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dc.contributor.authorLee, Michelle Seng Ah
dc.contributor.authorFloridi, Luciano
dc.contributor.authorSingh, Jat
dc.date.accessioned2021-10-23T15:29:40Z
dc.date.available2021-10-23T15:29:40Z
dc.date.issued2020-07-31
dc.date.submitted2021-03-23
dc.identifier.issn2730-5953
dc.identifier.others43681-021-00067-y
dc.identifier.other67
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/329815
dc.description.abstractAbstract: 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.
dc.languageen
dc.publisherSpringer International Publishing
dc.subjectOriginal Research
dc.subjectAlgorithmic fairness
dc.subjectAlgorithmic ethics
dc.subjectMachine learning
dc.subjectKey ethics indicators
dc.subjectEthical trade-offs
dc.titleFormalising trade-offs beyond algorithmic fairness: lessons from ethical philosophy and welfare economics
dc.typeArticle
dc.date.updated2021-10-23T15:29:39Z
prism.endingPage544
prism.issueIdentifier4
prism.publicationNameAI and Ethics
prism.startingPage529
prism.volume1
dc.identifier.doi10.17863/CAM.77260
dcterms.dateAccepted2021-05-31
rioxxterms.versionofrecord10.1007/s43681-021-00067-y
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidSingh, Jat [0000-0002-5102-6564]
dc.identifier.eissn2730-5961


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