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hughesie5's review
challenging
informative
reflective
slow-paced
1.75
This book was quite insightful and I’m glad I read it, but I did got bogged down in a bit of statistical jargon at times and some of it became repetitive in the middle. Overall, I liked the overall argument and conclusion presented and can think of lots of practical ways to reflect on and apply it to my own life, especially in an educational setting.
nekomancer42's review
1.0
This is one of the worst popular press social sciences books I've ever read, and I've read many. It gets a lot wrong about what we know regarding decision-making and basic statistics. While it's true that algorithms are highly useful when applied appropriately, this book massively overstates the case in their favor while neglecting important counterpoints, among other serious problems. Kahneman's "Thinking, Fast and Slow" remains one of my favorite books on research in psychology and this is an extremely disappointing step down. I recommend skipping "Noise" entirely and looking elsewhere if you're interested in the subjects it touches on. Want a book on statistics? Try "Naked Statistics" by Charles Wheelan. Interested in decision-making? "Thinking, Fast and Slow" is still good, but skip the chapter of priming (it doesn't hold up). "Thinking in Bets" is decent as well. Want critical thinking with a healthy dose of data interpretation? "Calling Bullshit: The Art of Skepticism in a Data-Driven World" is pretty good. Just, whatever you do, skip "Noise" and spend your time elsewhere.
rick2's review
1.0
You know what the real lesson here is, don’t pre-order books based on the authors reputation alone. In a world filled with noise, these authors contribute to it through their generally inadequate book.
I really wanted to like this. I liked Nudge which has Cass as an author, I generally liked Thinking Fast and Slow, and I want someone who’s not Nate Silver explain signal to noise ratios to help me curate better information in my life. But this book isn’t it. This book is literally noise. Worthless noise in an already noisy world.
Someone like Kahneman, a founder of behavioral economics, you would think would have interesting new research and considered takes on how to cut through the amount of chatter out there in the world. It’s an important problem. But it seems like behavioral economics has stalled out into finding goofy and minor errors in our cognitive biases. Hey look! two people came to different answers when asked to mentally calculate an abstract concept. Look at how I can create methodologically dubious and unreplicatible studies that confuse people into making decisions against their best interests. Am I a behavioral economist yet?
I’m so sick of people writing shitty books to promote themselves as “thought leaders” and charge more for their consulting. I expected a better book out of these authors but found myself extremely disappointed in the shallowness of the ideas and writing. It’s a bad regurgitation of ideas that has been done better in other places.
If you like feeling cocktail-party smart without actually having to put in the effort to be smart, you will probably like this. It’s full of pithy blurbs. (Judges are impacted by whether or not their favorite football team won the night before.) Memorize a few and you’ll impress your wife’s-bosses-cousin in no time. Freakonomics did it better. But the fundamental problem is that this book doesn’t say anything that hasn’t been beaten to death before.
Essentially decisions come down to judgments and judgments can be skewed through bias and noise. Noise = randomness except it’s a lot harder to charge six figure consulting fees when you say “oh jeez, there’s just a lot of randomness all up in here.” Much sexier to call it a “noise audit” and point to your crappy book as a guide. People may not be great predictors but we sure are predictably gullible.
Then this book plays a bad game of telephone where the authors summarize research they did not do, and at times seems like it might’ve been sourced from a Reddit comment section, in an effort to make their publishers and publicist happy by hitting a page count.
Read Phillip Tetlocks “Expert Political Judgement” and “Superforcasting” for better and more in depth research on the core topics covered here. Invisible Women does a good job with some of this. Honestly this book felt like a psych sophomore five solo cups of thunder punch deep trying to explain their thoughts on cognitive bias. Don’t waste your time.
I really wanted to like this. I liked Nudge which has Cass as an author, I generally liked Thinking Fast and Slow, and I want someone who’s not Nate Silver explain signal to noise ratios to help me curate better information in my life. But this book isn’t it. This book is literally noise. Worthless noise in an already noisy world.
Someone like Kahneman, a founder of behavioral economics, you would think would have interesting new research and considered takes on how to cut through the amount of chatter out there in the world. It’s an important problem. But it seems like behavioral economics has stalled out into finding goofy and minor errors in our cognitive biases. Hey look! two people came to different answers when asked to mentally calculate an abstract concept. Look at how I can create methodologically dubious and unreplicatible studies that confuse people into making decisions against their best interests. Am I a behavioral economist yet?
I’m so sick of people writing shitty books to promote themselves as “thought leaders” and charge more for their consulting. I expected a better book out of these authors but found myself extremely disappointed in the shallowness of the ideas and writing. It’s a bad regurgitation of ideas that has been done better in other places.
If you like feeling cocktail-party smart without actually having to put in the effort to be smart, you will probably like this. It’s full of pithy blurbs. (Judges are impacted by whether or not their favorite football team won the night before.) Memorize a few and you’ll impress your wife’s-bosses-cousin in no time. Freakonomics did it better. But the fundamental problem is that this book doesn’t say anything that hasn’t been beaten to death before.
Essentially decisions come down to judgments and judgments can be skewed through bias and noise. Noise = randomness except it’s a lot harder to charge six figure consulting fees when you say “oh jeez, there’s just a lot of randomness all up in here.” Much sexier to call it a “noise audit” and point to your crappy book as a guide. People may not be great predictors but we sure are predictably gullible.
Then this book plays a bad game of telephone where the authors summarize research they did not do, and at times seems like it might’ve been sourced from a Reddit comment section, in an effort to make their publishers and publicist happy by hitting a page count.
Read Phillip Tetlocks “Expert Political Judgement” and “Superforcasting” for better and more in depth research on the core topics covered here. Invisible Women does a good job with some of this. Honestly this book felt like a psych sophomore five solo cups of thunder punch deep trying to explain their thoughts on cognitive bias. Don’t waste your time.
kclem's review
4.0
Human judgement is flawed. We have a bias for bias and will constantly seek the simple explanation for events that are better explained by probabilities. This book does an excellent job explaining how statistical noise impacts both daily and societal decision making.
phsn's review
4.0
“Noise is rarely recognised, bias is the star of the show.”
A book attempt to redress the balance.
Bias: systematic deviation
Noise: random scatter
Judgement: a form of measurement with human mind as instrument
Theme:
• Wherever there is judgment, there is noise —and more of it than you think.
• Whenever there is prediction, there is ignorance, and probably more of it than we think.
Component of noise:
✔️error into bias & system noise
✔️system noise into level noise & pattern noise
✔️pattern noise into stable pattern noise & occasion noise
Key Points:
1- Judgement is difficult because the world is complicated, uncertain place —disagreement is unavoidable wherever
2- The extent of these disagreements is much greater than expected
3- Noise can be reduced —some methods adopted to reduce noise can simultaneously reduce bias as well.
4- Noise reduction efforts often raise objections and run into serious difficulties.
5- Poor group dynamics add/amplify noise
Fav parts:
• A good question to ask that caught my attention is, “How would a value of such an improvement compare with the value of reducing bias?” —Suggested few methods
• Variability is expected, not just between us but within ourselves which influenced by countless factors.
• “How good is human judgement in relative to formula? How noise impairs clinical judgement?” —mechanical aggregation outperforms clinical judgement
• “We think we understand what is going on here, but could we have predicted it?”
Not up to my expectations :( BUT, they did made this book easier to understand & in short chapters thus suitable for #beginners. Good that each chapters ended with brief generalised propositions but some inputs are not constant throughout the book. Recommended to those who would like to start reading on psychology & anyone interested in learning/reducing effects of noise in decision making.
“Noise is often a larger component of error than bias —bias is a compelling figure, while noise is the background to which we pay no attention”
mkesten's review
3.0
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.
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.