In more and more situations, artificially intelligent algorithms have to model humans' (social) preferences on whose behalf they increasingly make decisions. They can learn these preferences through the repeated observation of human behavior in social encounters. In such a context, do...

With Big Data, decisions made by machine learning algorithms depend on training data generated by many individuals. In an experiment, we identify the effect of varying individual responsibility for the moral choices of an artificially intelligent algorithm. Across treatments, we manipulated the...

Whereas economists have made extensive studies of the impact of levels of incentives on behavior, they have paid little attention to the effects of regularity and frequency of incentives. We contrasted three ways of rewarding participants in a real-effort experiment in which individuals had to...

We study the influence of risk and time preferences on trust and trustworthiness by conducting a field experiment in Vietnamese villages and by estimating the parameters of the Cumulative Prospect Theory and of quasi-hyperbolic time preferences. We find that while probability sensitivity or risk...

Variable pay creates a link between pay and performance but may also help firms in attracting more productive employees. Our experiment investigates the impact of performance pay on both incentives and sorting and analyzes the influence of repeated interactions between firms and employees on...

We devise an experiment to explore the effect of different degrees of competition on optimal contracts in a hidden-information context. In our benchmark case, each principal is matched with one agent of unknown type. In our second treatment, a principal can select one of three agents, while in a...

This paper extends the standard work effort model by allowing workers to interact through networks. We investigate experimentally whether peer performances and peer contextual effects influence individual performances. Two types of network are considered. Participants in Recursive networks are...