The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action - Les publications du Centre de recherche de l'École de Droit de Sciences Po Access content directly
Conference Papers Year : 2024

The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action

Abstract

Various metrics and interventions have been developed to identify and mitigate unfair outputs of machine learning systems. While individuals and organizations have an obligation to avoid discrimination, the use of fairness-aware machine learning interventions has also been described as amounting to ‘algorithmic positive action’ under European Union (EU) non-discrimination law. As the Court of Justice of the European Union has been strict when it comes to assessing the lawfulness of positive action, this would impose a significant legal burden on those wishing to implement fair-ml interventions. In this paper, we propose that algorithmic fairness interventions often should be interpreted as a means to prevent discrimination, rather than a measure of positive action. Specifically, we suggest that this category mistake can often be attributed to neutrality fallacies: faulty assumptions regarding the neutrality of (fairness-aware) algorithmic decision-making. Our findings raise the question of whether a negative obligation to refrain from discrimination is sufficient in the context of algorithmic decision-making. Consequently, we suggest moving away from a duty to ‘not do harm’ towards a positive obligation to actively ‘do no harm’ as a more adequate framework for algorithmic decisionmaking and fair ml-interventions.
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Dates and versions

hal-04565960 , version 1 (02-05-2024)

Licence

Attribution - NonCommercial - NoDerivatives

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Hilde Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy. The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), Jun 2024, Rio de Janeiro, Brazil. pp.11, ⟨10.1145/3630106.3659025⟩. ⟨hal-04565960⟩
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