Lessons Learned: Co-design of Trustworthy AI. Best Practice. By Helga Brogger, President of the Norwegian Society of Radiology

Mission: …Aid the development of designs with reduced end-user vulnerability…

-“…Socio-technical scenarios can be used to broaden stakeholders’ understanding of one’s own role in the technology, as well as awareness of stakeholders’ interdependence…”

– “…Recurrent, open-minded, and interdisciplinary discussions involving different perspectives of the broad problem definition….”

– “…The early involvement of an interdisciplinary panel of experts broadened the horizon of AI designers which are usually focused on the problem definition from a data and application perspective…”

– “…Consider the aim of the future AI system as a claim that needs to be validated before the AI system is deployed..”

-“…Involve patients at every stage of the design process … it is particularly important to ensure that the views, needs, and preferences of vulnerable and disadvantaged patient groups are taken into account to avoid exacerbating existing inequalities…”

Thank you, Roberto V. Zicari and the rest of the team for these insights!

— Helga Brogger, President of the Norwegian Society of Radiology

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

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 and Renee Wurth.

Front. Hum. Dyn. |Human and Artificial Collaboration for Medical Best Practices, July 13, 2021

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