Other Sellers on Amazon
Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet or computer – no Kindle device required. Learn more
Read instantly on your browser with Kindle Cloud Reader.
Using your mobile phone camera, scan the code below and download the Kindle app.
Enter your mobile phone or email address
By pressing ‘Send link’, you agree to Amazon's Conditions of Use.
You consent to receive an automated text message from or on behalf of Amazon about the Kindle App at your mobile number above. Consent is not a condition of any purchase. Message and data rates may apply.
Noise: The new book from the authors of ‘Thinking, Fast and Slow’ and ‘Nudge’ Paperback – 19 May 2021
Enhance your purchase
‘A monumental, gripping book … Outstanding’ Sunday Times
Wherever there is human judgement, there is noise.
‘Noise may be the most important book I've read in more than a decade. A genuinely new idea so exceedingly important you will immediately put it into practice. A masterpiece’
Angela Duckworth, author of Grit
‘An absolutely brilliant investigation of a massive societal problem that has been hiding in plain sight’
Steven Levitt, co-author of Freakonomics
From the world-leaders in strategic thinking and the multi-million copy bestselling authors of Thinking Fast and Slow and Nudge, the next big book to change the way you think.
Imagine that two doctors in the same city give different diagnoses to identical patients – or that two judges in the same court give different sentences to people who have committed matching crimes. Now imagine that the same doctor and the same judge make different decisions depending on whether it is morning or afternoon, or Monday rather than Wednesday, or they haven’t yet had lunch. These are examples of noise: variability in judgements that should be identical.
In Noise, Daniel Kahneman, Olivier Sibony and Cass R. Sunstein show how noise produces errors in many fields, including in medicine, law, public health, economic forecasting, forensic science, child protection, creative strategy, performance review and hiring. And although noise can be found wherever people are making judgements and decisions, individuals and organizations alike commonly ignore its impact, at great cost.
Packed with new ideas, and drawing on the same kind of sharp analysis and breadth of case study that made Thinking, Fast and Slow and Nudge international bestsellers, Noise explains how and why humans are so susceptible to noise and bias in decision-making. We all make bad judgements more than we think. With a few simple remedies, this groundbreaking book explores what we can do to make better ones.
Frequently bought together
The Sunday Times bestseller (May 2021)
‘A tour de force of scholarship and clear writing’
New York Times
‘This is a monumental, gripping book. It is also bracing … The three authors have transformed the way we think about the world. They have looked beneath and beyond the way we make decisions and organise our lives. A follow-up of sorts to Thinking, Fast and Slow, it is a further step down the road towards a more complex and realistic grasp of human affairs that is replacing the crude simplifications of the recent past. Outstanding’
‘As you’d expect from its authors, it is a rigorous approach to an important topic… There’s lots to surprise and entertain. Anyone who has found the literature on cognitive biases important will find this a valuable addition to their knowledge’ Danny Finkelstein, The Times
‘Noise is everywhere and is seriously disruptive. The authors have come up with a bold solution. The book is a satisfying journey through a big but not unsolvable problem, with plenty of fascinating case studies along the way. Humans are often bad at making decisions. But we can get better’
Martha Gill, Evening Standard
‘The greatest source of ineffective policies are often not biases, corruption or ill-will, but three “I”: Intuition, Ignorance and Inertia. This book masterfully demonstrates why the three “I” are so pervasive, and what we can do to fight them. An essential, eye opening read’
Esther Duflo, winner of a 2019 Nobel Prize
‘In Noise, the authors brilliantly apply their unique and novel insights into the flaws in human judgment to every sphere of human endeavour… Noise is a masterful achievement and a landmark in the field of psychology’
Philip E. Tetlock, co-author of Superforecasting
‘An electrifying exploration of the human mind, this book will permanently change the way we think about the scale and scope of bias’
The new book from the authors of ‘Thinking, Fast and Slow’ and ‘Nudge’
- Publisher : HarperCollins GB (19 May 2021)
- Language : English
- Paperback : 464 pages
- ISBN-10 : 0008309000
- ISBN-13 : 978-0008309008
- Dimensions : 15.3 x 3.6 x 23.4 cm
- Best Sellers Rank: 312 in Books (See Top 100 in Books)
- Customer Reviews:
About the author
Review this product
Top reviews from Australia
There was a problem filtering reviews right now. Please try again later.
As others have said, it's verbose. It starts by drawing a distinction between noise and bias, then continues with nearly 400 pages on noise. It would have been a better book if it included both noise and bias in that number of pages.
Top reviews from other countries
And so to Noise, a book, we are told that is designed to offer suggestions for the improvement of human judgement. As for Noise itself we are told in the book that that noise is about statistical thinking. We are also told that noise is a distinct source of error and that "the scatter in the forecasts is noise" and, that whenever we observe noise we should work to reduce it. However, we are also told that noise is invisible and embarrassing.
Noise occurs because people are idiosyncratic; they inhabit different psychological spaces; their moods are triggered by a unique set of contexts - they see and respond to the evidence in different ways. Not to mention their unconscious response to particular cues. (In many respects - seemingly the same things that trigger biases, and we are told rather confusingly that "psychological biases create system noise when many people differ in their biases.") We enter a convoluted vortex - biases cause noise - where there is noise (invisible) there will surely also be more biases at work - the two, it seems, exist in relationship that is characterised by their mutual and continuous interruption of each other. And there is actually no clear sense given as to how one should go about unpicking them.
Surprise surprise the authors pay passing homage to prediction markets, of which they say; "much of the time prediction markets have been found to do very well.") Prediction markets, in the wild (outisde of organisations) have not actually performed very well at all - because they lack insiders and do nothing more than aggregate noise. Their record on political events over the past ten years has been terrible (In the recent Chesham and Amersham By-Election in the UK, for example, the Tories were trading at 1.17 on the Betfair Betting Exchange as Polls opened - they lost). A better example, in the context of noise would have been horse racing betting markets - which contain lots of noise and bias, but which display a consistent ability to be predictive - because of the presence of insiders, who cancel out the noise.
Sadly it seems that we have gone back twenty years, to the notion of the jar of sweets and the benefits of aggregating independent judgements. In a nutshell, this book is about 380 pages too long.
Consider that the following studies listed in the Notes to the Introduction all used p-values:
(2) Child Protection and Child Outcomes: Measuring the Effects of Foster Care
(4) Refugee Roulette: Disparities in Asylum Adjudication
In Chapter 1:
(14) A Survey(!!!) of 47 Judges (dated 1977) (Survey vs. Random Control Study)
(16) Extraneous Factors in Judicial Decisions cites a p-value <.0001 on page 5
... and similar p-value references associated with judges' differential and variance in sentencing: related to food breaks, nearby NFL Team winning recently, birthdays, outside air temperature. IMHO, the identification of these explanatory factors based on p-values are bogus and illustrative of John Ioannidis' 2005 paper: Why Most Published Research Findings Are False.
It is disconcerting that these scholar authors utilize many questionable references to architect a thesis about what is more commonly known as variance. As the normal Gaussian distribution is ubiquitous, one should not be startled that selected ranges within it vary significantly.
Given the presence of uncertainty and the idiosyncracy and variability of individual experience, human judgments will vary. Human judgment is noisy! DUH !!!
The authors have failed their scholarship and profession.
The basic premise seems to be that decisions have noise in them (duh) and its important to understand that we should evaluate the decision making process and not just the outcome. Accuracy, Precision, and Bias are terms familiar to anyone with a basic understanding of statistics; for others, a couple of early examples focusing on shooting targets easily educates the three terms and their differences. The authors keep on stating the same concepts in a number of ways for the first 5-6 chapters. And very often, simple observations are turned to very dense phrases without really serving any purpose than trying to sound very academic or scholarly. (For example, "..what they are trying to achieve is, regardless of verifiability, is the internal signal of completion provided by the coherence between the facts of the case and the judgement. And what they should be trying to achieve...is the judgement process that would provide the best judgement over an ensemble of similar cases") . Then the authors spend a chapter or two differentiating "predictive" and "evaluative" judgements only to conclude that the difference is "fuzzy" (genius observation) and a decision will usually require both.
If you are able to grind your way through the first 3 Parts (12 chapters), you will be able to pick up some new insights in Part IV and V that discuss on how variability/noise occurs and their various sources. Conducting a "noise audit" and what constitutes decision "hygiene" are sections worth reading for those whose roles require constant synthesis of inputs from various experts/sources/stakeholders etc.
Overall, the unnecessarily dense style that overcomplicates a simple message, lack of a clear target audience, and a narrative arc that just takes too long to provide new insights or provocative thoughts, makes this a fairly dull read.