Humans are natural storytellers; they attempt to make sense of the world by attaching stories to events that occur. Because of this, Kahneman explains, humans have a difficult time reckoning with purely statistical or numerical information and they underestimate the randomness in the world. One of the biggest difficulties that people face in making decisions or analyzing data is when they are presented with statistical information in conjunction with a narrative about the same principle. Even though the statistical information should hold as much weight—if not more—than the narrative, people generally prefer the narrative.
Humans will readily violate the laws of probability when they are presented with details that play into their impulse to automatically construct stories in their minds. After hearing priming details about a fictional person named Linda—including the facts that she is single, outspoken, concerned with discrimination and social justice—people said that it was more probable that Linda was a feminist bank teller than a bank teller, even though this violates the law of probability because any feminist bank teller is, by default, a bank teller (so simply saying “bank teller” would be the better guess). In another example, Kahneman describes a scenario: a cab was involved in a hit and run accident at night. 85 percent of the cabs in the city are green and 15 percent are blue. A witness identified the cab as blue; witnesses under these circumstances correctly identify cab colors 80 percent of the time. What is the probability that the cab was green? Kahneman finds that people usually ignore the base rates of the number of cabs, and instead favor the witness’s accuracy, guessing about 80 percent. However, if the first sentence had said that green cabs are involved in 85 percent of accidents, people give more weight to that information because they construct a story assuming that the green cabs are more reckless. Thus, the narrative assumptions cloud the statistical information and make people less accurate.
People often place more weight in causality (the fact that an event directly leads to another event) because it helps them make sense of the world. However, this leads to errors in judgment because the world is often more random than people believe it to be. Kahneman worked with the Israeli Air Force, and he describes how one of the instructors emphasized punishment over reward. The instructor stated that when he praised flight cadets for a good maneuver, they usually did worse. Screaming into a cadet’s ear for bad execution generally led to better performance. However, this discredits the fact that a particularly good execution of a certain maneuver will more likely than not be followed by a less well-executed maneuver, and vice-versa with a particularly bad execution. Thus, while the instructor may appear to be correct, he is inappropriately attaching causality between his actions and the cadets’ performances. In general, people will assign greater significance to talent, stupidity, and intentions than to luck. Entire industries are built on expert analysts explaining what is often just due to laws of probability and chance. Kahneman points to analysis of the Olympic ski jump, in which athletes jump twice. If athletes have a good first jump, commentators say they will have a worse second jump because they will feel pressure; if athletes have a bad first jump, commentators say that they have nothing to lose and will have a better second jump. The analyst has detected a principle of luck and chance and has assigned a causal story to it. But Kahneman points out that, like the cadets, the athletes are simply more likely to have a worse jump if they had a better jump just prior, and vice versa.
The previous examples demonstrate how people lack objectivity when looking at statistics, but people also lack objectivity when they are forced to evaluate their own experiences. How an experience ends seems to hold greater weight in people’s memory than how it was as a whole. A record scratch at the end of an enjoyable concert “ruins” the experience. Even though the past is fixed, memory is mutable, and the story of how a person experienced the concert is changed in retrospect. Similarly, when people have a bad experience, the duration of that experience is less important than the memory of it. In an experiment, people are exposed to two experiences: first, sixty seconds of putting their hand in a cold water bath; second, sixty seconds of putting their hand in a cold water bath followed by thirty additional seconds with slightly less cold water. People prefer to repeat the second experience rather than the first, even though the second experience encompasses the first experience. Subjectively, people believe the second option is slightly less painful because it ends in a better way. This is another way in which people’s perceptions do not match statistical data and therefore cause them to act or respond in unexpected ways.
Constructing stories about the world is a useful way to make sense of it, but it also becomes one of the primary ways in which people commit errors in thinking and judgment. Using these examples, Kahneman tries to impress on his readers that things like intentions, talent, and stupidity only tell part of the story, and that luck and randomness should be just as critical in our understanding of how the world works.
Stories and Subjectivity vs. Statistics and Objectivity ThemeTracker
Stories and Subjectivity vs. Statistics and Objectivity Quotes in Thinking, Fast and Slow
We are far too willing to reject the belief that much of what we see in life is random.
People without training in statistics are quite capable of using base rates in predictions under some conditions. […] However, concern for base rates evidently disappears as soon as Tom W’s personality is described.
The set of feminist bank tellers is wholly included in the set of bank tellers, as every feminist bank teller is a bank teller. Therefore the probability that Linda is a feminist bank teller must be lower than the probability of her being a bank teller. […] The problem therefore sets up a conflict between the intuition of representativeness and the logic of probability.
Nisbett and Borgida found that when they presented their students with a surprising statistical fact, the students managed to learn nothing at all. But when the students were surprised by individual cases—two nice people who had not helped—they immediately made the generalization and inferred that helping is more difficult than they had thought.
Indeed, we pay people quite well to provide interesting explanations of regression effects. A business commentator who correctly announces that “the business did better this year because it had done poorly last year” is likely to have a short tenure on the air.
You read that “a vaccine that protects children from a fatal disease carries a 0.001% risk of permanent disability.” The risk appears small. Now consider another description of the same risk: “One of 100,000 vaccinated children will be permanently disabled.” The second statement does something to your mind that the first does not.