Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm - Bruynseels, Koen; Santoni de Sio, Filippo; van den Hoven, Jeroen (Frontiers in Genetics, 2018)
Personalized medicine uses fine grained information on individual persons, to pinpoint deviations from the normal. ‘Digital Twins’ in engineering provide a conceptual framework to analyse these emerging data-driven health care practices, as well as their implications for therapy, preventative care and human enhancement. Digital Twins stands for a specific engineering paradigm, where individual physical artefacts are paired with a digital model that dynamically reflects the status of that artefact. When applied to persons, Digital Twins are an emerging technology that builds in silico representations of an individual that dynamically reflect molecular status, physiological status and life style over time. We use Digital Twins as the hypothesis that one would be in the possession of very detailed bio-physical and lifestyle information of a person over time. This perspective redefines the concept of ‘normality’ or ‘health’, as a set of patterns that are regular for a particular individual, against the backdrop of patterns observed in the population. This perspective also will impact what is considered therapy and what is enhancement, as can be illustrated with the cases of the ‘asymptomatic ill’ and life extension via anti-ageing medicine. This changes are the consequence of how meaning is derived, in case measurement data is available. Moral distinctions namely will be based on patterns found in these data and the meanings that are grafted on these patterns. Ethical and societal implications of Digital Twins are explored. Digital Twins imply a data-driven approach to health care. This approach has the potential to deliver significant societal benefits, and can function as a social equalizer, by allowing for effective equalizing enhancement interventions. It can as well though be a driver for inequality, given the fact that a digital twin might not be an accessible technology for everyone, and given the fact that patterns identified across a population of digital twins can lead to segmentation and discrimination. This duality calls for governance as this emerging technology matures, including measures that ensure transparency of data usage and derived benefits, and data privacy.