Noise: A Flaw in Human Judgment

by Daniel Kahneman

to predict the temperature in their city one week out,

the average answer of a large number of people is likely to be close to the truth. The reason is basic statistics: averaging several independent judgments (or measurements) yields a new judgment, which is less noisy, albeit not less biased, than the individual judgments.

Vul and Pashler wanted to find out if the same effect extends to occasion noise: can you get closer to the truth by combining two guesses from the same person, just as you do when you combine the guesses of different people? As they discovered, the answer is yes. ...

“You can gain about 1/10th as much from asking yourself the same question twice as you can from getting a second opinion from someone else.” This is not a large improvement. But you can make the effect much larger by waiting to make a second guess. When Vul and Pashler let three weeks pass before asking their subjects the same question again, the benefit rose to one-third the value of a second opinion.

this result certainly provides a rationale for the age-old advice to decision makers: “Sleep on it, and think again in the morning.”

First, assume that your first estimate is off the mark. Second, think about a few reasons why that could be. Which assumptions and considerations could have been wrong? Third, what do these new considerations imply? Was the first estimate rather too high or too low? Fourth, based on this new perspective, make a second, alternative estimate.

dialectical bootstrapping,

The gain in accuracy with two immediately consecutive “dialectical” estimates was about half the value of a second opinion.

if you can get independent opinions from others, do it—this real wisdom of crowds is highly likely to improve your judgment. If you cannot, make the same judgment yourself a second time to create an “inner crowd.” You can do this either after some time has passed—giving yourself distance from your first opinion—or by actively trying to argue against yourself to find another perspective on the problem. Finally, regardless of the type of crowd, unless you have very strong reasons to put more weight on one of the estimates, your best bet is to average them.

People who are in a good mood are generally more positive. They find it easier to recall happy memories than sad ones, they are more approving of people, they are more generous and helpful, and so on. Negative mood has the opposite effects.

mood has a measurable influence on what you think: what you notice in your environment, what you retrieve from your memory, how you make sense of these signals.

a good mood makes us more likely to accept our first impressions as true without challenging them.

People who are in a good mood are more likely to let their biases affect their thinking.

Gordon Pennycook and colleagues have conducted many studies of people’s reactions to meaningless, pseudo-profound statements generated by assembling randomly selected nouns and verbs from the sayings of popular gurus into grammatically correct sentences, such as “Wholeness quiets infinite phenomena” or “Hidden meaning transforms unparalleled abstract beauty.” The propensity to find meaning in such statements is a trait known as bullshit receptivity.

Inducing good moods makes people more receptive to bullshit and more gullible in general; they are less apt to detect deception or identify misleading information.

Utilitarian calculation, associated with English philosopher Jeremy Bentham, suggests that the loss of one life is preferable to the loss of five. Deontological ethics, associated with Immanuel Kant, prohibits killing someone, even in the service of saving several others.

Making the utilitarian choice to push the man off the bridge requires people to overcome their aversion to a physically violent act against a stranger. Only a minority of people (in this study, fewer than one in ten) usually say they would do so. However, when the subjects were placed in a positive mood—induced by watching a five-minute video segment—they became three times more likely to say that they would push the man off the bridge.

you are not the same person at all times. As your mood varies (something you are, of course, aware of), some features of your cognitive machinery vary with it (something you are not fully aware of).

Among the extraneous factors that should not influence professional judgments, but do, are two prime suspects: stress and fatigue.

physicians are significantly more likely to prescribe opioids at the end of a long day.

toward the end of the day, physicians are more likely to prescribe antibiotics and less likely to prescribe flu shots.

the effect of weather is probably “mediated” by mood (that is, the weather does not directly affect decisions but modifies the decision maker’s mood, which in turn does change how they decide).

“Clouds Make Nerds Look Good.”

the gambler’s fallacy: we tend to underestimate the likelihood that streaks will occur by chance.

the chance that an asylum applicant will be admitted in the United States drops by 19% if the hearing follows two successful ones by the same judge.

you are not always the same person, and you are less consistent over time than you think. But somewhat reassuringly, you are more similar to yourself yesterday than you are to another person today.

extraneous

“Judgment is like a free throw: however hard we try to repeat it precisely, it is never exactly identical.”

“Your judgment depends on what mood you are in, what cases you have just discussed, and even what the weather is. You are not the same person at all times.”

“Although you may not be the same person you were last week, you are less different from the ‘you’ of last week than you are from someone else today. Occasion nois...

in the previous chapter that aggregating the judgments of multiple individuals reduces noise. But because of group dynamics, groups can add noise, too.

because of the dynamics among group members—our emphasis here—the level of noise can be high.

Salganik and his coauthors meant to explore. They were testing for a particular driver of noise: social influence.

a song benefited from early popularity, it could do really well. If it did not get that benefit, the outcome could be very different.

the very worst songs (as established by the control group) never ended up at the very top, and the very best songs never ended up at the very bottom. But otherwise, almost anything could happen.

“The level of success in the social influence condition was more unpredictable than in the independent condition.” In short, social influences...

popularity is self-reinforcing.

Suppose that a small group consisting of, say, ten people is deciding whether to adopt some bold new initiative. If one or two advocates speak first, they might well shift the entire room in their preferred direction. The same is true if skeptics speak first. At least this is so if people are influenced by one another—and they usually are. For this reason, otherwise similar groups might end up making very different judgments simply because of who spoke first and initiated the equivalent of early downloads.

an initial burst of popularity is self-reinforcing, and if a proposal attracts little support on the first day, it is essentially doomed. In politics, as in music, a great deal depends on social influences

“chance variation in a small number of early movers” can have major effects in tipping large populations

seeing an initial up vote (and recall that it was entirely artificial), the next viewer became 32% more likely to give an up vote.

The effect of a single positive early vote is a recipe for noise. Whatever the reason for that vote, it can produce a large-scale shift in overall popularity.

simple estimation tasks

crowds were indeed wise as long as they registered their views independently. But if they learned the estimates of other people—for example, the average estimate of a group of twelve—the crowd did worse.

social influences are a problem because they reduce “group diversity without diminishing the collective error.” The irony is that while multiple independent opinions, properly aggregated, can be strikingly accurate, even a little social influence can produce a kind of herding that undermines the wisdom of crowds.

people tend to neglect the possibility that most of the people in the crowd are in a cascade, too—and are not making independent judgments of their own.

truculent,

obtuse,

apparent consensus of the group, or the views of early speakers,

bandwagon effect,