Accuracy of confidence: Relationship with decision-making and decision outcomes in a complex social-ecological system

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When making decisions in risky and uncertain environments, the level of confidence humans have in their understanding of the situation influences decision-making, often more so than the level of understanding itself. This effect exists in areas as diverse as medicine, finance, and politics, as well as in group decision-making, where people also use other’s confidence to guide own decisions. For example, physicians who are overconfident about the accuracy of their diagnosis are less likely to seek out additional diagnostic information, bureaucrats who overestimate their level of expertise are more likely to endorse risk-taking policies, and people follow more the advices of more confident advice-givers. Despite being a prime example of risky decisions, uncertain environments, and naturally involving group decision-making, research on how humans collectively manage the use of common-pool resources, however, has largely neglected the potential influence of confidence in understanding. Here three fundamental questions will be addressed: When deciding about the use of a common resource, does own confidence in understanding the resource dynamics (development of the resource over time) predict decisions, even when controlling for understanding? Does other group members’ confidence predict own decisions, potentially even when their confidence is unwarranted? How do potentially confidence-driven decisions relate to groups’ success in sustainably managing the resource? A multi-experiment, multi-method approach will be taken to deliver robust answers by (i) analyzing existing experimental data where groups of people collectively managed a common resource under externally varied levels of risk; (ii) conducting a specifically designed follow-up experiment that allows for investigating changes in state-of the art measures of understanding and confidence as a function of group interaction; and (iii) a computational modeling approach where possible confidence-based decision strategies are formalized and compared against the behavioral data. In sum, the project will contribute to our understanding of what drives individual and group decisions on common-pool resource use, and will deliver solid estimates of the relative weights of understanding versus confidence in explaining these risky decisions.