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Heuristics and Biases 1C- Forecasting, Confidence, and Calibration


13. The Weighting of Evidence and the Determinants of Confidence

In cases where little evidence is available, people tend to be overconfident, whereas  when much evidence is available, people tend to be underconfident. The strength of the evidence (heads as evidence coin is biased towards heads)is overweighted compared to other considerations like base rate, or the number of iterations.

One of the major findings that has emerged from this research is that people are often more confident in their judgments than is warranted by the facts. Overconfidence is not limited to lay judgment or laboratory experiments. The well-publicized observation that more than two-thirds of small businesses fail within 4 years (Dun & Bradstreet, 1967) suggests that many entrepreneurs overestimate their probability of success (Cooper, Woo, & Dunkelberg, 1988). With some notable exceptions, such as weather forecasters (Murphy & Winkler, 1977), who receive immediate frequentistic feedback and produce realistic forecasts of precipitation, overconfidence has been observed in judgments of physicians (Lusted, 1977), clinical psychologists (Oskamp, 1965), lawyers (Wagenaar & Keren, 1986), negotiators (Neale & Bazerman, 1990), engineers (Kidd, 1970), and security analysts (Staël von Holstein, 1972). As one critic described expert prediction, “often wrong, but rarely in doubt” (5353).

If the subjects were Bayesian, the solid lines would coincide with the dotted line. Instead, intuitive judgments based on the small sample (n = 5) were overconfident, whereas the judgments based on the larger sample (n = 17) were underconfident (5443).

Both conservatism and overconfidence, therefore, can be generated by a common bias in the weighting of evidence; namely, the dominance of strength over weight (5456).

The preceding analysis suggests that people assess their confidence in one of two competing hypotheses on the basis of their balance of arguments for and against this hypothesis, with insufficient regard for the quality of the data. This mode of judgment gives rise to overconfidence when people form a strong impression on the basis of limited knowledge and underconfidence when people form a moderate impression on the basis of extensive data (5576).

Note: Afterlife?

When predictability is reasonably high, experts are generally better calibrated than lay people. Studies of race oddsmakers (Griffith, 1949; Hausch, Ziemba, & Rubinstein, 1981; McGlothlin, 1956) and expert bridge players (Keren, 1987) are consistent with this conclusion. When predictability is very low, however, experts may be more prone to overconfidence than novices (5660).

14. Inside the Planning Fallacy: The Causes and Consequences of Optimistic Time Predictions

People are way overconfident in their plan making, showing an enormous optimism bias. Even when subjects had ample experience making plans about similar things, they ignored past performance in their judgments. Only the “recall-relevance” manipulation, described below, had decent effects debiasing.

Our work has been guided by two questions that have surely puzzled many people: Why is the underestimation of task times so common? Why don’t people learn from past experience and adjust their predictions accordingly? (5736)

Our third debiasing manipulation required participants to link their past experiences with their specific plans for an upcoming task. In this ”recall-relevance” manipulation, participants first indicated the date and time they would finish a computer assignment if they finished it as far before its deadline as they typically completed assignments (Buehler et al., 1994, Study 4). Second, they described a plausible scenario – based on their past experiences – that would result in their completing the computer assignment at their typical time. This procedure should prevent participants from either ignoring past experiences with similar tasks or discounting the relevance of those experiences (6169).

Tony Blair, British Prime Minister, illustrated this in his own paradoxical manner, proclaiming ”I don’t make predictions. I never have, and I never will” (6179).

15. Probability Judgement Across Cultures

East Asians have shown higher rates of overconfidence compared to people in Western cultures, with some exceptions, like Japan. This effect has persisted even when attempts to look for statistical artifacts or other explanations have been made. The leading hypothesis is a cultural tendency not to think in probabilities.

The sections of the chapter are organized according to the various questions that have been addressed: •  Are indications of greater Asian overconfidence mere artifacts of research procedure? •  Do the previously observed cross-cultural variations generalize – to other cultures, other target events besides the correctness of answers to categorical general-knowledge questions, and aspects of accuracy other than overconfidence? •  What explains the variations that exist? •  Finally, what do these variations imply for our understanding of fundamental principles of judgment and decision making and for practical affairs in arenas such as intercultural collaborations and commerce? (6227)

16. Durability Bias in Affective Forecasting

Human beings are overly pessimistic in their predictions of how long negative events will impact them. For many reasons, people recover from negative life events more quickly than predicted. The main culprit examined is the neglect of the emotional immune system. This is a partial explanation, but when negative events are impending or considered, we focus on the salient negative parts, whereas when the negative events have occurred, we begin to focus on other things, like how to meliorate the suffering, what steps to take next, etc., and the suffering is reduced.

But even if people can estimate with some accuracy the valence and intensity of the affect that future events will evoke, they may be less adept at estimating the duration of that affect – and it is often the prediction of duration that shapes the individual’s decisions (6682)

Common events typically influence people’s subjective well-being for little more than a few months (Suh, Fujita, & Diener, 1996; Wortman & Silver, 1989), and even uncommon events – such as losing a child in a car accident, getting cancer, becoming paralyzed, or being sent to a concentration camp – seem to have less impact on long-term happiness than one might naively expect (6692)

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