Formalising trade-offs beyond algorithmic fairness: lessons from ethical philosophy and welfare economics
Publication Date
2020-07-31Journal Title
AI and Ethics
ISSN
2730-5953
Publisher
Springer International Publishing
Volume
1
Issue
4
Pages
529-544
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Lee, M. S. A., Floridi, L., & Singh, J. (2020). Formalising trade-offs beyond algorithmic fairness: lessons from ethical philosophy and welfare economics. AI and Ethics, 1 (4), 529-544. https://doi.org/10.1007/s43681-021-00067-y
Abstract
Abstract: There is growing concern that decision-making informed by machine learning (ML) algorithms may unfairly discriminate based on personal demographic attributes, such as race and gender. Scholars have responded by introducing numerous mathematical definitions of fairness to test the algorithm, many of which are in conflict with one another. However, these reductionist representations of fairness often bear little resemblance to real-life fairness considerations, which in practice are highly contextual. Moreover, fairness metrics tend to be implemented within narrow and targeted fairness toolkits for algorithm assessments that are difficult to integrate into an algorithm’s broader ethical assessment. In this paper, we derive lessons from ethical philosophy and welfare economics as they relate to the contextual factors relevant for fairness. In particular we highlight the debate around the acceptability of particular inequalities and the inextricable links between fairness, welfare and autonomy. We propose Key Ethics Indicators (KEIs) as a way towards providing a more holistic understanding of whether or not an algorithm is aligned to the decision-maker’s ethical values.
Keywords
Original Research, Algorithmic fairness, Algorithmic ethics, Machine learning, Key ethics indicators, Ethical trade-offs
Identifiers
s43681-021-00067-y, 67
External DOI: https://doi.org/10.1007/s43681-021-00067-y
This record's URL: https://www.repository.cam.ac.uk/handle/1810/329815
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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