πŸ’Ž On the various ways in which social proof affects us (obesity is contagious)

Obesity is contagious. If your best friends get fat, your risk of gaining weight goes up.

Broadcasters mimic one another, producing otherwise inexplicable fads in programming. (Think reality television, American Idol and its siblings, game shows that come and go, the rise and fall and rise of science fiction, and so forth.)

The academic effort of college students is influenced by their peers, so much so that the random assignments of first-year students to dormitories or roommates can have big consequences for their grades and hence on their future prospects. (Maybe parents should worry less about which college their kids go to and more about which roommate they get.)

In the American judicial system, federal judges on three-judge panels are affected by the votes of their colleagues. The typical Republican appointee shows pretty liberal voting patterns when sitting with two Democratic appointees, and the typical Democratic appointee shows pretty conservative voting patterns when sitting with two Republican appointees. Both sets of appointees show far more moderate voting patterns when they are sitting with at least one judge appointed by a president of the opposing political party.

Excerpt from: Nudge: Improving Decisions About Health, Wealth and Happiness by Richard Thaler and Cass Sunstein

πŸ’Ž On how social cohesion among groups leads to conformity and reduced (financial) performance

The worst-performing clubs were built on affective ties and primarily social; the best-performing clubs had limited social connections and were focused on increasing returns. Dissent was far more frequent in the high-performing clubs. The low performers usually had unanimous votes, with little open debate. Harrington found that the votes in low-performing groups were “cast to build social cohesion rather than make the best financial decision.” In short conformity resulted in significantly lower returns.

Excerpt from: Conformity: The Power of Social Influences by Cass Sunstein

πŸ’Ž On our tendency to be unrealistically optimistic (see divorce rates)

People are unrealistically optimistic even when the stakes are high. About 50 percent of marriages end in divorce, and this is a statistic most people have heard. But around the time of the ceremony, almost all couples believe that there is approximately a zero percent chance that their marriage will end in divorce — even those who have already been divorced! (Second marriage, Samuel Johnson once quipped, ‘is the triumph of hope over experience.’) A similar point applies to entrepreneurs starting new businesses, where the failure rate is at least 50 percent. In one survey of people staring new businesses (typically small businesses, such a contracting firms, restaurants, and salons), respondents were asked two questions: (a) What do you think is the chance of success for a typical business like yours? (b) What is your chance of success? The most common answers to these questions were 50 percent and 90 percent, respectively, and many said 100 percent to to the second question.

Unrealistic optimism can explain a lot of individual risk taking, especially in the domain of risks to life and health.

Excerpt from: Nudge: Improving Decisions About Health, Wealth and Happiness by Richard Thaler and Cass Sunstein

πŸ’Ž On how the group consensus sways other people’s opinions (we like to conform)

Additional experiments, growing out of Asch’s basic method, find large conformity effects for judgments of many different kinds. Consider the following finding. People were asked, β€˜Which one of the following do you feel is the most important problem facing our country today?’ Five alternatives were offered: economic recession, educational facilities, subversive activities, mental health, and crime and corruption. Asked privately, a mere 12 percent chose subversive activities. But when exposed to an apparent group consensus unanimously selecting that option, 48 percent of people made the same choice!

Excerpt from: Nudge: Improving Decisions About Health, Wealth and Happiness by Richard Thaler and Cass Sunstein

πŸ’Ž Our tendency to underestimate the variance – or noise – in business

In a well-run insurance company, if you randomly selected two qualified underwriters or claims adjusters, how different would you expect their estimates for the same case to be? Specifically, what would be the difference between the two estimates, as a percentage of their average?

We asked numerous executives in the company for their answers, and in subsequent years, we have obtained estimates from a wide variety of people in different professions. Surprisingly, one answer is clearly more popular than all others. Most executives of the insurΒ­ance company guessed 10% or less.Β  When we asked 828 CEOs and senior executives from a variety of industries how much variation they expected to find in similar expert judgments, 10% was also the median answer and the most frequent one (the second most popular was 15%). A 10% difference would mean, for instance, that one of the two underwriters set a premium of $9,500 while the other quoted $10,500. Not a negligible difference, but one that an organization can be expected to tolerate.

Our noise audit found much greater differences. By our measure. the median difference in underwriting was 55%, about five times as large as was expected by most people, including the company’s executives.

Excerpt from: Noise: A flaw in human judgement by Daniel Kahneman, Olivier Sibony and Cass R. Sunstein