Uncovering the Impact of Noise on Human Decision-Making

kotani takaharu: 本の状態は説明通りでした。配達日も予定通りに届きました。

Japan on Oct 05, 2023

Cliente Amazon: From bias to different types of noise, this book lay down the knowledge required to understand decision-making errors and potential to become more accurate in all sort of domains.

Italy on Apr 18, 2023

Frank Calberg: Top takeaways from reading the book:
- Page 78: To reduce noise and improve judgment, get independent opinions from people with different views.
- Pages 78 and 222: To reduce noise and improve judgment, average all estimates you have.
- Page 119: People are likely to distrust algorithms and keep using their own judgment - even when that choice produces worse results.
- Page 123: Research by Philip Tetlock shows that long term predictions about specific events are impossible. The world is a messy place, where minor events can have large consequences.
- Page 178: Diversity of skills in a group of professionals is an asset because different professionals will cover different aspects of the problem and complement one another.
- Page 204: To reduce noise and improve judgment, use nudges. Example: In supermarkets, put healthy foods in prominent places.
- Pages 207 and 243: Checklists help reduce noise and improve decisions.
- Page 286: Algorithms can outperform human beings on whatever combination of criteria we select.
- Page 317: Because of their facelessness, algorithms may inspire distrust.

Germany on Mar 13, 2023

Uta C. Groeschel: Both biases and noise expose us to unequal treatment when equal treatment should be expected and are thus worth understanding. The book explains the concepts and the countermeasures. These include using AI and ways to make it unbiased - an important topic in 2022 and beyond!
Also: Anybody wanting to improve their understanding of the workings of statistics and the reliability of studies will get quite a lot of useful information.

Germany on Nov 17, 2022

brian doyle: Need a good level of statistics knowledge to understand the key points and follow the chapters

United Kingdom on Nov 07, 2022

Wally Bock: Noise: A Flaw in Human Judgment is an excellent book. But if you’re a reader of business books, Noise may not be the book for you. Most business books get right to practical applications of the author/s key ideas. This book does not. It’s an academic book with business applications. The big question is whether this book is worth your time as a business reader.

The first two thirds of the book set up the later chapters. The later chapters cover many specific techniques you can use to reduce noise and improve judgement and prediction. Don't jump right to them, though.  The early part of the book lays the necessary groundwork for you to understand why the techniques work. Later I’ll identify chapters with particular value for business readers.

Noise is about two things that affect our judgment. Bias is systematic deviation. Noise is random scatter. We need to understand both to improve judgment. Alas, most of the time noise hardly gets any consideration while bias is the star of the show. The authors wrote this book to “redress the balance.”

They say that the key theme of the book is: “wherever there is judgment there is noise --and more of it...

United States on Dec 14, 2021

Aran Joseph Canes: Daniel Kahneman always stresses the importance of priming: loosely, that we naturally allow the most recent experience to affect our judgment.

With that in mind, many readers come to Noise hoping for something of like importance to Thinking Fast and Slow. That work summarized decades of Nobel Prize winning research that showed how human beings use heuristics to reach decisions that run counter to what a statistical, or at least well thought out approach, would make.

Noise is not such a book. Most of the research are summaries of the work of other scientists, there is a lot of explanatory material that many readers will find redundant with their education and both wordiness and repeated material that should have been avoided.

Nevertheless, it is an important book. Noise shows in the real world the importance of the statistician’s distinction between bias and variance. A model can be inaccurate not only by being biased and consistent but also by providing widely varying answers around a true value.

While most people in research or the business world emphasize reducing bias, Kahneman and his co-authors emphasize the importance of reducing noise. Prison...

United States on May 19, 2021