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dc.contributor.authorS Golpayegani, Seyedeh Delaramen
dc.contributor.authorHovsha, Joshuaen
dc.date.accessioned2023-01-03T10:15:39Z
dc.date.available2023-01-03T10:15:39Z
dc.date.created19-21 September 2022en
dc.date.issued2022en
dc.date.submitted2022en
dc.identifier.citationDelaram Golpayegani, Joshua Hovsha, Leon W. S. Rossmaier, Rana Saniei, Jana Misic, Towards a Taxonomy of AI Risks in the Health Domain, 2022 Fourth International Conference on Transdisciplinary AI (TransAI), Laguna Hills, CA, USA, 19-21 September 2022, IEEE, 2022, 1 - 8en
dc.identifier.otherYen
dc.descriptionPUBLISHEDen
dc.descriptionLaguna Hills, CA, USAen
dc.description.abstractThe adoption of AI in the health sector has its share of benefits and harms to various stakeholder groups and entities. There are critical risks involved in using AI systems in the health domain; risks that can have severe, irreversible, and life-changing impacts on people’s lives. With the development of innovative AI-based applications in the medical and healthcare sectors, new types of risks emerge. To benefit from novel AI applications in this domain, the risks need to be managed in order to protect the fundamental interests and rights of those affected. This will increase the level to which these systems become ethically acceptable, legally permissible, and socially sustainable. In this paper, we first discuss the necessity of AI risk management in the health domain from the ethical, legal, and societal perspectives. We then present a taxonomy of risks associated with the use of AI systems in the health domain called HART, accessible online at https://w3id.org/hart. HART mirrors the risks of a variety of different real-world incidents caused by use of AI in the health sector. Lastly, we discuss the implications of the taxonomy for different stakeholder groups and further research.en
dc.description.sponsorshipThe project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813497.en
dc.format.extent1en
dc.format.extent8en
dc.language.isoenen
dc.publisherIEEEen
dc.rightsYen
dc.subjectrisken
dc.subjectAI systemsen
dc.subjecthealthen
dc.subjectAI regulationen
dc.subjectethics of AIen
dc.subjectAI public policyen
dc.subjecttaxonomyen
dc.titleTowards a Taxonomy of AI Risks in the Health Domainen
dc.title.alternative2022 Fourth International Conference on Transdisciplinary AI (TransAI)en
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/sgolpaysen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/hovshajen
dc.identifier.rssinternalid248946en
dc.relation.ecprojectidinfo:eu-repo/grantAgreement/EC/FP7/813497
dc.rights.ecaccessrightsopenAccess
dc.subject.TCDTagAI Regulationen
dc.subject.TCDTagARTIFICIAL INTELLIGENCEen
dc.subject.TCDTagETHICS OF AIen
dc.subject.TCDTagKNOWLEDGE ENGINEERINGen
dc.subject.TCDTagPublic Policyen
dc.subject.TCDTagRISK MANAGEMENTen
dc.subject.TCDTagSEMANTIC WEBen
dc.subject.TCDTagTAXONOMYen
dc.status.accessibleNen
dc.contributor.sponsorEuropean Commissionen
dc.contributor.sponsorGrantNumber813497en
dc.identifier.urihttp://hdl.handle.net/2262/101926


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