Standard
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
Harvard
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
APA
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
Vancouver
Zicari RV, Ahmed S, Amann J, Braun SA
, Brodersen J, Bruneault F et al.
Co-design of a trustworthy AI system in healthcare: Deep learning based skin lesion classifier.
Frontiers in Human Dynamics . 2021 Jul;3. 688152.
https://doi.org/10.3389/fhumd.2021.688152
Author
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.
Bibtex
@article{5877f957ad784f0e97e20200b4c331f6,
title = "Co-design of a trustworthy AI system in healthcare: Deep learning based skin lesion classifier",
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.",
author = "Zicari, {Roberto V.} and Sheraz Ahmed and Julia Amann and Braun, {Stephan Alexander} and John Brodersen and Fr{\'e}d{\'e}rick Bruneault and James Brusseau and Erik Campano and Megan Coffee and Andreas Dengel and Boris D{\"u}dder and Alessio Gallucci and Gilbert, {Thomas Krendl} and Philippe Gottfrois and Emmanuel Goffi and Haase, {Christoffer Bjerre} and Thilo Hagendorff and Eleanore Hickman and Elisabeth Hildt and Sune Holm and Pedro Kringen and Ulrich K{\"u}hne and Adriano Lucieri and Madai, {Vince I.} and Moreno-S{\'a}nchez, {Pedro A.} and Oriana Medlicott and Matiss Ozols and Eberhard Schnebel and Andy Spezzatti and Tithi, {Jesmin Jahan} and Steven Umbrello and Dennis Vetter and Holger Volland and Magnus Westerlund and Renee Wurth",
year = "2021",
month = jul,
doi = "10.3389/fhumd.2021.688152",
language = "English",
volume = "3",
journal = "Frontiers in Human Dynamics ",
issn = "2673-2726",
publisher = "Frontiers Media",
}
RIS
TY - JOUR
T1 - Co-design of a trustworthy AI system in healthcare
T2 - Deep learning based skin lesion classifier
AU - Zicari, Roberto V.
AU - Ahmed, Sheraz
AU - Amann, Julia
AU - Braun, Stephan Alexander
AU - Brodersen, John
AU - Bruneault, Frédérick
AU - Brusseau, James
AU - Campano, Erik
AU - Coffee, Megan
AU - Dengel, Andreas
AU - Düdder, Boris
AU - Gallucci, Alessio
AU - Gilbert, Thomas Krendl
AU - Gottfrois, Philippe
AU - Goffi, Emmanuel
AU - Haase, Christoffer Bjerre
AU - Hagendorff, Thilo
AU - Hickman, Eleanore
AU - Hildt, Elisabeth
AU - Holm, Sune
AU - Kringen, Pedro
AU - Kühne, Ulrich
AU - Lucieri, Adriano
AU - Madai, Vince I.
AU - Moreno-Sánchez, Pedro A.
AU - Medlicott, Oriana
AU - Ozols, Matiss
AU - Schnebel, Eberhard
AU - Spezzatti, Andy
AU - Tithi, Jesmin Jahan
AU - Umbrello, Steven
AU - Vetter, Dennis
AU - Volland, Holger
AU - Westerlund, Magnus
AU - Wurth, Renee
PY - 2021/7
Y1 - 2021/7
N2 - 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.
AB - 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.
U2 - 10.3389/fhumd.2021.688152
DO - 10.3389/fhumd.2021.688152
M3 - Journal article
VL - 3
JO - Frontiers in Human Dynamics
JF - Frontiers in Human Dynamics
SN - 2673-2726
M1 - 688152
ER -