It's Not Fairness, and It's Not Fair: The Failure of Distributional Equality and the Promise of Relational Equality in Complete-Information Hiring Games

TL;DR

This paper critiques current fairness definitions in computational systems, highlighting their failure to address social relational inequalities, and proposes a new relational fairness concept for complete-information hiring games.

Contribution

It introduces a relational fairness notion in complete-information games, demonstrating the limitations of distributional fairness and proposing a new approach to social equality in computational systems.

Findings

Existing fairness measures fail to prevent social relational inequalities.

A self-confirming equilibrium can be relationally unfair despite satisfying distributional fairness.

The proposed relational fairness concept offers a new perspective for equitable computational systems.

Abstract

Existing efforts to formulate computational definitions of fairness have largely focused on distributional notions of equality, where equality is defined by the resources or decisions given to individuals in the system. Yet existing discrimination and injustice is often the result of unequal social relations, rather than an unequal distribution of resources. Here, we show how optimizing for existing computational and economic definitions of fairness and equality fail to prevent unequal social relations. To do this, we provide an example of a self-confirming equilibrium in a simple hiring market that is relationally unequal but satisfies existing distributional notions of fairness. In doing so, we introduce a notion of blatant relational unfairness for complete-information games, and discuss how this definition helps initiate a new approach to incorporating relational equality into computational systems.