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Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier

Authors :
Roberto V. Zicari
Sheraz Ahmed
Julia Amann
Stephan Alexander Braun
John Brodersen
Frédérick Bruneault
James Brusseau
Erik Campano
Megan Coffee
Andreas Dengel
Boris Düdder
Alessio Gallucci
Thomas Krendl Gilbert
Philippe Gottfrois
Emmanuel Goffi
Christoffer Bjerre Haase
Thilo Hagendorff
Eleanore Hickman
Elisabeth Hildt
Sune Holm
Pedro Kringen
Ulrich Kühne
Adriano Lucieri
Vince I. Madai
Pedro A. Moreno-Sánchez
Oriana Medlicott
Matiss Ozols
Eberhard Schnebel
Andy Spezzatti
Jesmin Jahan Tithi
Steven Umbrello
Dennis Vetter
Holger Volland
Magnus Westerlund
Renee Wurth
Source :
Frontiers in Human Dynamics, Vol 3 (2021)
Publication Year :
2021
Publisher :
Frontiers Media S.A., 2021.

Abstract

This paper documents how an ethically aligned co-design methodology ensures trustworthiness in the early design phase of an artificial intelligence (AI) system component for healthcare. The system explains decisions made by deep learning networks analyzing images of skin lesions. The co-design of trustworthy AI developed here used a holistic approach rather than a static ethical checklist and required a multidisciplinary team of experts working with the AI designers and their managers. Ethical, legal, and technical issues potentially arising from the future use of the AI system were investigated. This paper is a first report on co-designing in the early design phase. Our results can also serve as guidance for other early-phase AI-similar tool developments.

Details

Language :
English
ISSN :
26732726
Volume :
3
Database :
Directory of Open Access Journals
Journal :
Frontiers in Human Dynamics
Publication Type :
Academic Journal
Accession number :
edsdoj.2e64c8269c74bb6b1a62dd06362edd7
Document Type :
article
Full Text :
https://doi.org/10.3389/fhumd.2021.688152