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dc.contributor.authorKOIVISTO, Ida
dc.date.accessioned2020-06-04T13:15:55Z
dc.date.available2020-06-04T13:15:55Z
dc.date.issued2020
dc.identifier.issn1831-4066
dc.identifier.urihttps://hdl.handle.net/1814/67272
dc.description.abstractThe normative attractivity of transparency is beyond compare. No wonder it is one of the main principles in the EU’s General Data Protection Regulation. It also features in a majority of AI ethics codes. Transparency is called for because it is assumed that it will solve the so-called ‘black box problem’ (uncertainty about how inputs translate into outputs in algorithmic systems) and by so doing legitimize automated decision-making (computer-based decisionmaking without human influence; ADM). In this paper, the legitimizing effect of transparency in ADM is discussed. I argue that transparency cannot deliver in its quest to resolve the black box problem. The main claim is that transparency is inherently performative in nature and cannot but be so. This performativity goes against the promise of unmediated visibility, vested in transparency. As demonstrated, when transparency is brought into the context of ADM, its hidden functioning logic becomes visible in a new way.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherEuropean University Instituteen
dc.relation.ispartofseriesEUI AELen
dc.relation.ispartofseries2020/01en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectTransparencyen
dc.subjectAutomated decision-makingen
dc.subjectThe black box problemen
dc.subjectAI ethicsen
dc.subjectData protectionen
dc.titleThinking inside the box : the promise and boundaries of transparency in automated decision-makingen
dc.typeWorking Paperen
dc.rights.licenseAttribution 4.0 International*


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International