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Digital twinning in medicine refers to the idea of simulating a person’s organs, muscles or perhaps their entire body, in order to arrive more effectively at accurate diagnoses, to make treatment recommendations that reflect chances of success and possible side-effects, and to better understand the long-term trajectory of an individual’s overall condition. Digital twins, in these ways, build on the recent movement toward personalised medicine,1 and they undoubtedly present us with exciting opportunities to advance our health. Of course, the opportunities are accompanied by newfound challenges—a common refrain in discussions surrounding emerging technologies.
In a recent article, Matthias Braun surveys numerous problems, including the precision of simulations, ownership and consent to the use of digital models, and issues of justice in assuring equitable access to novel medical systems.2 In particular, he places special emphasis on the notion of representation. According to Braun, proper representation naturally calls for correspondence—namely a precise model offering dynamic, real-time feedback as well as transparency, both for the patient and the practitioner, in terms of the data being employed. While technical challenges remain, these goals are quite clear and relatively uncontroversial. Where a host of questions arise, however, is in the discussion on the interaction between the represented persons and their simulations.
Alongside questions regarding ownership of one’s digital twin, Braun raises the concern that ‘giving …
Contributors DT is the sole author of this manuscript.
Funding DT is supported by the Bavarian Research Institute for Digital Transformation, on the project ‘Responsible Robotics: Tracing Ethical and Social Aspects of AI-Based Transformations in Healthcare Work and Knowledge Environments’ (PIs Alena Buyx, Sami Haddadin, and Ruth Müller) at the Technical University of Munich.
Competing interests None declared.
Provenance and peer review Commissioned; internally peer reviewed.
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