How robust is the optimistic update bias for estimating self-risk and population base rates?

Humans hold unrealistically optimistic predictions of what their future holds. These predictions are generated and maintained as people update their beliefs more readily when receiving information that calls for adjustment in an optimistic direction relative to information that calls for adjustment in a pessimistic direction. Thus far this update bias has been shown when people make estimations regarding the self. Here, we examine whether asymmetric belief updating also exists when making estimations regarding population base rates. We reveal that while participants update beliefs regarding risk in the population in an asymmetric manner, such valence-dependent updating of base rates can be accounted for by priors. In contrast, we show that optimistic updating regarding the self is a robust phenomenon, which holds even under different empirical definitions of desirable information

Overconfident people are more exposed to “black swan” events: a case study of avalanche risk

Overconfidence is a well-established bias in which someone’s subjective confidence in their own judgment is systematically greater than their objective accuracy. There is abundant anecdotal evidence that overconfident people increase their exposure to risk. In this paper, we test whether overconfident backcountry skiers underestimate the probability of incurring a snow avalanche accident. An avalanche accident is a typical “black swan” event as defined by Taleb (The black swan: the impact of the highly improbable, Random House, New York, 2007) because it has a very low probability of occurring but with potentially dramatic consequences. To consider black swan events when studying overconfidence is particularly important, in light of previous findings on the role of overconfidence when feedbacks on tasks previously performed are inconclusive and infrequent. We run our test by measuring individual overconfidence using standard tools from the literature and then use a random effect logit model to measure its effect on the probability to take the ski route. We show that (1) overconfidence is widespread in our sample; (2) practitioners who are more prone to overestimate their knowledge are also more likely to take risks associated with a ski trip under the threat of avalanche danger, a result robust to a set of specification tests we perform. This suggests that overconfident people are more exposed to black swan events, by taking a risky decision that can bring about fatal consequences