Noise: The new book from the authors of ‘Thinking, Fast and Slow’ and ‘Nudge’ Paperback – 31 May 2022
- Choose from over 20,000 locations across the UK
- FREE unlimited deliveries at no additional cost for all customers
- Find your preferred location and add it to your address book
- Dispatch to this address when you check out
Enhance your purchase
THE INTERNATIONAL BESTSELLER
‘A monumental, gripping book … Outstanding’ SUNDAY TIMES
‘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.
We like to think we make decisions based on good reasoning – and that our doctors, judges, politicians, economic forecasters and employers do too. In this groundbreaking book, three world-leading behavioural scientists come together to assess the last great fault in our collective decision-making: noise.
We all make bad judgements more than we think. Noise shows us what we can do to make better ones.
Special offers and product promotions
- Buy at least 4 items of your choice and save 5%. Offered by Amazon.co.uk. Shop items
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 : William Collins; 1st edition (31 May 2022)
- Language : English
- Paperback : 464 pages
- ISBN-10 : 0008309035
- ISBN-13 : 978-0008309039
- Dimensions : 12.9 x 2.9 x 19.8 cm
- Best Sellers Rank: 775 in Books (See Top 100 in Books)
- Customer reviews:
About the authors
Reviewed in the United Kingdom on 14 October 2021
Reviews with images
Top reviews from United Kingdom
There was a problem filtering reviews right now. Please try again later.
This book does him no favours, and I'm absolutely gobsmacked so many "illustrious" authors and writers have gushed forth with praise for this book.
As another reviewer pointed out, noise is just a manifestation of variance...without "noise", we wouldn't have arguments on many ways of approaching a problem, which is hugely valuable in understanding and solving the problem. Without "noise", we would all think the same way, approach every problem the same way, and would be no better than robots. The fact that there are many people who have very different impressions about this very book is an example of the "noise" the authors talk about - if we all thought the same, we would all love or hate this book. Without noise, there would be no nuance, and that would be sooooo very boring!
The way they mostly define noise is the AGGREGATION of individual biases (though in some cases, individual variation in decision making - e.g. more leniency after lunch, birthdays, etc) are a problem, though the evidence for this has not been replicated (a MAJOR problem in the field of psychology research).
Overall, I feel the authors have banked on their reputations to sell this not very persuasive and badly argued book. I'd wager that if this book was published by an unknown author, this book and its arguments would be widely panned!!
By all means read it, but do not be influenced by the celebrity status of the authors.
As for me, I'm happy to contribute to the "noise" by giving this book just 1 star....
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.
At the same time, they bring into the discussion some serious tools you won’t even meet until you get to graduate school in statistics, like the “percentage concordant,” which is not some type of supersonic airplane, but a rank correlation type of measure, and even provide a mini-table to move you from percentage concordant (PC) to correlation. The table, by the way, is bogus in the absence of context, as percentage concordant is a construct that I’m willing to bet relies heavily on assumptions that go unmentioned here.
The chapters end with summaries, which was OK for Thinking Fast and Slow, but a bit of an insult when the subject matter is so plain.
The style is pompous and paternalistic.
System A and System B are parachuted in, but (i) they’re barely explained (ii) that’s a theory to explain bias rather than noise (and invite a celebrity author to the proceedings)
Most annoyingly, terribly little ground is covered in this weighty tome. Gun to my head, I could probably get it all down to one page. Let me try:
1. Noise is just as bad as bias in terms of messing up your results
2. A good way to measure how bad your results are is the mean square error
3. Composition of Mean Square Error:
• Mean square error is made up of Bias and Noise
• Noise is made up of Level Noise and Pattern Noise
• Pattern Noise is made up of Stable Pattern Noise and Occasion Noise
• Level Noise is the kind of noise that comes from the fact that some judges are harsh and some are lenient, so two guys who did the same crime could get very different punishment.
• Pattern Noise is the kind of noise that comes from the fact that a judge may have a daughter, making him less harsh on young women that remind him of his daughter. He could be a harsh judge who is less harsh on young women who remind him of his daughter; or he could be a lenient judge who is extra lenient on young women who remind him of his daughter.
• Occasion Noise is the kind of noise that comes from the fact that judges are harsher right before lunch. Same judge, same crime, same perpetrator, different outcome, because it was a different occasion
4. If you ask people to measure something independently from one another, the more the merrier; but if they talk to each other first, then they will amplify errors for a variety of reasons that lead to groupthink
5. Machines beat people when it comes to cutting noise
6. In the quest to limit noise, people can fight back by sticking to simple rules
7. We humans like to build stories after the fact to explain what happened; they’re usually bogus: statistical explanations beat causal explanations
8. Bias can be the source of noise: inconsistency in bias is noise
9. Noise can arise when you’re told to rank things on a scale; to cut noise, it’s better to go ordinal than cardinal
10. To improve judgements you need (i) better judges (ii) a decision process that aggregates in a way that maintains independence among the judges (iii) guidelines (iv) relative rather than absolute judgements
11. There is a place for intuition: it’s got to be brought in at the very end, after all the mechanical work has finished
12. There actually is a place for noise: when people are bound to game the system
Read something else!