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Now we’ve spoken about the availability heuristic, but there’s another heuristic
I really like, called representativeness. Now Danny Kahneman already introduced us to
this character called Linda the bank teller, and Linda is described as very outgoing and
bright. As a student, she was really passionate about social justice issues and discrimination,
and she even participated in anti-nuclear demonstrations.
Now when you ask people, “Is Linda a bank teller or a feminist bank teller,” people
are way more likely to report that Linda is a feminist bank teller, even though just thinking
about the base rates and the probability, there are way more bank tellers than there
are feminist bank tellers. So what the Linda example sets up is—kind of conflicts between
probability and base rates on one hand, what is actually true, versus representativeness,
on the other. So those two things conflict, and representativeness wins. The description
of Linda being so representative of a feminist sort of pushes the probability down and were
more likely to respond that Linda is a feminist bank teller.
This works not only for toy scenarios like the Linda problem, but it’s broader than
that. It’s more general in terms of category learning. If you think, for example, about
fruit. When I say fruit, what’s the first thing that comes into mind? It’s probably
an apple or an orange or something, not a tomato or pumpkin, which are also fruits but
are probably not the first that you’d think of. You do the same thing with—I don’t
know—a grocery store clerk. We have these ideas about how things are supposed to work.
When you walk into a grocery store, for example, you have an idea about who works there and
who doesn’t. I’ve made this mistake in the past. I walked into a grocery store and
I asked somebody where the lime juice was—those little containers of lime juice. I walk in,
“Where does this belong?” A guy says, “I don’t actually work here,” but he
had a clipboard. That’s what gets me. The guy had a clipboard. Who walks around in a
grocery store with a clipboard? But he doesn’t have—he totally fit the mold of somebody
who worked in the store because he had a clipboard and he was walking. He even had a tie. So
I was confused. But for the most part, I mean, that kind of
example demonstrates that for the most part, it gets us by. When I walk into a store, I
can always tell who works there 99 percent of the time. So this idea of representativeness,
of relying on prototypes, gets us by most of the time, but when we can create these
scenarios where we don’t operate with 100 percent accuracy.
So Danny Kahneman and Amos Tversky had to create this Linda problem, so she really fit
the mold of a feminist bank teller, to kind of trick people in the sense to fall in to
this mistake. What we’re going to do now is present another
example, one from, again, Danny Kahneman and Amos Tversky, that they came up with, where
we talk about Rudy who’s in a similar sort of vein as Linda the famous feminist bank
teller. Let’s see if people still make the same sort of error when it comes to Rudy.