The AI ethics of digital COVID-19 diagnosis and their legal, medical, technological, and operational managerial implications

  • The COVID-19 pandemic has given rise to a broad range of research from fields alongside and beyond the core concerns of infectiology, epidemiology, and immunology. One significant subset of this work centers on machine learning-based approaches to supporting medical decision-making around COVID-19 diagnosis. To date, various challenges, including IT issues, have meant that, notwithstanding this strand of research on digital diagnosis of COVID-19, the actual use of these methods in medical facilities remains incipient at best, despite their potential to relieve pressure on scarce medical resources, prevent instances of infection, and help manage the difficulties and unpredictabilities surrounding the emergence of new mutations. The reasons behind this research-application gap are manifold and may imply an interdisciplinary dimension. We argue that the discipline of AI ethics can provide a framework for interdisciplinary discussion and create a roadmap for the application of digitalThe COVID-19 pandemic has given rise to a broad range of research from fields alongside and beyond the core concerns of infectiology, epidemiology, and immunology. One significant subset of this work centers on machine learning-based approaches to supporting medical decision-making around COVID-19 diagnosis. To date, various challenges, including IT issues, have meant that, notwithstanding this strand of research on digital diagnosis of COVID-19, the actual use of these methods in medical facilities remains incipient at best, despite their potential to relieve pressure on scarce medical resources, prevent instances of infection, and help manage the difficulties and unpredictabilities surrounding the emergence of new mutations. The reasons behind this research-application gap are manifold and may imply an interdisciplinary dimension. We argue that the discipline of AI ethics can provide a framework for interdisciplinary discussion and create a roadmap for the application of digital COVID-19 diagnosis, taking into account all disciplinary stakeholders involved. This article proposes such an ethical framework for the practical use of digital COVID-19 diagnosis, considering legal, medical, operational managerial, and technological aspects of the issue in accordance with our diverse research backgrounds and noting the potential of the approach we set out here to guide future research.show moreshow less

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Metadaten
Author:Christina C. BartenschlagerGND, Ulrich M. GassnerGND, Christoph Römmele, Jens O. BrunnerORCiDGND, Kerstin Schlögl-FlierlORCiDGND, Paula ZiethmannGND
URN:urn:nbn:de:bvb:384-opus4-1126097
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/112609
ISSN:0933-3657OPAC
Parent Title (English):Artificial Intelligence in Medicine
Publisher:Elsevier
Place of publication:Amsterdam
Type:Article
Language:English
Year of first Publication:2024
Publishing Institution:Universität Augsburg
Release Date:2024/04/22
Tag:Artificial Intelligence; Medicine (miscellaneous)
Volume:152
First Page:102873
DOI:https://doi.org/10.1016/j.artmed.2024.102873
Institutes:Juristische Fakultät
Katholisch-Theologische Fakultät
Wirtschaftswissenschaftliche Fakultät
Katholisch-Theologische Fakultät / Systematische Theologie
Wirtschaftswissenschaftliche Fakultät / Institut für Betriebswirtschaftslehre
Juristische Fakultät / Institut für Öffentliches Recht
Medizinische Fakultät
Wirtschaftswissenschaftliche Fakultät / Institut für Betriebswirtschaftslehre / Lehrstuhl für Health Care Operations / Health Information Management
Katholisch-Theologische Fakultät / Systematische Theologie / Lehrstuhl für Moraltheologie
Juristische Fakultät / Institut für Öffentliches Recht / Juniorprofessur für Öffentliches Recht
Medizinische Fakultät / Universitätsklinikum
Nachhaltigkeitsziele
Nachhaltigkeitsziele / Ziel 3 - Gesundheit und Wohlergehen
Dewey Decimal Classification:1 Philosophie und Psychologie / 10 Philosophie / 100 Philosophie und Psychologie
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)