Modeling cultural and personality biases in decision-making

Abstract

Cultural, personality and affective biases in decision-making are well documented. This chapter describes a method for modeling multiple decision biases resulting from cultural effects, personality traits and affective states, within the context of a symbolic cognitive-affective agent architecture: the MAMID methodology and architecture. The approach emphasizes the role of affect in decision-biases, as the primary mediating factor of a wide range of biasing effects, and lends itself to exploring alternative mechanisms mediating a wide range of decision biases. The approach provides a uniform framework for modeling both content and processing biases, in terms of parameter vectors that control processing within the architecture modules. The effects of these biases are encoded in specific values of architecture parameters, which then influence the processing of the distinct architecture modules, including the architecture topology itself. The associated simulation environment enables the modeling of a wide variety of decision-makers, in terms of distinct personality and cultural profiles, and consequent affective profile and affect-induced decision-biases. The key contribution, and distinguishing feature, of the MAMID modeling approach is the parameter space it provides for representing the interacting effects of multiple types and sources of biases, and the potential of this approach for modeling the fundamental mechanisms that mediate decision-biases.