Good Decisions or Bad Outcomes? A Model for Group Deliberation on Value-Laden Topics
Agent-based models present an ideal tool for interrogating the dynamics of communication and exchange. Such models allow individual aspects of human interaction to be isolated and controlled in a way that sheds new insight into complex behavioral phenomena. This approach is particularly valuable in settings beset by confounding factors and mixed empirical evidence. The political communication setting of deliberation is one such salient setting: in business, politics, and everyday life, individuals with varying opinions, experience, and information attempt to collaborate and make decisions. Empirical evidence suggests that such collaborative reasoning can lead to good decisions, yet there are numerous deliberative failures which may frequently cause groups to reach bad outcomes. Using the substantive setting of deliberation, this paper presents an agent-based model aimed at disambiguating the individual factors which influence decision-making conversations. We model this communicative process as a deliberative game of “giving and asking for reasons.” Agents share beliefs around possible policy initiatives and attempt to enact “good” policies through a process of mutual exchange and consideration. The model considers an interconnected policy landscape in which implementing or not implementing a policy mediates the value of other policies. Within this framework, the paper considers the impacts of three canonical failures of deliberation: limited cognitive capacity, group factions, and tendencies to make poor judgments when accepting or rejecting others’ views. We find that cognitive capacity can significantly decrease the ability of a group to reach a good decision. However, this effect appears to be mitigated for groups of opposing factions. Indeed, polarized groups do surprisingly well at identifying optimal policy solutions, suggesting that heterogeneous agents can achieve good outcomes if they are willing to talk and learn from each other.