Happiness as a Measure of Fairness

TL;DR

This paper introduces a new fairness framework based on happiness, measuring group utility from decision outcomes, which is both human-centered and mathematically rigorous, enabling efficient optimization and unification of existing fairness notions.

Contribution

The paper presents a novel happiness-based fairness framework that is scalable, unifies existing fairness definitions, and is grounded in a simple linear programming approach.

Findings

Efficient linear program computes optimal fair strategies.

Unifies multiple fairness definitions under a single framework.

Demonstrates practical effectiveness across diverse scenarios.

Abstract

In this paper, we propose a novel fairness framework grounded in the concept of happiness, a measure of the utility each group gains fromdecisionoutcomes. Bycapturingfairness through this intuitive lens, we not only offer a more human-centered approach, but also one that is mathematically rigorous: In order to compute the optimal, fair post-processing strategy, only a linear program needs to be solved. This makes our method both efficient and scalable with existing optimization tools. Furthermore, it unifies and extends several well-known fairness definitions, and our empirical results highlight its practical strengths across diverse scenarios.