Thinking, Fast and Slow, by Daniel Kahneman. New York: Farrer, Straus and Giroux, 2011. 499 pages. Sacred Heart University Library: BF441 .K238 2011
Kahneman, a Nobel Prize winner in in Economics, assembles much of his life's work in this accessible, entertaining, and thought-provoking book. It's not short, but it's worth it. His main target is the model of rational decision-making assumed or implied in many fields: economics, public affairs, diplomacy, psychology, even politics, sociology, and meta-scientific discussion (where "the rational person would ... [fill in the blank]").
Kahneman instead finds two systems that drive human behavior, thinking, and decision-making. "System 1" is fast, emotional, intuitive, reflexively automatic, and constantly monitors the surroundings for changes, threats, opportunities, and emotional signals. "System 2" is slower, logical, deliberative. Everyone has a lively and functioning System 1, but System 2 can be trained, influenced by education and life-experience, and varying levels of self-awareness. System 2 can be inordinately influenced, however, by assumptions, intuitions, and consequent deliberative errors to which System 1 is prone, and System 2 can merely authorize, validate, and intensify decisions resolved by System 1.
These two systems are "characters," easily discernible shorthand for a congeries of mental habits, neurological links, learned behavior, and physical states. In short, easily read chapters Kahneman discloses numerous fallacies, biases, and heuristic errors to which even highly-trained, logical people are prone. The "availability bias," jumping to conclusions, the "halo affect" and numerous other well-studied behaviors not only unduly influence personal judgments and biases but influence political deliberations, financial calculations, and above all economic policies. The self-destructive ways that human fall apart (sometimes, especially, powerful ones), the unintended, sometimes disastrous consequences of well-meaning policy shifts, and other human ills are illuminated if not quite completely explained.
Occasionally Kahneman falls into an unintentional paternalism of asking set-up questions at the beginning of a chapter to induce the reader towards an error. Fun to read, sometimes these questions seem too clever by half and take advantage of critical but unexplored ambiguities. For example, in Chapter 14 (page 146) "Tom W is a graduate student at the main university in your state." The reader is asked to "rank nine subsequent fields of graduate specialization in order of the likelihood that Tom W is now a student in each of those fields." Fields in not-quite alphabetical order are listed, one of them is "humanities and education." (--Interesting to combine both of those in one line when some would say they differ substantially.)
I'm a reader in Connecticut. What is the main university of my state? by USNews rankings, Yale? or by the enrollment numbers, UConn? I happen to know, however, that Yale doesn't teach education at a graduate level, and surely has an above-average graduate enrollment in the humanities. Meanwhile, UConn has numerous graduate students in education, because all teacher certification in Connecticut is channeled through fifth-year "graduate" education programs. So what is the answer to Kahneman's ambiguous and simple question?
Kahneman tells us that the key to the answer is the relative size of enrollment in different fields. That still doesn't tell me which is the "main university" in my state --and pity the poor reader in California or New York. Which is the "main university" in Connecticut? I know already that total enrollment at Yale is smaller than UConn. When the reader is subsequently given more personal information about Tom W, it is given to suggest occupational stereotypes associated with fields of graduate study. The reader is paternalistically manipulated into speculating that Tom W is a computer science student. He was written up as an "anti-base rate" character, deliberatively suggestive of smaller-enrollment fields of study and unlike stereotypes of larger fields.
The lesson is to discipline the practice of predicting by representativeness by recourse to rules associated with Bayesian statistics. (Kahneman explains all this, p. 154) But I was left with a sense that the example was set up simply to illustrate where Kahneman was heading anyway, and I would just as soon have followed him there without the suggestive manipulation of a deliberately ambiguous example.
Despite all this, I enjoyed the book. I wish it had been shorter, and that Kahneman actively solicited errors of judgment less. They occur anyway --give the reader a rest, sometimes. I learned a great deal, however, and I watched the "availability heuristic" guide a University deliberative meeting while I was reading it. It was an eerie experience, and well explored in this book.
--Gavin Ferriby
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