mlsanityData to 7 Oct 2026

The Long Arc of Fairness: Formalisations and Ethical Discourse

arXiv 2203.06038 ↗First posted 8 Mar 2022cs.LG cs.CYcited by 12

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Abstract (arXiv)

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.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 12 of its 44 references that are in the map. First posted on arXiv 8 Mar 2022.

Builds on

12 of 44 references.

References · 12

  1. 2016Equality of Opportunity in Supervised Learningcited by 2,000
  2. 2017Counterfactual Fairnesscited by 802
  3. 2016Fair prediction with disparate impact: A study of bias in recidivism prediction instrumentscited by 671
  4. 2019Measurement and Fairnesscited by 299
  5. 2017Avoiding Discrimination through Causal Reasoningcited by 191
  6. 2018Delayed Impact of Fair Machine Learningcited by 183
  7. 2019On the Apparent Conflict Between Individual and Group Fairnesscited by 126
  8. 2017On Formalizing Fairness in Prediction with Machine Learningcited by 65
  9. 2020How Do Fair Decisions Fare in Long-term Qualification?cited by 59
  10. 2018Downstream Effects of Affirmative Actioncited by 34
  11. 2019A Causal Bayesian Networks Viewpoint on Fairnesscited by 19
  12. 2021Allocating Opportunities in a Dynamic Model of Intergenerational Mobilitycited by 12

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Cited by year

Citing papers per year: 2022: 2; 2023: 4; 2024: 2; 2025: 4.

12 papers.