Digitizing Dignity: Analyzing Digital Twins Through the Lens of Multidimensional Human Dignity

Abstract

In precision medicine, digital twins-virtual models of patients created using personalized data and advanced machine learning-are potentially changing healthcare by predicting health outcomes and guiding medical decisions. However, their use raises complex ethical questions, particularly concerning their relationship to human dignity. Patients often regard dignity as central to their healthcare experience, and failing to incorporate this principle into the design and application of digital twins risks undermining personal autonomy, misusing sensitive data, eroding patient-provider trust, and creating broader ethical challenges. This paper argues that digital twins are not mere data sets or predictive tools, but symbolic extensions of the dignity of the individuals they represent. Using David Kirchhoffer's multidimensional framework of human dignity, this study examines how digital twins engage with both absolute (inherent) and contingent (socially constructed) dimensions of dignity. The analysis begins by exploring the multidimensional concept of human dignity, followed by a discussion of how digital twins embody these dimensions, illustrated through examples such as digital brain twins, posthumous digital representations, and disability contexts. Finally, the paper addresses the ethical implications of these findings, emphasizing the moral responsibilities of researchers, developers, and clinicians to treat digital twins as representations of patient dignity, thereby ensuring these technologies advance healthcare without compromising the fundamental respect owed to every individual.

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