Adversarial Decision Making: Choosing between Models Constructed by Interested Parties

In this article, we characterize adversarial decision making as a choice between competing interpretations of evidence (models) constructed by interested parties. We show that if a court cannot perfectly determine which party's model is more likely to have generated the evidence, then adversaries face a trade-off: a model farther from the most likely interpretation has a lower probability of winning but also a higher payoff following a win. We characterize an equilibrium in which both adversaries construct optimal models, and we use the characterization to compare adversarial decision making to an inquisitorial benchmark. We find that adversarial decisions are biased and that the bias favors the party with the less likely, and more extreme, interpretation of the evidence. Court bias disappears as the court is better able to distinguish between the likelihoods of the competing models or as the amount of evidence grows.