Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier - Zicari, Roberto V.; Ahmed, Sheraz; Amann, Julia; Braun, Stephan Alexander; Brodersen, John; Bruneault, Frédérick; Brusseau, James; Campano, Erik; Coffee, Megan; Dengel, Andreas; Düdder, Boris; Gallucci, Alessio; et al. (Frontiers in Human Dynamics, 2021)
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.