Artificial Delegates and Absentee Fairness: Robustness of RCV and Proportional Systems with Partial Turnout

Shah et al. (2025) show that absenteeism can undermine fairness in sequential collective decisions, but propose “artificial delegates” to represent missing voters. This idea would extend their approach specifically to electoral contexts: simulating RCV and proportional elections with varying turnout, and deploying different strategies for artificial delegate assignment (e.g., based on past votes, demographic similarity, or learned preference models). The research would measure how these interventions affect minority representation, proportionality, and susceptibility to strategic manipulation. This work is novel because it directly tackles a recurring real-world problem—partial turnout—and rigorously evaluates how emerging AI tools can either mitigate or exacerbate fairness issues in voting systems.

References:

1. Artificial Delegates Resolve Fairness Issues in Perpetual Voting with Partial Turnout. Apurva Shah, Axel Abels, Ann Nowé, Tom Lenaerts (2025). International Conference on Climate Informatics.