decision-making and willingness to share in the context of a personal financial decision. Content geared toward giving better … deception have externalities on other peoples' literacy and decision-making. Our work has important implications for policies …

We study the perfect Bayesian equilibrium of a model of learning over a general social network. Each individual … characterize the conditions under which there will be asymptotic learning -- that is, the conditions under which, as the social … unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some …

. In this paper, we explore the consequences of improved prediction in decision-making. To do so, we adapt existing models … of decision-making under uncertainty to account for the process of determining payoffs. We label this process of … on whether the improvements in prediction enable automated decision-making. We discuss the implications of improved …

. For all members of the Federal Open Market Committee (FOMC) since 1951, we estimate an adaptive learning rule based on …

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 …

investigate this claim using a simple model of Bayesian learning. Two individuals with different priors observe the same infinite … behavior in a range of circumstances. We illustrate how the type of learning outlined in this paper interacts with economic …

We examine how a social stigma of seeking information can inhibit learning. Consider a Seeker of uncertain ability who … whether a Seeker's ability is revealed to the paired Advisor, irrespective of the seeking decision. We find that low …