Optimal nudging
- Frederick Callaway, Princeton University, Princeton, New Jersey, United States
- Mathew Hardy, Computational Cognitive Science Lab, Princeton University, Princeton, New Jersey, United States
- Tom Griffiths, Psychology & Computer Science, Princeton University, Princeton, New Jersey, United States
AbstractPeople's judgments and decisions often deviate from classical notions of rationality, incurring costs to both themselves and to society. In response, researchers have proposed using psychological theories to redesign decision problems in order to reduce the costs of people's biases. These modifications, or nudges, can have dramatic results and have been successfully applied to variety of domains. However, the formal underpinning of nudge theory is limited, and it is not always clear what the effect of a nudge will be before it is implemented. As a result, designing nudges can be time consuming and error-prone. In this paper, we propose an automatic method for deriving optimal nudges. The method is based on a resource-rational model, which assumes that people make decisions in a way that achieves a near-optimal tradeoff between the cost and benefits of deliberation. We then frame nudges as modifications to the costs of different cognitive operations, encouraging the cognitively frugal decision maker to consider some problem features over others. As a proof of concept, we apply the method to the Mouselab process-tracing paradigm, finding that optimal nudges lead participants to make better decisions with less cognitive effort.