The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty

CHAPTER 14

Decision Trees

My introduction to what is known today as decision analysis occurred in Paris. It was the winter of 1951, when at age 6, I asked my father what he was working on. He had received a Guggenheim fellowship to write his book, The Foundations of Statistics,¹ and was on sabbatical from the University of Chicago. He told me that he was thinking about how people made decisions, and he gave me the following example of how they don’t.

A man in a restaurant is trying to decide between the fried chicken and the roast beef. He is inclined toward the chicken, but asks the waiter one more question: “Do you also have duck today?” “Yes we do,” responds the waiter. “Oh, in that case,” says the man, “I’ll have the beef.” My father eventually arrived at a set of rules that proposed to describe how rational people would make decisions in the face of uncertainty. The preceding restaurant decision would be deemed irrational, because whether the restaurant had duck was irrelevant to the choice between chicken and beef.

My father stayed in this line of work for the rest of his life, collaborating with Milton Friedman and others on what came to be known as the THEORY OF RATIONAL EXPECTATION. He put it this way on page 16 of The Foundations of Statistics:

The point of view under discussion may be symbolized by the proverb “Look before you leap,” and the one to which it is opposed by the proverb, “You can cross that bridge when you come to it.”

The theory is based on the principle ...