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Noise: The new book from the authors of…
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Noise: The new book from the authors of ‘Thinking, Fast and Slow’ and ‘Nudge’ (edition 2021)

by Daniel Kahneman (Author), Olivier Sibony (Author), Cass R. Sunstein (Author)

MembersReviewsPopularityAverage ratingMentions
1,0371819,623 (3.56)7
I actually liked this book. Useful framework for noise expressed as essentially variance components. Clearly and with great variety, established the significance of the subject. Offered ideas to address the concerns. Then with an openness uncharacteristic of books that propose solutions, sought to address the tradeoff and weakness with their own proposal. Not an attack on other ideas to be found. ( )
  boeintuy2 | Apr 20, 2022 |
Showing 18 of 18
An important subject but poorly written book, bad organisation, lacking depth of analisys in key experiments, lacking in take away general specific knowledge. The authors are working on something important but it is not yet integrated and experimental evidence is not presented in a convincing way.
( )
  yates9 | Feb 28, 2024 |
I found the first 200 pages of this book to be almost impenetrable and frequently forgot a sentence shortly after reading it.

That said, the book and its import improve.

If you’ve read Kahneman’s earlier work, Thinking Fast and Slow, you’ll be familiar with the use of a core metaphor to the argument. While the book says it’s about “Noise” it’s really about the statistical sources of bad judgments.

Noise is the shorthand systems engineers use to explain flaws in the system.

Kahneman et al want us to take a systems view of bad judgments, and bad judges. There is hope for them yet.

Forestalling judgment until the evidence is collected, breaking down complex judgments to their constituent parts, employing baseline comparisons, and employing objective referees will all yield better judgments in business, in law and medicine, and in life.

I certainly hope so. I have trouble just dealing with the volume of judgments I am called upon to make everyday in business.

There is a lot here to think about, especially about the people who are the experts we rely upon, and how they frequently get important things wrong. ( )
  MylesKesten | Jan 23, 2024 |
Educational but not particularly enjoyable to read ( )
  danielskatz | Dec 26, 2023 |
Focuses specifically on system noise (which is different from cognitive biases). With implications on decision-making and all types of human judgments and systems. You'll learn:
• What is system noise and how it affects all types of decisions, from personal to professional judgments, individual to group decisions, and private sector to public sector;
• The difference between noise and bias, the components of system noise, how to evaluate the quality of judgments and measure noise;
• A range of strategies for reducing noise, including: how to do noise audits, find good judges, use de-biasing, and adopt various preventive decision hygiene strategies;
• Problems and limits to noise reduction, and how we can consider the “right” level of noise to accept.

Book summary at: https://readingraphics.com/book-summary-noise/ ( )
  AngelaLamHF | Jul 29, 2023 |
Yet another pop science book where economists try to convince you that they came up with a basic concept. This time: statistical variation. ( )
  HundredFlowersBloom | Jan 27, 2023 |
This book is excellent. Much like Kahneman’s* definitive book on bias, Thinking Fast and Slow, Noise provides an excellent, fairly comprehensive treatment of another source of error in human judgement, which the authors define as noise. Noise is, as a term in this book, used to describe inconsistency in human judgment, as opposed to bias, which is a systematic departure from “correct” results. There is some overlap in terms here, as, for example, hungry judges systematically make harsher decisions, which is referred to as bias in Thinking Fast and Slow, but because we’re looking at error across the entire range of outcomes in a different way here, is called occasion noise. I do not believe this detracts from what the book brings to the table, but it’s worth noting that in this book, bias is used to refer to the difference between the average outcome and the “correct” outcome, or other errors across the range of outcomes such as minorities being treated differently in cases where there isn’t a “correct” outcome to measure.

What this book does not do is claim that all noise should be completely eliminated. Eliminating noise has costs. However, a wide disparity of outcomes in similar cases can be extremely unfair. Should two people with similar histories and mitigating/aggravating factors have several years of difference in sentencing for the same crime? Should the luck of who evaluates your insurance policy or what mood they’re in when they do make hundreds of dollars in difference to your premiums or policy payouts? Certain types of judgements are judgements where inconsistency is inherently unfair.

Noise looks at these judgements. It looks at hiring decisions where projection is inherently difficult and outcomes are hard to evaluate. It looks at expert judgement in fields like forensics where experts are asked to make evaluations of objective facts and whether there is noise in those outcomes as well.


I feel like I should be writing many more paragraphs about this book, but for now I’ll leave it here. This book is held to a high standard of rigor and is evidence backed throughout, again in line with Kahneman’s Thinking, Fast and Slow. The two books combine to provide an extreme amount of information on how to improve your judgement as an individual or an organization. I highly recommend this book and it will be very close to the top of my list of “must read” books on intelligence and the human brain.



*There are three authors here and I don’t wish to downplay any role of Cass Sunstein or Oliver Sibony, which I am obviously not in position to evaluate. This book has led me to investigate their other work and likely will result in me reading at least one from each. However, Kahneman is the most well known partly because he’s one of the most influential figures in the field of human judgement, widely cited by psychologists and behavioral economists, and Thinking Fast and Slow is in my opinion is probably the best book on the brain everyone should read. ( )
  jdm9970 | Jan 26, 2023 |
Important stuff for people trying to understand decision-making flaws in large organizations. But overly long and a bit repetitive too. My main gripe is that it focused on problems for a handful of types of decision-makers, such a judges, doctors, insurers, Human Resources staff. Those are important people that do things that affect all of us, but it wasn’t made clear to me if the concepts in this book really apply to most people in every day situations.

I think it was interesting in the sections where they contrast noise (sorta-random mistakes in decision-making) and bias (more predictable mistakes). ( )
  steve02476 | Jan 3, 2023 |
Bias, clustered outcomes centered away from the "target", are commonly understood if not always corrected when people make judgements. Here, noise, outcomes scattered around a target are analyzed, and several common types are identified. Why humans are bad at identifying noise is also discussed. The running examples, insurance underwriting, judicial sentencing, performance evaluation, and hiring decisions are interesting. (The Google analysis showing interview results were uncorrelated with subsequent job performance was cited). ( )
  Castinet | Dec 11, 2022 |
Gets very technical but it is interesting. Didn’t finish. The book discusses the MANY variables made in decision-making and it’s implications within our society. Need to finish! ( )
  creighley | Apr 27, 2022 |
I actually liked this book. Useful framework for noise expressed as essentially variance components. Clearly and with great variety, established the significance of the subject. Offered ideas to address the concerns. Then with an openness uncharacteristic of books that propose solutions, sought to address the tradeoff and weakness with their own proposal. Not an attack on other ideas to be found. ( )
  boeintuy2 | Apr 20, 2022 |
'Thinking, Fast and Slow' vond ik een zeer interessant boek dat toeliet/toelaat je eigen denken, al naargelang de situatie, beter te begrijpen. Het is verre van lichte kost, ook al is het boek geschreven voor een breed publiek.

'Noise' ofwel de Nederlandstalige versie, 'Ruis', sprak me in eerste instantie ook aan, alleen al omwille van het thema. Dit keer wou ik de vertaalde versie lezen, ook omdat ik maar weinig (te weinig wellicht) in het Nederlands lees.

Het zijn drukke tijden en dan kun je niet alle dagen even geconcentreerd zijn (ruis?). Na enkele tientallen bladzijden moet ik echter bekennen dat het boek dan toch niet bevat wat ik dacht dat het zou bevatten. Men beroept zich vooral (afgaande op wat ik gelezen en bij het bladeren gezien heb) op statistiek en de studies die andere onderzoekers uitgevoerd hebben. Het is bijgevolg niet zo toegankelijk qua inhoud.

Ook de vertaling leek me redelijk stroef. Wellicht omdat deze zeer dicht bij de Engelstalige versie moest aanleunen? Het leest niet echt vlot, vind ik. Dit gezegd zijnde, wil ik het werk van de vertalers (Lidwien Biekmann en Koos Mebius) zeker niet afbreken. Het was wellicht geen makkelijke klus.

Lang verhaal kort: Dit boek is, zoals het nu is, niet aan mij besteed. Wel onthoud ik dat er bij alle beoordelingen (op het werk, in de vrije tijd, ...) ruis en bias aanwezig zijn en dat het belangrijk en nuttig is om dit te beseffen en na te gaan hoe/waar dit zoveel mogelijk te beperken. ( )
  TechThing | Feb 28, 2022 |
As someone who enjoyed Kahneman’s “Thinking Fast and Slow” so much that I integrated some of the fascinating insights into my college-level communications course, I was eagerly looking forward to reading his new work. I was profoundly disappointed. One candid reviewer describes the book as a “rough slog.” The reviewer was being kind. In all honesty, I recall some sessions in my high school algebra class as more lively and engaging. It’s not like I didn’t give Kahneman’s latest work a genuine try. I read about a third of this dense work before calling it quits. I assign it 2 stars because I did glean several nuggets that shed light on decision-making and fuzzy judgements. ( )
  brianinbuffalo | Jan 29, 2022 |
Prof. Kahneman's explanations of the flaws in decision making in Thinking Fast and Slow are popular and well-regarded. In this work, the authors explain the statistics of departures from the normal decisions make on certain facts. The variability of "judgment" by trusted experts - bail pending criminal trial, insurance premiums, medical diagnosis - has consequences. The authors correcty point out that variability conceals personal animosity, discriminary motives, personal quirks and faulty thought processes. They favour decisions based on rules to judgment. They flirt with automated decision making, challenging some of the critics of digital solutionism. Automated decision making fascinates big business for the potential of resolving problems without expensive and complicated human intervention. ( )
  BraveKelso | Dec 14, 2021 |
The authors comprise a distinguished group: Kahneman is an Israeli psychologist and economist notable for his work on the psychology of judgment and decision-making, as well as behavioral economics, for which he was awarded the 2002 Nobel Memorial Prize in Economic Sciences. Sibony is Professor of Strategy at HEC Paris, an Associate Fellow of Saïd Business School in Oxford University, and has taught at London Business School, Ecole Polytechnique, ENA, IE Madrid, and other institutions. Sunstein is currently the Robert Walmsley University Professor at Harvard, and is the founder and director of the Program on Behavioral Economics and Public Policy at Harvard Law School. In 2018, he received the Holberg Prize from the government of Norway, sometimes described as the equivalent of the Nobel Prize for law and the humanities.

The authors seek to illuminate the real nature of decision-making, focusing on the pervasive persistence of “noise” and how it affects what we believe and what we decide. What is this noise and what is its source? Noise, the authors state, “is the unwanted variability of judgments, and there is too much of it.” What motivated them to write the book, they explain in the conclusion, is “the sheer magnitude of system nose and the amount of damage it does.”

Noise come about from a looseness of standards that allow for unintended variables to affect outcomes. Think of judges for example, who can base punishment on a number of situations that are specified, but also have latitude. Thus, if the judge is in a bad mood, or tired, or subject to prejudices that might be unconscious, the judge is apt to rule differently than if those conditions do not apply. A similar situation obtains with doctors making diagnoses, with noise also coming from what array of symptoms they were, or were not, exposed to in medical school. The result of this noise is an array of decisions affected by random variations rather than fair, consistent, and predictable outcomes.

The authors suggest conducting a “noise audit” to check for variation in decisions across similar and even identical circumstances. They then suggest ways to combat this noise that is inevitably discovered.

One technique is to have multiple persons involved in reaching decisions. Another is to establish guidelines and constraints that limit intuition, idiosyncratic preferences, and cognitive biases. Exercises with decision makers evaluating decisions made by others can help expose noise and make those participating in the exercise more aware of it in their own behavior.

Overall, I found this book both moderately entertaining and ultimately depressing. With noise being not only bruited but valued by one half of American society, reason is increasingly taking a back seat. It doesn’t seem likely that “exercises” are likely to remedy the problem of massive misinformation and its astonishing influence. ( )
  nbmars | Sep 25, 2021 |
Noise is a masterful deconstruction of the components of error in our human judgment process, followed by plenty of practical advice about how to minimize it rationally. Among my favorite take-aways: a simple model often beats complex weightings (in a sense, because of noise), social perceptions can be substantially wrong when initial early signs cascade into bigger impacts, and one helpful solution is having a deliberate process that includes various ways of thinking and re-thinking. ( )
  jpsnow | Aug 26, 2021 |
When similar decisions have different outcomes that is seen as noise. The interesting question is whether there is nose in the right answer or if it really makes sense to think in terms of a right answer. Heisenberg's uncertainty principle States there are limits to accuracy with which certain physical properties of matter can be known. Perhaps both the uncertainty of the future and or incomplete knowledge of the present make noise in decisions inevitable. The book is very thought provoking and examines ways to improve the judgement process. ( )
1 vote waldhaus1 | Jul 29, 2021 |
The problem of noise is very much worth raising and this is a fair analysis of it but the way it's presented oversteps approachable straight into simplified and patronising. It's clearly written for the busy executive. It even has recaps and readymade soundbites you can repeat to your underlings and fellow board members at the end of each chapter. ( )
  Paul_S | Jul 24, 2021 |
The sheer variety of ways judgment can be clouded is mind-boggling. The more closely we examine judgments, the more noise turns up as a factor. In Noise, an A-list team of celebrity psych stars, Daniel Kahneman, Olivier Sibony and Cass Sunstein pull together their confrères and evidence from the usual innumerable studies to delineate how bad it really is.

Noise, at least in psychology, is “unwanted variability”. In practical terms, that means even the most focused person might be swayed by unnoticed noise. Noise can be the home team losing the night before, lunch coming up in half an hour, miserable weather, a toothache – pretty much anything that has nothing to do with the issue at hand. This is all in addition to personal prejudices and the framework of bureaucratic rules that are always in play, restricting the range of possible decisions, and misdirecting them where they should not be going.

All kinds of studies show that trial judges are inconsistent when not totally wrong. The authors say two judges viewing the same evidence in the same case will come to two completely different decisions. So will the same judge given the same case on two different occasions. Sentencing is all over the place, which has led to enforced sentencing guidelines that often make things worse. It has also led to judge-shopping, as the decision patterns of judges builds up over the years. This is not based on evidence or argument, but in which way the judge’s decisions can be erroneous. Think political parties, religion, and stubborn pig-headedness.

The same goes for mere mortals, like supervisors. They all believe they do a creditable job, but the stats show the direct opposite. Even simple linear models do a far better job in every case. Not just sometimes – every time, according to Noise. Even randomly generated models do a far more accurate job of judging people correctly than people do. Artificial intelligence algorithms can also add a little more accuracy, though surprisingly, not significantly so. But people on their own perform miserably.

Still, no one, but no one, would trust a simple model to make a decision on their future; they feel better having personally tried with another human, regardless of the facts. It immediately reminded me of Lake Wobegon, where all the kids are above average. Doesn’t work like that. In the authors’ words, “Models of reality, of a judge or randomly generated models all perform better than nuanced, intuitive, insightful and experienced humans.” To which I would add: anyone who claims they can accurately size up a person on meeting them, can’t.

Errors occur far more frequently than people realize, because everyone trusts their own judgment foremost, and far too often, the judgment of others (their lawyers, doctors and managers, for example).

The worst example of this occurs in job interviews and performance appraisals. Everyone knows the single worst way to make a hire is through a personal, unstructured interview. Yet managers still insist on interviews, and so do candidates, thinking they can master the battle and win the job if they can simply deal with someone in person. Both are totally wrong, yet nonetheless, they both persist. Job interviews have become a nightmare for candidates, going back multiple times for essentially no good reason, as the more people interview them, the more inaccurate their ultimate decision will be.

As for quarterly, semi-annual and annual performance appraisals, those who have to work with the results know they are usually totally worthless. Managers burdened with multiple reports grind them out against a deadline, having little or nothing to do with an individual’s performance. Most everyone is “satisfactory”, especially when managers are required to rate them on a scale. No decisions can validly be taken from these exercises in frustration, but they are taken anyway. And while essentially no one in any organization likes or ever looks forward to the whole process, the noise persists, clouding futures.

Scales themselves are useless, as the authors show in examples such as for astronauts. A bell-curve distribution would show one or two excellent performers, one or two total failures, and most in the middle. But there are no total failures among astronauts. The yearslong training requires and ensures it. So grading on a scale against a bell-curve can be just more noise.

For the open-minded, Noise provides details, tips and tricks to leverage. For example, deliberation, the vaunted value of teams, actually increases the noise around a decision. The mere fact that team members discuss their reasoning before they make a decision increases the noise for everyone participating. The key to making teams work, ironically, is for everyone to do their own research in isolation, and once they have all come to a decision, they can then compare with others on the team.

They call this independent work “decision hygiene”. It cuts down noise in general, but no one can know what specifically, or by how much. The authors liken it to handwashing- no one knows what germs were there to kill. All they know is that handwashing kills germs, and that you can never get rid of all of them.

The authors show that noise occurs in almost any shape or form. The quality of the paper used for a business plan, and the font it is presented in, can tip the success or failure of a proposal in the hands of potential investors.

Another interesting noise source is called whitecoat syndrome. This is noise some people generate going to see a doctor, nurse or lab technician. Their blood pressure rises in anticipation, sometimes causing an erroneous diagnosis.

Things like prejudice are not so much noise as bias. When assessing decisions that go wrong, noise is the standard deviation of errors, while bias is the mean itself. The book is a thorough attempt to make a science of noise and errors in judgment.

Bias is a likely driver of noise. But the book is all about separating the two. It shows that biases, such as “planning fallacy, loss aversion, overconfidence, the endowment effect, status quo bias, excessive discounting of the future, and various biases against various categories of people” are all factors in erroneous decisions. But despite all this, sheer noise outweighs bias heavily.

They use Gaussian mean squared errors to demonstrate the effect of both bias and noise, with noise the clear winner, and dramatically so. Squaring the errors makes them visually arresting, But they still need to be stopped - somehow.

It transpires that errors do not cancel each other out, either. Instead, they add up, taking decisionmakers farther away from the right decision. And with the book piling on a seemingly infinite selection of noise factors and sources, it’s a wonder Man has made it even this far.

Speaking of erroneous judgments, it is difficult to decide what kind of book Noise is. It is steeped in psychology, but it is not a groundbreaking new discipline. People and firms have been actively trying to filter out noise since forever (the better ones, anyway). Nor is it a psych textbook, really, though there are exercises the reader can use right while poring over it. I think it is closer to a handbook of what to be aware of: forewarned is forearmed sort of thing. Though clearly, mere knowledge of the situation is far from enough to counteract it. The book includes how-tos like implementing an audit to identify and isolate noise, so the book definitely has practical applications. Handbook it is, then.

This noise thing is ego-deflating for all humans, who run their lives continually making decisions, not only on facts, but predictive judgments as well (Predictions provide an “illusion of validity”). That we are not equipped to pull this off successfully – at all – should cause a total rethink of where we go from here. Noise is pernicious. Trusting models looms heavily over us all.

David Wineberg ( )
6 vote DavidWineberg | Apr 14, 2021 |
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