The Long Arc of Fairness: Formalisations and Ethical Discourse

Pola Schwöbel, Peter Remmers

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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.

Original languageEnglish
Title of host publicationProceedings of 5th ACM Conference on Fairness, Accountability, and Transparency
PublisherAssociation for Computing Machinery
Publication date21 Jun 2022
Pages2179-2188
ISBN (Electronic)9781450393522
DOIs
Publication statusPublished - 21 Jun 2022
Event5th ACM Conference on Fairness, Accountability, and Transparency - Virtual, Online, Korea, Republic of
Duration: 21 Jun 202224 Jun 2022

Conference

Conference5th ACM Conference on Fairness, Accountability, and Transparency
LocationVirtual, Online
Country/TerritoryKorea, Republic of
Period21/06/202224/06/2022

Keywords

  • Algorithmic decision making
  • Algorithmic fairness
  • Dynamic fairness modelling
  • Ethics of machine learning
  • Fairness metrics

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