The memory people have of their past behavior is one of the main sources of information about themselves. To study whether people retrieve their memory self-servingly in social encounters, we designed an experiment in which participants play binary dictator games and then have to recall the...

Psychological game theory can contribute to renew the analysis of unethical behavior by providing insights on the nature of the moral costs of dishonesty. We investigate the moral costs of embezzlement in situations where donors need intermediaries to transfer their donations to recipients and...

Psychological game theory can contribute to renew the analysis of unethical behavior by providing insights on the nature of the moral costs of dishonesty. We investigate the moral costs of embezzlement in situations where donors need intermediaries to transfer their donations to recipients and...

A donation may have ambiguous costs or ambiguous benefits. In a laboratory experiment, we show that individuals use this ambiguity strategically as a moral wiggle room to behave less generously without feeling guilty. Such excuse-driven behavior is more pronounced when the costs of a donation -...

Studying the likelihood that individuals cheat requires a valid statistical measure of dishonesty. We develop an easy empirical method to measure and compare lying behavior within and across studies to correct for sampling errors. This method estimates the full distribution of lying when agents...

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 moral choices of an artificially intelligent algorithm. Across treatments, we manipulated the...

Humans shape the behavior of artificially intelligent algorithms. One mechanism is the training these systems receive through the passive observation of human behavior and the data we constantly generate. In a laboratory experiment with a sequence of dictator games, we let participants’...

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 moral choices of an artificially intelligent algorithm. Across treatments, we manipulated the...

Humans shape the behavior of artificially intelligent algorithms. One mechanism is the training these systems receive through the passive observation of human behavior and the data we constantly generate. In a laboratory experiment with a sequence of dictator games, we let participants' choices...

If individuals tend to behave like their peers, is it because of conformity, that is, the preference ofpeople to align behavior with the behavior of their peers; homophily, that is, the tendency ofpeople to bond with similar others; or both? We address this question in the context of an...