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dc.contributor.authorGundersen, Torbjørn
dc.contributor.authorBærøe, Kristine
dc.date.accessioned2022-12-28T10:01:43Z
dc.date.available2022-12-28T10:01:43Z
dc.date.created2022-04-09T11:20:31Z
dc.date.issued2022
dc.identifier.issn1353-3452
dc.identifier.urihttps://hdl.handle.net/11250/3039616
dc.description.abstractThis article examines the role of medical doctors, AI designers, and other stakeholders in making applied AI and machine learning ethically acceptable on the general premises of shared decision-making in medicine. Recent policy documents such as the EU strategy on trustworthy AI and the research literature have often suggested that AI could be made ethically acceptable by increased collaboration between developers and other stakeholders. The article articulates and examines four central alternative models of how AI can be designed and applied in patient care, which we call the ordinary evidence model, the ethical design model, the collaborative model, and the public deliberation model. We argue that the collaborative model is the most promising for covering most AI technology, while the public deliberation model is called for when the technology is recognized as fundamentally transforming the conditions for ethical shared decision-making.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleThe Future Ethics of Artificial Intelligence in Medicine: Making Sense of Collaborative Modelsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.source.articlenumber17en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.1007/s11948-022-00369-2
dc.identifier.cristin2016323
dc.source.journalScience and Engineering Ethicsen_US
dc.identifier.citationScience and Engineering Ethics. 2022, 28, 17.en_US
dc.source.volume28en_US
dc.source.issue2en_US


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