We examine how machine learning can be used to improve and understand human decision-making. In particular, we focus on … a decision that has important policy consequences. Millions of times each year, judges must decide where defendants will … await trial—at home or in jail. By law, this decision hinges on the judge's prediction of what the defendant would do if …

We examine how machine learning can be used to improve and understand human decision-making. In particular, we focus on … a decision that has important policy consequences. Millions of times each year, judges must decide where defendants will … await trial--at home or in jail. By law, this decision hinges on the judge's prediction of what the defendant would do if …

. We discuss how these findings relate to both dual-system and unitarysystem theories of decision making.We observe that … predictions of both recent dual-system and drift–diffusion models of the decision-making process are confirmed by our data and …

decision making. Fairness in the sense of equality has become an essential element of economic models aiming at explaining …

We report an experiment on a decision task by SAMUELSON and BAZERMAN (1985). Subjects submit a bid for an item with an … unknown value. A winner s curse phenomenon arises when subjects bid too high and make losses. Learning direction theory can … account for this. However, other influences on behaviour can also be identified. We introduce impulse balance theory to make …

Starting from the literature on decision processes in public choices, aim of the paper is to suggest an integrated … Municipality of Rome. The choice of sustainable mobility as a target of decision process lies on the fact that actually it is …