### The perils of prediction

My brother pointed me to this New Yorker review of a book titled “Expert Political Judgment: How Good Is It? How Can We Know?” by Philip Tetlock. One part I found particularly interesting concerns a common error:

Apparently, Tetlock's research (he's a psychologist who teaches at Berkeley) shows that experts tend not to be all that good at making predictions. It reminds me of a book I read years ago (Futurehype by Max Dublin) which made a similar point. Prediction is a tricky business.

" ... like most of us, experts violate a fundamental rule of probabilities by

tending to find scenarios with more variables more likely. If a prediction needs

two independent things to happen in order for it to be true, its probability is

the product of the probability of each of the things it depends on. If there is

a one-in-three chance of x and a one-in-four chance of y, the probability of

both x and y occurring is one in twelve. But we often feel instinctively that if

the two events “fit together” in some scenario the chance of both is greater,

not less. The classic “Linda problem” is an analogous case. In this experiment,

subjects are told, “Linda is thirty-one years old, single, outspoken, and very

bright. She majored in philosophy. As a student, she was deeply concerned with

issues of discrimination and social justice and also participated in antinuclear

demonstrations.” They are then asked to rank the probability of several possible

descriptions of Linda today. Two of them are “bank teller” and “bank teller and

active in the feminist movement.” People rank the second description higher than

the first, even though, logically, its likelihood is smaller, because it

requires two things to be true—that Linda is a bank teller and that Linda is an

active feminist—rather than one."

Apparently, Tetlock's research (he's a psychologist who teaches at Berkeley) shows that experts tend not to be all that good at making predictions. It reminds me of a book I read years ago (Futurehype by Max Dublin) which made a similar point. Prediction is a tricky business.

## 1 Comments:

The "Linda problem" is one of my favorite examples for illustrating how people do not grasp probabilities. When I tell students, "If you ask for more, then you're less likely to get it!" They agree. Then give them the Linda problem and watch them fall right into the snare. [sigh]

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