Christoph March Reihenfolge der Bücher

Artificial intelligence (AI) is starting to pervade the economic and social life rendering strategic interactions with artificial agents more and more common. At the same time, experimental economic research has increasingly employed computer players to advance our understanding of strategic interaction in general. What can this strand of research teach us about an AI-shaped future? I review 90 experimental studies using computer players. I find that, in a nutshell, humans act more selfishly and more rational in the presence of computer players, and they are often able to exploit these players. Still, many open questions prevail.

We investigate how individual risk preferences affect the likelihood of selecting the more able contestant within a two-player Tullock contest. Our theoretical model yields two main predictions: First, an increase in the risk aversion of a player worsens her odds unless she already has a sufficiently large advantage. Second, if the prize money is sufficiently large, a less able but less risk averse contestant can achieve an equal or even higher probability of winning than a more able but more risk averse opponent. In a laboratory experiment we confirm both, the non-monotonic impact and the compensating effect of risk aversion on winning probabilities. Our results suggest a novel explanation for the gender gap and the optimality of limited monetary incentives in selection contests.

We provide new experimental evidence which suggests an asymmetric discouragement effect in lottery contests with heterogeneous abilities. Compared to a symmetric contest, subjects invest less effort when facing a stronger opponent, but they invest the same when facing a weaker opponent. Our results can be explained by a simple model of disappointment aversion.