Temporal Fairness in Multiwinner Voting

TL;DR

This paper introduces a unified framework for analyzing temporal fairness in multiwinner voting, addressing the challenges of repeated elections over time and connecting various existing approaches.

Contribution

It proposes a comprehensive framework that consolidates different models of temporal multiwinner voting and highlights future research directions.

Findings

Unified framework for temporal fairness in multiwinner voting

Connections established with existing models and approaches

Identification of gaps and opportunities for future research

Abstract

Multiwinner voting captures a wide variety of settings, from parliamentary elections in democratic systems to product placement in online shopping platforms. There is a large body of work dealing with axiomatic characterizations, computational complexity, and algorithmic analysis of multiwinner voting rules. Although many challenges remain, significant progress has been made in showing existence of fair and representative outcomes as well as efficient algorithmic solutions for many commonly studied settings. However, much of this work focuses on single-shot elections, even though in numerous real-world settings elections are held periodically and repeatedly. Hence, it is imperative to extend the study of multiwinner voting to temporal settings. Recently, there have been several efforts to address this challenge. However, these works are difficult to compare, as they model multi-period voting in very different ways. We propose a unified framework for studying temporal fairness in this domain, drawing connections with various existing bodies of work, and consolidating them within a general framework. We also identify gaps in existing literature, outline multiple opportunities for future work, and put forward a vision for the future of multiwinner voting in temporal settings.