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

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posted on 2021-01-01, 00:00 authored by 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
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.

History

Journal

Frontiers in Human Dynamics

Volume

3

Article number

688152

Pagination

1 - 20

Publisher

Frontiers Media SA

Location

Lausanne, Switzerland

eISSN

2673-2726

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

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