City Research Online

Abstract

Evidence indicates that, when people forecast potential social risks, they are not only guided by facts, but often also by motivated reasoning. Here I apply a Bayesian decision framework to interpret the role of motivated reasoning during forecasting and assess some of the ensuing predictions. In two online studies, for each of a set of potential risky social events (such as economic crisis, rise of income inequality, and increase in violent crime), participants expressed judgments about (i) the probability that the event will occur, (ii) how negative occurrence of the event would be, and (iii) whether society is able to intervene upon the event. Supporting predictions of the Bayesian decision model, the analyses revealed that participants who deemed the events as more probable also assessed occurrence of the events as more negative and believed society to be more capable to intervene upon the events. Supporting the notion that a social threat is appraised as more probable when an intervention is deemed to be possible, these findings are compatible with a form of intervention bias. These observations are relevant for campaigns aimed at informing the population about potential social risks such as climate change, economic dislocations, and pandemics.

Publication Type:	Article
Additional Information:	This article has been published in its final form in American Journal of Psychology and it's available at: https://doi.org/10.5406/19398298.136.4.07
Publisher Keywords:	forecasting; risk; motivated reasoning; Bayesian; intervention bias; decision
Subjects:	B Philosophy. Psychology. Religion > BF Psychology H Social Sciences > HM Sociology H Social Sciences > HN Social history and conditions. Social problems. Social reform
Departments:	School of Health & Psychological Sciences > Psychology
SWORD Depositor:	Symplectic Administrator

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