might have been hungry; he may have felt that sunny day was too hot, despite the air conditioning in the office; his hometown football team might have just lost an important game. Researchers have shown that each of these irrelevant factors can affect the decisions of bank loan officers, baseball umpires, physicians, and judges.
Importantly, in all of these scenarios, one person repeatedly confronts substantially the same situation, yet makes different judgments. Researchers call this variability occasion noise, and it’s one of the major categories of noise. But it’s not the only one.
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.
Noise (2021) explores the pervasive problem of noise and its impact on our decision-making processes. Here's why this book is worth reading:
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Try Blinkist to get the key ideas from 7,500+ bestselling nonfiction titles and podcasts. Listen or read in just 15 minutes.
Start your free trialBlink 3 of 8 - The 5 AM Club
by Robin Sharma
What is the main message of Noise?
The main message of Noise is that random factors can heavily influence decision-making and lead to errors and biases.
How long does it take to read Noise?
Reading Noise takes several hours. Reading the Blinkist summary takes just a few minutes.
Is Noise a good book? Is it worth reading?
Noise is worth reading because it sheds light on the impact of noise in decision-making and offers practical solutions. It's a valuable book for everyone.
Who is the author of Noise?
The authors of Noise are Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein.