"Thinking, fast and slow" by Daniel Kahneman

This book is a sort of retrospective of the life's work of Daniel Kahneman, a psychologist who won the Nobel Prize for Economics by replacing the rational agent of classical Economics with a real person.

It seeks to divide human thinking into two systems; there are three ways he does this. In part one he compares the fast, intuitive ways in which we think with the slow, effort-full, rational ways of thinking. Because rational thinking is hard work we lazt humans tend to default to intuition which makes us more gullible. In part two he compares the rational agent of Economics (the 'Econ') with Humans. Part three pits the present against the past and shows how what we remember about what we experienced is rarely the same as what we experience.

Kahneman recounts the hundreds of experiments he has conducted during his long career. Many of them offer profound insights into how humans operate. It is clear that if one wishes to improve communications, improve pedagogy, or manipulate people better, there are lessons to be learnt.

One little quibble: many of these experiments were conducted with someone called Amos. Because I had skipped the introduction (I often read introductions at the end because I believe that if a book is strong enough it should stand without the introduction) I did not know who he was talking about. It was Amos Tversky, a long time collaborator, now dead. In some ways this book is Kahneman's tribute to Mr Tversky.

One thing I loved was the evidence base. Many of these experiments prove counter-intuitive conclusions. This hammers home the fact that we are not who we think we are. This book has a massive evidence base for Kahneman's view of humans, in contrast to the scarcely visible evidence base of Roger Scruton's The Uses of Pessimism.

A lot of what Kahneman has to say I have encountered before, for example in Nudge which was written by Richard Thaler and Cass Sunnstein, both former colleagues of Kahneman. For example, I knew about anchoring and that algorithms give better long-range forecasts than expert opinions. Nevertheless, this is a brilliant introduction to these ideas  if you are new to the topic and possibly the most comprehensive text I have encountered (but also try Irrationality by Stuart Sutherland). My only real quibble is that Kahneman does not go into sufficient detail about Bayes Theorem (for which you need The Signal and the Noise by Nate Silver).

Not only is this a book full of fascinating ideas but it is also extrememly readable. August 2013; 418 pages.