Purchasing Information to Reduce Uncertainty in Trajectory Prediction

Abstract

Previous studies show people underestimate the amount of uncertainty in predictive states. This experiment tested an implication of such findings: that people will be less likely (than optimal) to acknowledge their uncertainty, and hence less likely to purchase information that reduces future uncertainty. In a trajectory prediction task, participants had the opportunity to reduce uncertainty by a constant amount by purchasing either an expensive (bad deal), neutral-cost, or cheap (bargain) sensor. Participants were biased, relative to expected value theory, in integrating cost with uncertainty reduction in their decisions to purchase. In contrast to our primary hypothesis that they would place more decision weighting on reducing the cost of the purchase, than on gaining information, our results revealed the opposite. The findings are interpreted in the context of models of attribute salience in decision-making.