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ferris_mx's review
2.0
This book wasn't nearly as good as "Thinking Fast and Slow", and was really diluted for a mainstream audience. At some points I was frustrated and put off by the oversimplifications. Nevertheless, some of the ideas were still relevant for me. Let me boil it down to a TL;DR.
There is noise any time there is a human "judge".
Error can be decomposed into the following orthogonal dimensions: bias, level (some judges are more critical than others), pattern (even adjusted for level, judges are not uniform in what they rank highly), occasion (representation of judge inconsistency across time/conditions). We pay lots of attention to bias, but it is harder to pay attention to the other sources of error.
What can be done about it?
* "Noise Audit"
* Picking good experts
* Aggregating results (mean, prediction market, etc.)
* If your process has multiple experts, they must be independent.
* Avoid setting a preliminary decision based on partial information.
* Keep updating your personal prediction model.
* Try to decide components before coming up with an overall recommendation.
There is noise any time there is a human "judge".
Error can be decomposed into the following orthogonal dimensions: bias, level (some judges are more critical than others), pattern (even adjusted for level, judges are not uniform in what they rank highly), occasion (representation of judge inconsistency across time/conditions). We pay lots of attention to bias, but it is harder to pay attention to the other sources of error.
What can be done about it?
* "Noise Audit"
* Picking good experts
* Aggregating results (mean, prediction market, etc.)
* If your process has multiple experts, they must be independent.
* Avoid setting a preliminary decision based on partial information.
* Keep updating your personal prediction model.
* Try to decide components before coming up with an overall recommendation.
paulgrostad's review
4.0
Interesting, fascinating even, but no where near as good as "Thinking fast and thinking slow"
chasinash's review against another edition
challenging
informative
inspiring
reflective
slow-paced
4.25
kafkaesquire's review
2.0
Much like Freakonomics, Noise is the sort of hackery that comes from completely divorcing data from the social context. The book is written with the idea that there's too much unnecessary variability in the way various tasks are carried out, but the examples that were used were really inconsistent. there's a lot more context required in handing down sentences as a judge than there is in underwriting insurance contracts. Overall, the book probably would have been more compelling if they had stuck to examples whose results didn't hinge on the decision maker's subjective worldview. Two stars because the descriptions of all the economic principles were nice and I learned about some new concepts
etopiei's review
4.0
This was quite an interesting book. I did feel it was a little repetitive but it had some helpful lessons and well explained examples.
izzymunford's review against another edition
Interesting theory but very long & very dry, felt never ending! So slow paced I put it down and couldn't pick it up again
emiann2023's review
5.0
Daniel Kahneman is always an interesting story teller, bringing together what you think you know and then pointing out the reality behind the mind. This was an interesting read. Less diverse in scope than Thinking Fast and Slow, but incredibly insightful still.