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dc.contributor.authorParfett, A
dc.contributor.authorTownley, S
dc.contributor.authorAllerfeldt, K
dc.date.accessioned2021-01-14T11:02:02Z
dc.date.issued2020-12-22
dc.description.abstractThe Bubonic Plague outbreak that wormed its way through San Francisco’s Chinatown in 1900 tells a story of prejudice guiding health policy, resulting in enormous suffering for much of its Chinese population. This article seeks to discuss the potential for hidden “prejudice” should Artificial Intelligence (AI) gain a dominant foothold in healthcare systems. Using a toy model, this piece explores potential future outcomes, should AI continue to develop without bound. Where potential dangers may lurk will be discussed, so that the full benefits AI has to offer can be reaped whilst avoiding the pitfalls. The model is produced using the computer programming language MATLAB and offers visual representations of potential outcomes. Interwoven with these potential outcomes are numerous historical models for problems caused by prejudice and recent issues in AI systems, from police prediction and facial recognition software to recruitment tools. Therefore, this research’s novel angle, of using historical precedents to model and discuss potential futures, offers a unique contribution.en_GB
dc.identifier.citationPublished online 22 December 2020en_GB
dc.identifier.doi10.1007/s00146-020-01120-w
dc.identifier.urihttp://hdl.handle.net/10871/124392
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.rights© The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_GB
dc.subjectArtifcial intelligenceen_GB
dc.subjectHealthcareen_GB
dc.subjectBiasen_GB
dc.subjectHistoryen_GB
dc.subjectMathematicsen_GB
dc.titleAI-based healthcare: a new dawn or apartheid revisited?en_GB
dc.typeArticleen_GB
dc.date.available2021-01-14T11:02:02Z
dc.identifier.issn0951-5666
dc.descriptionThis is the final version. Available on open access from Springer via the DOI in this recorden_GB
dc.identifier.journalAI and Societyen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-11-16
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-12-22
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-01-14T11:00:14Z
refterms.versionFCDVoR
refterms.dateFOA2021-01-14T11:02:09Z
refterms.panelBen_GB


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© The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's licence is described as © The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.