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How We Know What Isn't So

The Fallibility of Human Reason in Everyday Life
Narrated by: Dan Gallagher
Length: 7 hrs and 23 mins
5 out of 5 stars (1 rating)

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Summary

Thomas Gilovich offers a wise and readable guide to the fallacy of the obvious in everyday life. 

When can we trust what we believe - that "teams and players have winning streaks", that "flattery works", or that "the more people who agree, the more likely they are to be right" - and when are such beliefs suspect? 

Thomas Gilovich offers a guide to the fallacy of the obvious in everyday life. Illustrating his points with examples, and supporting them with the latest research findings, he documents the cognitive, social, and motivational processes that distort our thoughts, beliefs, judgments and decisions. In a rapidly changing world, the biases and stereotypes that help us process an overload of complex information inevitably distort what we would like to believe is reality. Awareness of our propensity to make these systematic errors, Gilovich argues, is the first step to more effective analysis and action.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2008 Thomas Gilovitch (P)2019 Echo Point Books & Media

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  • Timothy Lin
  • 06-09-19

Great book although ironically slightly overconfident

It’s a great message on how to think clearly and has lots of critical lessons that I think are valuable for everyone.

It’s just a bit ironic that he goes off on a tangent for a whole chapter in this book on how ESP is not possible with the intense confidence he has. It’s almost like he has a personal vendetta against it.

Much of this book is also written with an air of supreme confidence which seems a bit anti-“everything he said in the book” so there’s a bit of irony there.

But all in all, great book I’d recommend it to anyone looking to improve their thinking clarity.

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  • N
  • 28-08-19

Good Information but very dour

Important information that everyone needs about drawing conclusions from data presented in a dull way.