Towards a system-theoretic approach to algorithmic (un)fairness

Eva de Winkel, Jacqueline Kernahan, Roel Dobbe
Proceedings of Fourth European Workshop on Algorithmic Fairness, PMLR 294:303-309, 2025.

Abstract

Most scholarship on algorithmic fairness understands fairness as a static problem that is addressed in the design of the algorithm and its components, overlooking its embedding in complex contexts of use and governance. This static framing limits the applicability of existing approaches to algorithmic fairness in new domains, where stakeholders lack established fairness norms and analogies to other fields may fall short. This paper examines the challenges of operationalizing algorithmic fairness in new contexts through a system-theoretic lens. Using a case study on algorithmic systems for managing grid congestion in electrical distribution grids, we identify three core challenges: (1) anticipating situations of unacceptably unfair outcomes, (2) localizing contributing factors, and (3) identifying interventions and associated responsibilities to prevent such outcomes. Drawing on system safety, a discipline that has dealt with complex safety problems in algorithmic systems for decades, we propose concepts and tools to support a system-theoretic approach to fairness.

Cite this Paper

BibTeX
@InProceedings{pmlr-v294-winkel25a, title = {Towards a system-theoretic approach to algorithmic (un)fairness}, author = {de Winkel, Eva and Kernahan, Jacqueline and Dobbe, Roel}, booktitle = {Proceedings of Fourth European Workshop on Algorithmic Fairness}, pages = {303--309}, year = {2025}, editor = {Weerts, Hilde and Pechenizkiy, Mykola and Allhutter, Doris and Corrêa, Ana Maria and Grote, Thomas and Liem, Cynthia}, volume = {294}, series = {Proceedings of Machine Learning Research}, month = {30 Jun--02 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v294/main/assets/winkel25a/winkel25a.pdf}, url = {https://proceedings.mlr.press/v294/winkel25a.html}, abstract = {Most scholarship on algorithmic fairness understands fairness as a static problem that is addressed in the design of the algorithm and its components, overlooking its embedding in complex contexts of use and governance. This static framing limits the applicability of existing approaches to algorithmic fairness in new domains, where stakeholders lack established fairness norms and analogies to other fields may fall short. This paper examines the challenges of operationalizing algorithmic fairness in new contexts through a system-theoretic lens. Using a case study on algorithmic systems for managing grid congestion in electrical distribution grids, we identify three core challenges: (1) anticipating situations of unacceptably unfair outcomes, (2) localizing contributing factors, and (3) identifying interventions and associated responsibilities to prevent such outcomes. Drawing on system safety, a discipline that has dealt with complex safety problems in algorithmic systems for decades, we propose concepts and tools to support a system-theoretic approach to fairness.} }
Endnote
%0 Conference Paper %T Towards a system-theoretic approach to algorithmic (un)fairness %A Eva de Winkel %A Jacqueline Kernahan %A Roel Dobbe %B Proceedings of Fourth European Workshop on Algorithmic Fairness %C Proceedings of Machine Learning Research %D 2025 %E Hilde Weerts %E Mykola Pechenizkiy %E Doris Allhutter %E Ana Maria Corrêa %E Thomas Grote %E Cynthia Liem %F pmlr-v294-winkel25a %I PMLR %P 303--309 %U https://proceedings.mlr.press/v294/winkel25a.html %V 294 %X Most scholarship on algorithmic fairness understands fairness as a static problem that is addressed in the design of the algorithm and its components, overlooking its embedding in complex contexts of use and governance. This static framing limits the applicability of existing approaches to algorithmic fairness in new domains, where stakeholders lack established fairness norms and analogies to other fields may fall short. This paper examines the challenges of operationalizing algorithmic fairness in new contexts through a system-theoretic lens. Using a case study on algorithmic systems for managing grid congestion in electrical distribution grids, we identify three core challenges: (1) anticipating situations of unacceptably unfair outcomes, (2) localizing contributing factors, and (3) identifying interventions and associated responsibilities to prevent such outcomes. Drawing on system safety, a discipline that has dealt with complex safety problems in algorithmic systems for decades, we propose concepts and tools to support a system-theoretic approach to fairness.
APA
de Winkel, E., Kernahan, J. & Dobbe, R.. (2025). Towards a system-theoretic approach to algorithmic (un)fairness. Proceedings of Fourth European Workshop on Algorithmic Fairness, in Proceedings of Machine Learning Research 294:303-309 Available from https://proceedings.mlr.press/v294/winkel25a.html.

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