001005478 001__ 1005478
001005478 005__ 20231027114358.0
001005478 0247_ $$2doi$$a10.1017/S0963180122000688
001005478 0247_ $$2ISSN$$a0963-1801
001005478 0247_ $$2ISSN$$a1469-2147
001005478 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-01494
001005478 0247_ $$2pmid$$a36621773
001005478 0247_ $$2WOS$$aWOS:000911204600001
001005478 037__ $$aFZJ-2023-01494
001005478 082__ $$a610
001005478 1001_ $$0P:(DE-Juel1)176538$$aRathkopf, Charles$$b0$$eCorresponding author
001005478 245__ $$aLearning to Live with Strange Error: Beyond Trustworthiness in Artificial Intelligence Ethics
001005478 260__ $$bCambridge University Press$$c2023
001005478 3367_ $$2DRIVER$$aarticle
001005478 3367_ $$2DataCite$$aOutput Types/Journal article
001005478 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1692950260_15832
001005478 3367_ $$2BibTeX$$aARTICLE
001005478 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001005478 3367_ $$00$$2EndNote$$aJournal Article
001005478 520__ $$aPosition papers on artificial intelligence (AI) ethics are often framed as attempts to work out technical and regulatory strategies for attaining what is commonly called trustworthy AI. In such papers, the technical and regulatory strategies are frequently analyzed in detail, but the concept of trustworthy AI is not. As a result, it remains unclear. This paper lays out a variety of possible interpretations of the concept and concludes that none of them is appropriate. The central problem is that, by framing the ethics of AI in terms of trustworthiness, we reinforce unjustified anthropocentric assumptions that stand in the way of clear analysis. Furthermore, even if we insist on a purely epistemic interpretation of the concept, according to which trustworthiness just means measurable reliability, it turns out that the analysis will, nevertheless, suffer from a subtle form of anthropocentrism. The paper goes on to develop the concept of strange error, which serves both to sharpen the initial diagnosis of the inadequacy of trustworthy AI and to articulate the novel epistemological situation created by the use of AI. The paper concludes with a discussion of how strange error puts pressure on standard practices of assessing moral culpability, particularly in the context of medicine.
001005478 536__ $$0G:(DE-HGF)POF4-5255$$a5255 - Neuroethics and Ethics of Information (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001005478 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001005478 7001_ $$0P:(DE-Juel1)166268$$aHeinrichs, Bert$$b1
001005478 773__ $$0PERI:(DE-600)1499985-7$$a10.1017/S0963180122000688$$gp. 1 - 13$$p1 - 13$$tCambridge quarterly of healthcare ethics$$v-$$x0963-1801$$y2023
001005478 8564_ $$uhttps://juser.fz-juelich.de/record/1005478/files/Invoice_APC600372580.pdf
001005478 8564_ $$uhttps://juser.fz-juelich.de/record/1005478/files/learning-to-live-with-strange-error-beyond-trustworthiness-in-artificial-intelligence-ethics.pdf$$yOpenAccess
001005478 8767_ $$8APC600372580$$92022-12-28$$a1200187732$$d2023-01-11$$eHybrid-OA$$jZahlung erfolgt$$zGBP 2110,-
001005478 909CO $$ooai:juser.fz-juelich.de:1005478$$pdnbdelivery$$popenCost$$pVDB$$pdriver$$pOpenAPC$$popen_access$$popenaire
001005478 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176538$$aForschungszentrum Jülich$$b0$$kFZJ
001005478 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)166268$$aForschungszentrum Jülich$$b1$$kFZJ
001005478 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)166268$$a Uni Bonn$$b1
001005478 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5255$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001005478 9141_ $$y2023
001005478 915pc $$0PC:(DE-HGF)0000$$2APC$$aAPC keys set
001005478 915pc $$0PC:(DE-HGF)0001$$2APC$$aLocal Funding
001005478 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2022-11-23
001005478 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
001005478 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2022-11-23
001005478 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001005478 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2023-10-21$$wger
001005478 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)1180$$2StatID$$aDBCoverage$$bCurrent Contents - Social and Behavioral Sciences$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)0130$$2StatID$$aDBCoverage$$bSocial Sciences Citation Index$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bCAMB Q HEALTHC ETHIC : 2022$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2023-10-21
001005478 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2023-10-21
001005478 920__ $$lyes
001005478 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0
001005478 980__ $$ajournal
001005478 980__ $$aVDB
001005478 980__ $$aUNRESTRICTED
001005478 980__ $$aI:(DE-Juel1)INM-7-20090406
001005478 980__ $$aAPC
001005478 9801_ $$aAPC
001005478 9801_ $$aFullTexts