People have two very different responses to streaks. For example, when watching a basketball game, we see a player hit two three-point shots in successive trips down the court, and we expect him to make a shot on the next trip down the court. The idea that a streak is highly likely to continue is a belief in a hot hand.
However, if you are playing roulette at a casino, and the lands on a red number 4 times in a row, you expect that there is a good chance that it will land on black the next time. The idea that the odds that a streak will end go up as the streak gets longer is called the gambler’s fallacy.
Just looking at these two reactions, it is clear that sometimes we expect streaks to continue and other times we expect streaks to end. What determines which of these reactions we are going to have?
Eugene Caruso, Adam Waytz, and Nicholas Epley looked at this issue in a 2010 paper in the journal Cognition. They find that you are most likely to assume that a streak will continue (the hot hand) when the cause of the streak is seen to be someone’s intentions. You believe the basketball player will keep hitting shots, because he intends to make the shots.
When the streak is caused by some kind of mechanical device, then people believe the streak will end (the gambler’s fallacy). The roulette wheel is a mechanical device that does not intend for the ball to land on either black or red numbers.
These authors tested this idea with a series of clever experiments and studies. In one experiment, people watched a video of someone flipping a coin. One group was told to focus on the intentions of the coin flipper to understand “what he is trying to accomplish with his tosses.” A second group was told to focus on his actions, “the specific movements of his hands and fingers.”
At various points, the groups made predictions for what the next coin flip would be. For one prediction, the previous 8 tosses involved a random-looking sequence of 4 heads and 4 tails. For a second prediction, 6 of the previous 8 tosses had been heads including a streak of 4 heads in a row. When the sequence was random, people in both groups predicted that the coin would come up heads about half the time. When the sequence ended with a streak, though, people who focused on the person’s intentions predicted that the coin would come up heads 68% of the time, while those who focused on the person’s actions predicted the coin would come up heads 28% of the time. That is, thinking about intentions led people to think the streak would continue, while thinking about the mechanism of the flip led people to think it would end.
In another study, people made predictions about stock prices. They were shown graphs of the performance of some stocks over a two-week period. The critical items in this study were graphs that had trends in the stock price. In one graph, the price of the stock went up consistently over the two week period. Another second graph had a decreasing trend. Participants were asked to predict the next day’s stock price. Unsurprisingly, people shown the increasing trend assumed that the stock would keep going up. People shown the decreasing trend assumed that the stock would keep going down.
However, the authors had participants complete a questionnaire about an individual difference in anthropomorphism. That is, some people have a tendency to give human traits and mental characteristics to inanimate objects, while others do not. Those people who were most likely to think that the stock market has a mind of its own were the ones who were most likely to think that the streak in stock prices would continue. Those people who were most likely to think that the stock market has no intentions were most likely to think that the streak in stock prices would end.
This last study has important implications. In daily life, we must often make predictions about what will happen in complex situations. It is important to recognize those situations in which we have a good causal understanding of the situation and know whether the data we observe are good predictors of future performance and those situations in which the most recent observations are just the outcome of a generally random process. In these situations, we must take some care not to ascribe intentions to processes that are really random.
It is more difficult to avoid anthropomorphizing than it looks. We talk about many institutions using language often associated with the actions of people. Reports in the business sections of newspapers talk about markets “reacting” to news. They describe companies “striving” to overcome poor performance. This language reinforces the idea that organizations may have intentions.
At times, it may make sense to treat a company like a person. Companies have managers who make decisions and these decisions may properly be cast as intentions for the strategy that will be followed in the future. At other times, though, this language may get in the way. There is a tremendous amount of randomness in the stock market. When we talk about it in human terms, we gloss over all of that randomness.
In the end, we should try to be a bit more mindful about when we assume that streaks are the results of an agent’s intentions.
