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Heuristic Processing: Availability and Representativeness

16 February, 2016 - 09:24

Another way that our information processing may be biased occurs when we use heuristics, which are information-processing strategies that areuseful in many cases but maylead to errors when misapplied. Let’s consider two of the most frequently applied (and misapplied) heuristics: the representativeness heuristicand the availabilityheuristic.

In many cases we baseour judgments on information that seems to represent, or match, what we expect will happen, whileignoring other potentiallymorerelevant statistical information. When we do so, we are using the representativeness heuristic. Consider, for instance, the puzzle presented in Table 8.4. Let’s say that you went to a hospital, and you checked the records of the babies that were born today. Which pattern of births do you think you are most likely to find?

Table 8.4 The Representativeness Heuristic

ListA

ListB

6:31 a.m.

Girl

6:31 a.m.

Boy

8:15 a.m.

Girl

8:15 a.m.

Girl

9:42 a.m.

Girl

9:42 a.m.

Boy

1:13 p.m.

Girl

1:13 p.m.

Girl

3:39 p.m.

Boy

3:39 p.m.

Girl

5:12 p.m.

Boy

5:12 p.m.

Boy

7:42 p.m.

Boy

7:42 p.m.

Girl

11:44 p.m.

Boy

11:44 p.m.

Boy

Using the representativenesheuristic maleaus to incorrectly believthasome patterns oobserved eventare more likely to havoccurred thaothersIn this case,lisseemmore randomand thus is judged amore likely to havoccurred, but statistically botlistare equally likely.

 

Most people think that list B is more likely, probably because list B looks more random, and thus matches (is “representative of”) our ideas about randomness. But statisticians know that any pattern of four girls and four boys is mathematically equally likely. The problem is that we have a schema of what randomness should be like, which doesn’t always match what is mathematically the case. Similarly, people who see a flipped coin come up “heads” five times in a r ow will frequently predict, and perhaps even wager money, that “tails” will be next. This behavior is known as the gamblers fallacy. But mathematically, the gambler’s fallacy is an error: The likelihood of any single c oin flip being “tails” is always 50%, regardless of how many times it has come up “heads” in the past.

Our judgments can also be influenced by how easy it is to retrieve a memory. Thetendencyto makejudgments of thefrequencyor likelihood that an event occurs on thebasis of the easewith which it can beretrievedfrom memoryis known as the availability heuristic (MacLeod & Campbell, 1992; Tversky & Kahneman, 1973). 1 Imagine, for instance, that I asked you to indicate whether there are more words in the English language that begin with the letter “R” or that have the letter “R” as the third letter. You would probably answer this question by trying to think of words that have each of the characteristics, thinking of all the words you know that begin with “R” and all that have “R” in the third position. Because it is much easier to retrieve words by their first letter than by their third, we may incorrectly guess that there are more words that begin with “R,” even though there are in fact more words that have “R” as the third letter.

The availability heuristic may also operate on episodic memory. We may think that our friends are nice people, because we see and remember them primarily when they are ar ound us (their friends, who they are, of course, nice to). And the traffic might seem worse in our own neighborhood than we think it is in other places, in part because nearby traffic jams are more easily retrieved than are traffic jams that occur somewhere else.