If you flip heads five times, are you “due” for tails?
Our brains have learned to take short cuts, but these shortcuts don’t always work. When they don’t work, we call them cognitive biases.
The representative heuristic is a cognitive bias where we estimate the probability of an event based on how much it resembles other events. Unfortunately, sometimes we fall for superficial similarities.
If you’re hiring for a librarian, you might think the quiet person who wears glasses and always has a book in his hand is more suitable than an extroverted candidate. In that case you assign too much weight to superficial details.
Or consider there’s a pool of 1,000 people, and you know that 70 percent of them are lawyers, and 30 percent are engineers. One person is randomly selected, and he’s wearing a pocket protector. You assume he’s an engineer based on that superficial detail even though it’s more likely that he’s a lawyer.
The Gambler’s Fallacy is a twist on the representativeness heuristic. If you’re flipping a coin, and it’s come up heads five times, the gambler might assume a tails is “due” because five heads in a row doesn’t seem representative of the expected 50/50 distribution. But every flip is independent of the flips before it, so each flip has a 50/50 chance of being heads.
There is an important exception to the Gambler’s Fallacy to keep in mind. If we switch from a coin to dice, and we see that 3 has come up very frequently, it’s also possible the dice are loaded. In other words, a departure from the expected distribution might be from chance. Reality is clumpy. On the other hand, it might not be as random as you think it is.
One of my favorite illustrations of the representativeness heuristic is when people combine two factors. For example, let’s say Linda is 31 years old, outspoken, and very bright. She majored in philosophy, was deeply concerned with issues of discrimination on campus, and took part in anti-nuclear protests. When people are asked whether it’s more likely that Linda is a bank teller or that she’s a bank teller who is active in the feminist movement, many people choose the latter option even though it’s less probable. It’s always less probable that someone is A and B rather than just A.
Why do they do this? Because being involved in the feminist movement seems more representative of Linda’s apparent personality than being a bank teller.
The point of the representativeness heuristic is that people often judge the probability of an event or the characteristics of a person based on how much they resemble a typical case or stereotype, rather than using actual statistical reasoning or probability.
To avoid this mistake, keep these things in mind.
- Consider the base rate. Take into account the actual statistical probabilities of an event.
- Consider multiple points of view.
- Educate yourself about common cognitive biases.
- Slow down your decision making. Remember, cognitive biases are often shortcuts.
- Use the representativeness heuristic against itself. Learn examples of this fallacy and then you can recognize, “Oh, this is like the Gamber’s Fallacy,” or “this is like Linda the bank teller.”