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Using edge cases to disentangle fairness and solidarity in AI ethics

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Abstract

Principles of fairness and solidarity in AI ethics regularly overlap, creating obscurity in practice: acting in accordance with one can appear indistinguishable from deciding according to the rules of the other. However, there exist irregular cases where the two concepts split, and so reveal their disparate meanings and uses. This paper explores two cases in AI medical ethics, one that is irregular and the other more conventional, to fully distinguish fairness and solidarity. Then the distinction is applied to the frequently cited COMPAS versus ProPublica dispute in judicial ethics. The application provides a broader model for settling contemporary and topical debates about fairness and solidarity. It also implies a deeper and disorienting truth about AI ethics principles and their justification.

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Authors and Affiliations

  1. Philosophy Department, Pace University, New York, USA

    James Brusseau

  2. Signals and Interactive Systems Lab, Department of Computer Science and Information Engineering, University of Trento, Trento, Italy

    James Brusseau

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  1. James Brusseau
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Correspondence to James Brusseau.

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Brusseau, J. Using edge cases to disentangle fairness and solidarity in AI ethics. AI Ethics 2, 441–447 (2022). https://doi.org/10.1007/s43681-021-00090-z

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  • DOI: https://doi.org/10.1007/s43681-021-00090-z

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