Talks and Presentations

(Joint work with Cailin O’Connor and Hannah Rubin.)

Abstract. The study of social justice asks: what sorts of social arrangements are equitable ones?  But also: how do we derive the inequitable arrangements we often observe in human societies?  In particular, in spite of explicitly stated equity norms, categorical inequity tends to be the rule rather than the exception.  The cultural red king hypothesis predicts that differentials in group size may lead to inequitable outcomes for minority groups even in the absence of explicit or implicit bias. We test this prediction in an experimental context where subjects divided into groups engage in repeated play of a bargaining game. We ran 14 trials involving a total of 112 participants. The results of the experiments are significant and suggestive: individuals in minority groups do indeed end up receiving fewer resources than those in majority groups.

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(Joint work with Cole Randall Williams.)

Abstract. Typically, public discussions of questions of social import exhibit two important properties: (1) they are influenced by conformity bias, and (2) the influence of conformity is expressed via social networks. We examine how social learning on networks proceeds under the influence of conformity bias. In our model, heterogeneous agents express public opinions where those expressions are driven by the competing priorities of accuracy and of conformity to one’s peers. Agents learn, by Bayesian con-ditionalization, from private evidence from nature, and from the public declarations of other agents. Our key findings are that networks that produce configurations of social relationships that sustain a diversity of opinions empower honest communication and reliable acquisition of true beliefs, and that the networks that do this best turn out to be those which are both less centralized and less connected.

Abstract. The replicator dynamics and Moran process are the main deterministic and stochastic models of evolutionary game theory. These models are connected by a mean-field relationship—the former describes the expected behavior of the latter. However, there are conditions under which their predictions diverge. I demonstrate that the divergence between their predictions is a function of standard techniques used in their analysis, and of differences in the idealizations involved in each. My analysis reveals problems for stochastic stability analysis in a broad class of games. I also demonstrate a novel domain of agreement between the dynamics, and draw a broader methodological moral for evolutionary modeling.

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Abstract.Within the framework of evolutionary game theory, equilibrium concepts adapted from rational choice game theory are employed to identify the probable outcomes of evolutionary processes. Over the past several decades results have emerged in the literature demonstrating limitations to each of the proposed equilibrium concepts. These results rely on an undefined notion of evolutionary significance. We explicitly define evolutionary significance for evolutionary games. This definition enables an analysis of the success of equilibrium concepts across different models of evolution. We demonstrate that even under favorable assumptions as to the underlying dynamics and stability concept—the replicator dynamics and asymptotic stability—each equilibrium concept makes errors of either omission or comission; often both.

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