Show simple item record

Files in this item

Thumbnail

Item metadata

dc.contributor.authorArandelovic, Oggie
dc.date.accessioned2023-01-11T10:30:07Z
dc.date.available2023-01-11T10:30:07Z
dc.date.issued2023-08-01
dc.identifier282799705
dc.identifierf7e2a3fc-24d0-49c2-a692-6b1e4a9a9fba
dc.identifier.citationArandelovic , O 2023 , ' Apropos of “Speciesist bias in AI: how AI applications perpetuate discrimination and unfair outcomes against animals” ' , AI & Ethics Journal , vol. 3 , pp. 1021-1023 . https://doi.org/10.1007/s43681-022-00255-4en
dc.identifier.issn2730-5961
dc.identifier.urihttps://hdl.handle.net/10023/26732
dc.description.abstractThe present comment concerns a recent AI & Ethics article which purports to report evidence of speciesist bias in various popular computer vision (CV) and natural language processing (NLP) machine learning models described in the literature. I examine the authors’ analysis and show it, ironically, to be prejudicial, often being founded on poorly conceived assumptions and suffering from fallacious and insufficiently rigorous reasoning, its appeal in large part relying on the extant consensus in the community.
dc.format.extent3
dc.format.extent619368
dc.language.isoeng
dc.relation.ispartofAI & Ethics Journalen
dc.subjectFairnessen
dc.subjectValue of lifeen
dc.subjectExploitationen
dc.subjectComputer visionen
dc.subjectMachine learningen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectBJ Ethicsen
dc.subjectT-NDASen
dc.subjectMCCen
dc.subject.lccQA75en
dc.subject.lccBJen
dc.titleApropos of “Speciesist bias in AI: how AI applications perpetuate discrimination and unfair outcomes against animals”en
dc.typeJournal itemen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doi10.1007/s43681-022-00255-4
dc.description.statusPeer revieweden


This item appears in the following Collection(s)

Show simple item record