The use of digital twins in healthcare

Socio-ethical benefits and socio-ethical risks

Bibliographic Data

ID8248656
AuthorsEugen Octav Popa (0000-0002-8214-8986, Wageningen University & Research, corresponding author), Mireille van Hilten (0000-0002-6665-9196, Ministry of Economic Affairs and Climate Policy), Elsje Oosterkamp, E B Oosterkamp (Ministry of Economic Affairs and Climate Policy), Marc-Jeroen Bogaardt, M J Bogaardt (Ministry of Economic Affairs and Climate Policy)
Year2021
Volume17
Issue1
Pages6-6
Publication date2021-12-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLife Sciences Society and Policy (JOURNAL)
Journal identifiersISSN: 2195-7819 • E-ISSN: 2195-7819
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1186/s40504-021-00113-x
PMID34218818
OpenAlexW3178150555
LanguageEN
Citations received16
References cited40

Anticipating the ethical impact of emerging technologies is an essential part of responsible innovation. One such emergent technology is the digital twin which we define here as a living replica of a physical system (human or non-human). A digital twin combines various emerging technologies such as AI, Internet of Things, big data and robotics, each component bringing its own socio-ethical issues to the resulting artefacts. The question thus arises which of these socio-ethical themes surface in the process and how they are perceived by stakeholders in the field. In this report we present the results of a qualitative study into the socio-ethical benefits and socio-ethical risks of using digital twins in healthcare. Employing insights from ethics of technology and the Quadruple Helix theory of innovation, we conducted desk research of white literature and 23 interviews with representatives from the four helixes: industry, research, policy and civil society. The ethical scan revealed several important areas where the digital twin can produce socio-ethical value (e.g., prevention and treatment of disease, cost reduction, patient autonomy and freedom, equal treatment) but also several important areas of socio-ethical risks (e.g., privacy and property of data, disruption of existing societal structures, inequality and injustice). We conclude with a reflection on the employed analytical tool and suggestions for further research

Autonomy · Beneficence · Big data · Digital health · Economic Justice · Engineering ethics · Health care · Injustice · Political science · Public relations · Sociology · Biomedical and Engineering Education · Computer Science · Digital Transformation in Industry · Engineering · Law · Psychology · Social Psychology · University-Industry-Government Innovation Models

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Open DOIOpen Access