Social Choice with Changing Preferences: Representation Theorems and Long-Run Policies

TL;DR

This paper extends social choice theory to dynamic decision-making by modeling changing group preferences as a Markov Decision Process, providing axiomatic characterizations of optimal policies aligned with utilitarian social welfare.

Contribution

It adapts classic social choice representation theorems to a dynamic setting and characterizes reward functions consistent with utilitarian social welfare in MDPs.

Findings

Axiomatic characterization of MDP reward functions aligned with social welfare

Identification of cases where social choice axioms may not yield optimal long-term outcomes

Framework for integrating social choice principles into automated decision systems

Abstract

We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main contribution is to show how classic representation theorems from social choice theory can be adapted to characterize optimal policies in this dynamic setting. We provide an axiomatic characterization of MDP reward functions that agree with the Utilitarianism social welfare functionals of social choice theory. We also provide discussion of cases when the implementation of social choice-theoretic axioms may fail to lead to long-run optimal outcomes.