Heuristics
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Did you know that our brain uses strategies to process information and draw conclusions? Although we're able to reach conclusions through these mental strategies, sometimes, our reasoning can be off. Read on to discover how our brain draws these conclusions and why they can be wrong.
What are heuristics? Let's start with an example of one.
Chances are, most of these people are exercising because they believe that doing so is healthy for them. But what if I believed exercise was, in fact, unhealthy? What if I reasoned that my grandfather, who never exercised, lived to be 104 and therefore, exercising must actually cause early death? Do you think my rationalization about exercise being unhealthy is compelling, or does it seem overly reliant on one measly data point, my grandfather?
Psychologists have given this type of reasoning a name - the availability heuristic. An availability heuristic allows us to judge something, such as the health benefits of exercise, based on the examples we can readily bring to mind. In the example I just gave, because I could quickly bring to mind the example of my grandfather, I based my judgment about exercise on him. If I had slowed down and considered more examples of people who did and did not exercise, I might have come to a different, and perhaps more statistically accurate, conclusion about the potential health benefits of exercise.
The availability heuristic is one of several possible heuristics. The term 'heuristic' refers to techniques for drawing conclusions. These techniques are based on things we have found or discovered through prior experience.
Sometimes, heuristics are helpful, because they help us reach conclusions faster. For example, maybe you're playing a board game with lots of possible moves, but you only have a limited amount of time to figure out what you're going to do. In this instance, choosing one of the moves that readily comes to mind based on your prior experience with the game might help you to score more points than would analyzing all possibilities, which might cause you to run out of time before making a move at all.
Sometimes, though, as was the case with the example about the health benefits of exercise, using heuristics can result in cognitive bias. Cognitive biases are deviations in judgment that result in distorted, inaccurate and illogical conclusions.
Here's another example of the availability heuristic resulting in cognitive bias. Although airplane crashes are rare compared to say, car crashes, you vividly remember all the ones you've seen in the news. Thus you begin to worry that the friendly skies are far more dangerous than they actually are. Though car crashes are much more common and deadly, they're not as dramatic and are less likely to be featured in the news. The availability heuristic would lead you to think that car travel is safer than air travel. Airplane crashes are also quite dramatic events; we can recall vivid details of the ones we see on the news: the fiery explosion, the strewn metal and the burned fuselage. This raises the issue of salience, which means that when details are particularly vivid or prominent, we're more likely to remember them, and thus more likely to bring them readily to mind.
Let's talk about one more kind of heuristic. Have you ever heard the saying, 'Lightning never strikes the same place twice'? This is an example of a representativeness heuristic. This term refers to drawing a conclusion based on the extent to which some event matches our expectations. Many people might have the expectation that lightning striking in a particular place is rare and that once it strikes any given place, the likelihood of it doing so again is even rarer. In truth, though, lightning is statistically just as likely to strike the same place again as it is likely to strike any other. Because of the representativeness heuristic, people are likely to incorrectly estimate the statistical probability of something if it interferes with their expectations.
A phenomenon known as the 'Gambler's Fallacy' also illustrates the representativeness heuristic. With it, the common expectation is that all possible outcomes of some random process will occur more or less equally. For example, if you're playing Roulette, you might have the expectation that red spins will result about as often as black. Now, suppose the past five spins have come up black. If you thereby believe that the next spin is more likely to be red, that's the gambler's fallacy, and also an example of cognitive bias resulting from a representativeness heuristic. Statistically, black and red are equally likely outcomes on the sixth spin; there is no logical reason to believe a red spin is more likely. Similarly, if you're flipping a coin and have turned up 10 heads in a row, the next flip is still 50% likely to be heads and 50% likely to be tails. Each flip, and each spin of the roulette wheel and each lightning strike is an individual event that does not depend on what's happened before.
To conclude, we've talked about two types of heuristics based on prior experience for making judgments or drawing conclusions. Although heuristics can be useful, they can also lead to cognitive biases, or deviations in good judgment. We've talked about how the availability heuristic leads us to make judgments based on information that is readily available to us, and about how the representativeness heuristic can lead us to conclusions based on our wrong expectations.