Please use this identifier to cite or link to this item: https://dl.eusset.eu/handle/20.500.12015/4186
Title: Accountability, Transparency and Explainability in AI for Healthcare
Authors: Moltubakk Kempton, Alexander
Vassilakopoulou, Polyxeni
Issue Date: 2021
Publisher: European Society for Socially Embedded Technologies (EUSSET)
metadata.dc.relation.ispartof: Infrahealth 2021 - Proceedings of the 8th International Conference on Infrastructures in Healthcare 2019
Series/Report no.: Reports of the European Society for Socially Embedded Technologies: vol. 5, no. 4
Abstract: The multiplicity of actors and the opacity of technologies involved in data management, algorithm crafting and systems ́ development for the deployment of Artificial Intelligence (AI) in healthcare create governance challenges. This study analyzes extant AI governance research in the context of healthcare focusing on accountability, transparency and explainability. We find that a significant part of this body of research lacks conceptual clarity and that the relationship between accountability, transparency and explainability is not fully explored. We also find that papers written back in the 1980s, identify and discuss many of the issues that are currently discussed. Up to today, most published research is only conceptual and brings contributions in the form of frameworks and guidelines that need to be further investigated empirically.
metadata.dc.identifier.doi: 10.18420/ihc2021_018
URI: https://dl.eusset.eu/handle/20.500.12015/4186
ISSN: 2510-2591
metadata.mci.conference.location: Kristiansand, Norway
metadata.mci.conference.date: 23-24 September 2021
Appears in Collections:InfraHealth 2021: Proceedings of the 8th International Conference on Infrastructures for Healthcare

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