The Long Arc of Fairness: Formalisations and Ethical Discourse

TL;DR

This paper reviews formal and ethical perspectives on fairness in algorithmic decision making, introduces a dynamic fairness model that considers long-term effects, and discusses its application to gender quota policies in Europe.

Contribution

It proposes a novel dynamic fairness modelling framework that integrates ethical goals, formal metrics, and downstream effects, bridging the gap between technical and ethical fairness discourse.

Findings

Dynamic fairness modelling aligns formal metrics with ethical considerations.

The framework helps navigate trade-offs in fairness interventions.

Early technical work demonstrates application to gender quota policies.

Abstract

In recent years, the idea of formalising and modelling fairness for algorithmic decision making (ADM) has advanced to a point of sophisticated specialisation. However, the relations between technical (formalised) and ethical discourse on fairness are not always clear and productive. Arguing for an alternative perspective, we review existing fairness metrics and discuss some common issues. For instance, the fairness of procedures and distributions is often formalised and discussed statically, disregarding both structural preconditions of the status quo and downstream effects of a given intervention. We then introduce dynamic fairness modelling, a more comprehensive approach that realigns formal fairness metrics with arguments from the ethical discourse. A dynamic fairness model incorporates (1) ethical goals, (2) formal metrics to quantify decision procedures and outcomes and (3) mid-term or long-term downstream effects. By contextualising these elements of fairness-related processes, dynamic fairness modelling explicates formerly latent ethical aspects and thereby provides a helpful tool to navigate trade-offs between different fairness interventions. To illustrate the framework, we discuss an example application -- the current European efforts to increase the number of women on company boards, e.g. via quota solutions -- and present early technical work that fits within our framework.