I'm writing this on the night of the release day. Amazon dropped off the book; I dropped everything and started reading. I will update this review after consequent readings of the book – this review is based on a careful reading of the first two parts, the conclusion, and a speed reading of the rest of the book. I do not hesitate to assign the book five stars already at this point and can't see docking any stars later on. This is a landmark book.
Instead of listing the contents of the book here (use the "Look inside" feature instead!), I'll summarize my immediate takeaways after spending a few hours with the book.
It is clear that Kahneman is looking at the problem space through a different lens than his magnum opus, "Thinking, Fast and Slow," which undoubtfully is also due to the influence of his co-authors. To emphasize this, the book is consistently narrated in the second person plural.
A major early concern is distinguishing noise from bias – the latter having been the star of the show in most popular psychology literature, including the aforementioned book. The focus in "Noise" is societal, statistical, instead of the causal stories of individual biases, which we prefer as explanations in our primarily individualistic Western cultures.
The first pages open with a delightfully insightful example of how to understand the difference between noise and bias (see the attached photos) that is immediately clear. The distinction is important, as is the realization that noise should be addressed first before bias is. Even if we don't know if we're aiming at the right thing, we need to narrow down the scatter pattern first. Counterintuitive perhaps but true: this strategy gives us a faster, more accurate way of actually hitting our target once the adjustments are made.
"Noise is the unwarranted variability of judgments, and there is too much of it." Kahneman, Sibony, and Sunstein are sounding an alarm. Noise is so pervasive that it is difficult to spot. We've learned to live with it, too much, and it is costing us and our institutions dearly. Noise is too often thought of as random errors that will cancel each other out, but that is not helpful. Indeed, it is a societal problem: if one judge over-sentences and another is overly lenient, there is no "averaging out" – there is human tragedy and failure of justice. To drive this point home, the book serves well-sourced and engaging narrative examples from criminal law, medicine, prediction, recruiting, forensic science, financial forecasting, patent law, education, insurance sales, and many more fields.
This is not a book to take lightly, though it is an easy read thanks to its excellent structure and perfectly balanced prose. I can only wish it will be read extremely widely, and its findings and recommendations will be rapidly put into use.
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Reviews with images
"Noise" is the society-level sequel to the individual-focused "Thinking, Fast and Slow"
I'm writing this on the night of the release day. Amazon dropped off the book; I dropped everything and started reading. I will update this review after consequent readings of the book – this review is based on a careful reading of the first two parts, the conclusion, and a speed reading of the rest of the book. I do not hesitate to assign the book five stars already at this point and can't see docking any stars later on. This is a landmark book.Instead of listing the contents of the book here (use the "Look inside" feature instead!), I'll summarize my immediate takeaways after spending a few hours with the book.It is clear that Kahneman is looking at the problem space through a different lens than his magnum opus, "Thinking, Fast and Slow," which undoubtfully is also due to the influence of his co-authors. To emphasize this, the book is consistently narrated in the second person plural.A major early concern is distinguishing noise from bias – the latter having been the star of the show in most popular psychology literature, including the aforementioned book. The focus in "Noise" is societal, statistical, instead of the causal stories of individual biases, which we prefer as explanations in our primarily individualistic Western cultures.The first pages open with a delightfully insightful example of how to understand the difference between noise and bias (see the attached photos) that is immediately clear. The distinction is important, as is the realization that noise should be addressed first before bias is. Even if we don't know if we're aiming at the right thing, we need to narrow down the scatter pattern first. Counterintuitive perhaps but true: this strategy gives us a faster, more accurate way of actually hitting our target once the adjustments are made."Noise is the unwarranted variability of judgments, and there is too much of it." Kahneman, Sibony, and Sunstein are sounding an alarm. Noise is so pervasive that it is difficult to spot. We've learned to live with it, too much, and it is costing us and our institutions dearly. Noise is too often thought of as random errors that will cancel each other out, but that is not helpful. Indeed, it is a societal problem: if one judge over-sentences and another is overly lenient, there is no "averaging out" – there is human tragedy and failure of justice. To drive this point home, the book serves well-sourced and engaging narrative examples from criminal law, medicine, prediction, recruiting, forensic science, financial forecasting, patent law, education, insurance sales, and many more fields.This is not a book to take lightly, though it is an easy read thanks to its excellent structure and perfectly balanced prose. I can only wish it will be read extremely widely, and its findings and recommendations will be rapidly put into use.
Top reviews from the United States
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Reviewed in the United States on May 19, 2021
Instead of listing the contents of the book here (use the "Look inside" feature instead!), I'll summarize my immediate takeaways after spending a few hours with the book.
It is clear that Kahneman is looking at the problem space through a different lens than his magnum opus, "Thinking, Fast and Slow," which undoubtfully is also due to the influence of his co-authors. To emphasize this, the book is consistently narrated in the second person plural.
A major early concern is distinguishing noise from bias – the latter having been the star of the show in most popular psychology literature, including the aforementioned book. The focus in "Noise" is societal, statistical, instead of the causal stories of individual biases, which we prefer as explanations in our primarily individualistic Western cultures.
The first pages open with a delightfully insightful example of how to understand the difference between noise and bias (see the attached photos) that is immediately clear. The distinction is important, as is the realization that noise should be addressed first before bias is. Even if we don't know if we're aiming at the right thing, we need to narrow down the scatter pattern first. Counterintuitive perhaps but true: this strategy gives us a faster, more accurate way of actually hitting our target once the adjustments are made.
"Noise is the unwarranted variability of judgments, and there is too much of it." Kahneman, Sibony, and Sunstein are sounding an alarm. Noise is so pervasive that it is difficult to spot. We've learned to live with it, too much, and it is costing us and our institutions dearly. Noise is too often thought of as random errors that will cancel each other out, but that is not helpful. Indeed, it is a societal problem: if one judge over-sentences and another is overly lenient, there is no "averaging out" – there is human tragedy and failure of justice. To drive this point home, the book serves well-sourced and engaging narrative examples from criminal law, medicine, prediction, recruiting, forensic science, financial forecasting, patent law, education, insurance sales, and many more fields.
This is not a book to take lightly, though it is an easy read thanks to its excellent structure and perfectly balanced prose. I can only wish it will be read extremely widely, and its findings and recommendations will be rapidly put into use.
"Noise" is the society-level sequel to the individual-focused "Thinking, Fast and Slow"
Reviewed in the United States on May 19, 2021
I'm writing this on the night of the release day. Amazon dropped off the book; I dropped everything and started reading. I will update this review after consequent readings of the book – this review is based on a careful reading of the first two parts, the conclusion, and a speed reading of the rest of the book. I do not hesitate to assign the book five stars already at this point and can't see docking any stars later on. This is a landmark book.Reviewed in the United States on May 19, 2021
Instead of listing the contents of the book here (use the "Look inside" feature instead!), I'll summarize my immediate takeaways after spending a few hours with the book.
It is clear that Kahneman is looking at the problem space through a different lens than his magnum opus, "Thinking, Fast and Slow," which undoubtfully is also due to the influence of his co-authors. To emphasize this, the book is consistently narrated in the second person plural.
A major early concern is distinguishing noise from bias – the latter having been the star of the show in most popular psychology literature, including the aforementioned book. The focus in "Noise" is societal, statistical, instead of the causal stories of individual biases, which we prefer as explanations in our primarily individualistic Western cultures.
The first pages open with a delightfully insightful example of how to understand the difference between noise and bias (see the attached photos) that is immediately clear. The distinction is important, as is the realization that noise should be addressed first before bias is. Even if we don't know if we're aiming at the right thing, we need to narrow down the scatter pattern first. Counterintuitive perhaps but true: this strategy gives us a faster, more accurate way of actually hitting our target once the adjustments are made.
"Noise is the unwarranted variability of judgments, and there is too much of it." Kahneman, Sibony, and Sunstein are sounding an alarm. Noise is so pervasive that it is difficult to spot. We've learned to live with it, too much, and it is costing us and our institutions dearly. Noise is too often thought of as random errors that will cancel each other out, but that is not helpful. Indeed, it is a societal problem: if one judge over-sentences and another is overly lenient, there is no "averaging out" – there is human tragedy and failure of justice. To drive this point home, the book serves well-sourced and engaging narrative examples from criminal law, medicine, prediction, recruiting, forensic science, financial forecasting, patent law, education, insurance sales, and many more fields.
This is not a book to take lightly, though it is an easy read thanks to its excellent structure and perfectly balanced prose. I can only wish it will be read extremely widely, and its findings and recommendations will be rapidly put into use.
Images in this review
Reviewed in the United States on May 19, 2021
Top reviews from other countries
Amazon Customer
Amazingly detailed and insightful, as expected !
Reviewed in India on June 13, 2024