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; Renee Wurth

doi:10.3389/fhumd.2021.688152

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 HolmPedro 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

Research output: Contribution to journal › Journal article › Research › peer-review

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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.

Original language	English
Article number	688152
Journal	Frontiers in Human Dynamics
Volume	3
Number of pages	20
ISSN	2673-2726
DOIs	https://doi.org/10.3389/fhumd.2021.688152
Publication status	Published - Jul 2021

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Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion ClassifierFinal published version, 1.04 MBLicence: CC BY

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Zicari, R. V., Ahmed, S., Amann, J., Braun, S. A., Brodersen, J., Bruneault, F., Brusseau, J., Campano, E., Coffee, M., Dengel, A., Düdder, B., Gallucci, A., Gilbert, T. K., Gottfrois, P., Goffi, E., Haase, C. B., Hagendorff, T., Hickman, E., Hildt, E., ... Wurth, R. (2021). Co-design of a trustworthy AI system in healthcare: Deep learning based skin lesion classifier. Frontiers in Human Dynamics , 3, [688152]. https://doi.org/10.3389/fhumd.2021.688152

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; Gilbert, Thomas Krendl ; Gottfrois, Philippe ; Goffi, Emmanuel; Haase, Christoffer Bjerre; Hagendorff, Thilo; Hickman, Eleanore ; Hildt, Elisabeth; Holm, Sune ; Kringen, Pedro; Kühne, Ulrich; Lucieri, Adriano; Madai, Vince I. ; Moreno-Sánchez, Pedro A.; Medlicott, Oriana; Ozols, Matiss; Schnebel, Eberhard; Spezzatti, Andy; Tithi, Jesmin Jahan ; Umbrello, Steven; Vetter, Dennis; Volland, Holger; Westerlund, Magnus; Wurth, Renee.

In: Frontiers in Human Dynamics , Vol. 3, 688152, 07.2021.

Research output: Contribution to journal › Journal article › Research › peer-review

Zicari, RV, Ahmed, S, Amann, J, Braun, SA, Brodersen, J, Bruneault, F, Brusseau, J, Campano, E, Coffee, M, Dengel, A, Düdder, B, Gallucci, A, Gilbert, TK, Gottfrois, P, Goffi, E, Haase, CB, Hagendorff, T, Hickman, E, Hildt, E, Holm, S, Kringen, P, Kühne, U, Lucieri, A, Madai, VI, Moreno-Sánchez, PA, Medlicott, O, Ozols, M, Schnebel, E, Spezzatti, A, Tithi, JJ, Umbrello, S, Vetter, D, Volland, H, Westerlund, M & Wurth, R 2021, 'Co-design of a trustworthy AI system in healthcare: Deep learning based skin lesion classifier', Frontiers in Human Dynamics , vol. 3, 688152. https://doi.org/10.3389/fhumd.2021.688152

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 ; Gilbert, Thomas Krendl ; Gottfrois, Philippe ; Goffi, Emmanuel ; Haase, Christoffer Bjerre ; Hagendorff, Thilo ; Hickman, Eleanore ; Hildt, Elisabeth ; Holm, Sune ; Kringen, Pedro ; Kühne, Ulrich ; Lucieri, Adriano ; Madai, Vince I. ; Moreno-Sánchez, Pedro A. ; Medlicott, Oriana ; Ozols, Matiss ; Schnebel, Eberhard ; Spezzatti, Andy ; Tithi, Jesmin Jahan ; Umbrello, Steven ; Vetter, Dennis ; Volland, Holger ; Westerlund, Magnus ; Wurth, Renee. / Co-design of a trustworthy AI system in healthcare : Deep learning based skin lesion classifier. In: Frontiers in Human Dynamics . 2021 ; Vol. 3.

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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.",

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AU - Campano, Erik

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AU - Gilbert, Thomas Krendl

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AU - Schnebel, Eberhard

AU - Spezzatti, Andy

AU - Tithi, Jesmin Jahan

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Co-design of a trustworthy AI system in healthcare: Deep learning based skin lesion classifier

Abstract

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