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Apropos of “Speciesist bias in AI: how AI applications perpetuate discrimination and unfair outcomes against animals”
Item metadata
dc.contributor.author | Arandelovic, Oggie | |
dc.date.accessioned | 2023-01-11T10:30:07Z | |
dc.date.available | 2023-01-11T10:30:07Z | |
dc.date.issued | 2023-08-01 | |
dc.identifier | 282799705 | |
dc.identifier | f7e2a3fc-24d0-49c2-a692-6b1e4a9a9fba | |
dc.identifier.citation | Arandelovic , 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/s43681-022-00255-4 | en |
dc.identifier.issn | 2730-5961 | |
dc.identifier.uri | https://hdl.handle.net/10023/26732 | |
dc.description.abstract | The 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.extent | 3 | |
dc.format.extent | 619368 | |
dc.language.iso | eng | |
dc.relation.ispartof | AI & Ethics Journal | en |
dc.subject | Fairness | en |
dc.subject | Value of life | en |
dc.subject | Exploitation | en |
dc.subject | Computer vision | en |
dc.subject | Machine learning | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | BJ Ethics | en |
dc.subject | T-NDAS | en |
dc.subject | MCC | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | BJ | en |
dc.title | Apropos of “Speciesist bias in AI: how AI applications perpetuate discrimination and unfair outcomes against animals” | en |
dc.type | Journal item | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.identifier.doi | 10.1007/s43681-022-00255-4 | |
dc.description.status | Peer reviewed | en |
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