Simulating theory and society: How multi-agent artificial intelligence modeling contributes to renewal and critique in social theory

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Abstract This article argues that a relatively novel methodology called multi-agent artificial intelligence modeling can play an important role in helping scholars fulfill eight desiderata for a “good” social scientific theory (conceptual clarity, logical consistency, empirical groundedness, parsimony, generativity, testability, insightfulness, and usefulness). The unique contributions of this methodology include its use of psychologically realistic agents in sociologically realistic networks that interact with each other and their simulated environment within an “artificial society.” These simulation tools utilize artificial intelligence in a way that enables scholars to causally generate the emergence of macro-level societal phenomena of interest from the micro-level behaviors and meso-level interactions of simulated agents that represent real world populations. These social digital twins can also integrate multiple social theories within a single causal architecture, providing a unique opportunity for the revolutionizing of our best theoretical frameworks.