A pessimistic view of optimistic belief updating

Abstract

Received academic wisdom holds that human judgment is characterized by unrealistic optimism, the tendency to underestimate the likelihood of negative events and overestimate the likelihood of positive events. With recent questions being raised over the degree to which the majority of this research genuinely demonstrates optimism, attention to possible mechanisms generating such a bias becomes ever more important. New studies have now claimed that unrealistic optimism emerges as a result of biased belief updating with distinctive neural correlates in the brain. On a behavioral level, these studies suggest that, for negative events, desirable information is incorporated into personal risk estimates to a greater degree than undesirable information (resulting in a more optimistic outlook). However, using task analyses, simulations, and experiments we demonstrate that this pattern of results is a statistical artifact. In contrast with previous work, we examined participants' use of new information with reference to the normative, Bayesian standard. Simulations reveal the fundamental difficulties that would need to be overcome by any robust test of optimistic updating. No such test presently exists, so that the best one can presently do is perform analyses with a number of techniques, all of which have important weaknesses. Applying these analyses to five experiments shows no evidence of optimistic updating. These results clarify the difficulties involved in studying human 'bias' and cast additional doubt over the status of optimism as a fundamental characteristic of healthy cognition.

What is unrealistic optimism?

“…But here too there are methodological problems, because unless we know what base rate a person expected at the beginning, we do not know whether the base rate information they are subsequently given constitutes positive or negative information in their eyes (Shah, Harris, Bird, Catmur, & Hahn, 2016). So, for example, if John thinks that the population base rate for heart attacks is 25% and that because of family history, his own likelihood is 35%, then the information that the base rate is 30% is not desirable information, even though it may look that way when we only compare the risk assessment John made for himself and the base rate he was then provided with 2.…”

Optimistic update bias holds firm: Three tests of robustness following Shah et al.

“…Likelihood ratios express how diagnostic the evidence available to a participant is. Shah et al (2016), claim to show an optimistic update bias in the agents used in their simulation. However, the authors themselves note that if the likelihood ratios are greater than 1, the opposite pattern ought to ensue - greater updating for bad news compared to good news.…”

“…Yet Shah et al (2016), report finding an optimistic asymmetry for negative life events but a pessimistic asymmetry for positive life events. Their studies, however, fall into two methodological pitfalls that need to be guarded against when studying belief updating.…”

“…A recent study by Shah, Harris, Hahn, Catmur, and Bird (2016) has revisited the phenomenon of optimistic asymmetry in belief updating. The authors claim that an optimistic bias is unlikely, apart from very specific cases including sports fans and smokers.…”

“…In their paper (Shah et al, 2016), Shah et al outline an issue that has been described and resolved in two previous papers (Garrett and Sharot, 2014, Kuzmanovic et al, 2015). The basic claim (outlined previously in Garrett & Sharot, 2014) is that participants may hold one estimate regarding their own likelihood of experiencing an event and another regarding the likelihood for someone like them.…”