Thinking and Deciding

THE MECHANISM OF JUDGMENT 379
1963. A scaled-down version opened in 1973, at a cost of $102 million! We could,
in principle, know all this and take it into account in making predictions (Kahneman
and Tversky, 1982c). We could regress toward the mean based on experience. (The
mean completion time might, for example, be about twice the initial estimate, so we
could routinely double all our estimates.) We fail to regress toward this kind of mean
because we think in terms of “singular” data — facts about the case at hand — rather
than “distributional” data, which concern other cases of the same type. Buehler and
his colleagues (1994) found that this overprediction phenomenon, for students completing
assignments, could be reduced if the students were told to think about past
experiences and relate them to the present case.
A final possible example of representativeness is the dilution effect (Nisbett,
Zukier, and Lemley, 1981). People use totally useless information. They seem
to average it in with useful information, so that it causes a kind of regression effect.
For example, when subjects were asked to predict Robert’s grade point average
(GPA) from the number of hours per week that Robert studies, they reasonably predict
a higher GPA when he studies thirty-one hours than when he studies three hours.
When they are also told that Robert “is widely regarded by his friends as being honest”
or “plays tennis or racquetball about three or four times a month,” they make
more moderate predictions. It is as thought they take this useless information to predict
a moderate GPA, and then they average this prediction with the more extreme
prediction derived from the hours per week of studying.
In sum, the representativeness heuristic seems to cause us to neglect the effects of
unpredictability. This results in many misinterpretations in daily life. For example,
when a person is learning a difficult skill such as flying an airplane, performance on
a given maneuver varies unpredictably from trial to trial. If we look at those trials
in which performance is exceptionally good, then it is very likely that performance
will be worse on the next trial. If we look at trials on which people do poorly, then
people are likely to do better on the next trial. Now suppose that we adopt a policy of
rewarding student pilots when they do well and punishing them when they do badly.
Further, suppose that the reward and punishment have only small effects, compared
to the variation in performance from trial to trial. It will appear that the reward
makes the pilots do worse on the next trial and that the punishment makes them do
better (Kahneman and Tversky, 1983).
In ordinary life, we are always asking questions that show that our expectations
are based on the representativeness heuristic. Why is it that brilliant women (men)
marry men (women) who are not quite as brilliant? Why is it that the food in restaurants
tends to be better the first time you go than the second? The answers to these
questions have to do with unpredictable variation. Brilliant women (men) marry men
(women) who are not quite as brilliant because equally brilliant partners are hard to
find, and it just might be that we look for other things in a mate besides equivalent
brilliance. Why is the food in restaurants better on the first visit than the second? Because
you go back a second time only when the food is very good the first time. Very
likely you have gone to that restaurant on a good day (for that restaurant). When you
go on a bad day, you are disappointed, and you do not go back.