Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Tithi, Jesmin J."'
Autor:
Zicari, Roberto V., Amann, Julia, Bruneault, Frédérick, Coffee, Megan, Düdder, Boris, Hickman, Eleanore, Gallucci, Alessio, Gilbert, Thomas Krendl, Hagendorff, Thilo, van Halem, Irmhild, Hildt, Elisabeth, Kararigas, Georgios, Kringen, Pedro, Madai, Vince I., Mathez, Emilie Wiinblad, Tithi, Jesmin J., Vetter, Dennis, Westerlund, Magnus, Wurth, Renee
Publikováno v:
arXiv
This report is a methodological reflection on Z-Inspection. Z-Inspection is a holistic process used to evaluate the trustworthiness of AI-based technologies at different stages of the AI lifecycle. It focuses, in particular, on the identification and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d534eda229efce2e731c860fe5c98e30
Autor:
Zicari, Roberto V., Ahmed, Sheraz, Amann, Julia, Braun, Stephan A., Brodersen, John, Bruneault, Frédérick, Brusseau, James, Campano, Erik, Coffee, Megan, Dengel, Andreas, Düdder, Boris, Gallucci, Alessio, Krendl Gilbert, Thomas, Gottfrois, Philippe, Goffi, Emmanuel, Bjerre Haase, Christoffer, 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 J., Umbrello, Steven, Vetter, Dennis, Volland, Holger, Westerlund, Magnus, Wurth, Renee
Publikováno v:
Frontiers in Human Dynamics, 3
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, Holm, S, Kringen, P, Kühne, U, Lucieri, A, Madai, V I, Moreno-Sánchez, P A, Medlicott, O, Ozols, M, Schnebel, E, Spezzatti, A, Tithi, J J, 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, 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, Holm, S, Kringen, P, Kühne, U, Lucieri, A, Madai, V I, Moreno-Sánchez, P A, Medlicott, O, Ozols, M, Schnebel, E, Spezzatti, A, Tithi, J J, 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 . https://doi.org/10.3389/fhumd.2021.688152
Frontiers in Human Dynamics, 3:688152. Frontiers Media S.A.
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, Holm, S, Kringen, P, Kühne, U, Lucieri, A, Madai, V I, Moreno-Sánchez, P A, Medlicott, O, Ozols, M, Schnebel, E, Spezzatti, A, Tithi, J J, 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, 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, Holm, S, Kringen, P, Kühne, U, Lucieri, A, Madai, V I, Moreno-Sánchez, P A, Medlicott, O, Ozols, M, Schnebel, E, Spezzatti, A, Tithi, J J, 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 . https://doi.org/10.3389/fhumd.2021.688152
Frontiers in Human Dynamics, 3:688152. Frontiers Media S.A.
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 ana
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dc50ee4a393be40f411867b33aab1ff
Autor:
Zicari, Roberto V., Brusseau, James, Blomberg, Stig N., Collatz Christensen, Helle, Coffee, Megan, Ganapini, Marianna B., Gerke, Sara, Krendl Gilbert, Thomas, Hickman, Eleanore, Hildt, Elisabeth, Holm, Sune, Kühne, Ulrich, Madai, Vince I., Osika, Walter, Spezzatti, Andy, Schnebel, Eberhard, Tithi, Jesmin J., Vetter, Dennis, Westerlund, Magnus, Wurth, Renee, Amann, Julia, Vegard, Antun, Beretta, Valentina, Bruneault, Frédérick, Campano, Erik, Düdder, Boris, Gallucci, Alessio, Goffi, Emmanuel, Haase, Christoffer B., Hagendorff, Thilo, Kringen, Pedro, Möslein, Florian, Ottenheimer, Davi, Ozols, Matiss, Palazzani, Laura, Petrin, Martin, Tafur, Karin, Tørresen, Jim, Volland, Holger, Kararigas, Georgios
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d58e958408d28f212fc6ccbfbcc794f