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Health-Related Digital Autonomy. A Response to the Commentaries

The COVID-19 pandemic has been a threat to both physical and mental health. The spreading disease and its impacts, the containment measures and the way all of our lives have dramatically changed have caused psychological stress and distress, aggravating existing mental health issues and evoking new ones. Mental healthcare, however, has been manifoldly hampered by the need for social distancing, tightened hygiene standards, and shifted medical and political priorities. According to the World Health Organization, critical mental health services have been disrupted or halted in almost every country. At the same time, an increased demand for mental health services highlights the urgent need to maintain and expand accessible, efficient and safe services for the prevention, diagnosis and treatment of mental issues (World Health Organization 2020). On a global scale, depression rates among the most prevalent and harmful of all diseases. Digital healthcare applications, such as depression detectors based on artificial intelligence (AI) and social media data, might be auxiliary tools for traditional mental healthcare in pandemic and post-pandemic times. However, they do come along with serious ethical challenges that have to be met if a responsible usage is intended. We chose a bioethical approach to investigate the ethical implications of AI depression detectors (AIDDs) regarding social media users’ health-related autonomy (Laacke et al. 2021). Machine learning models that process data from Instagram (Reece and Danforth 2017) and Twitter (Reece et al. 2017) served as application examples for AIDDs. Assuming a medical purpose of these systems, we introduced four plausible usage scenarios and emphasized that automatic screening raises the most significant ethical concerns. We described the relevant characteristics of AIDDs and differences between the digital context of social media and traditional healthcare settings. Against this background, we critically discussed the normative criteria for patient autonomy as developed by Beauchamp and Childress (2019). “Intentionality,” “understanding” and “independence/non-control” remain core requirements in our model for an ethical use of AIDDs. Due to conceptual restrictions, we extended the classical approach to patient autonomy by the “availability of alternatives” and “empowerment.” The result is a concept of healthrelated digital autonomy (HRDA) that, as far as we can see, more appropriately addresses the specific ethical challenges linked with AIDDs and the digital context of social media. The HRDA may serve as (one element of) an ethical framework for various stakeholders involved in regulating, developing, implementing and evaluating AIDDs and comparable digital healthcare applications. We are grateful and appreciate the instructive and well-informed commentaries we received. The commentaries once again illustrate the high level of complexity and importance of the issue we are facing. All commentators have made a significant contribution to the discourse. They help us to appraise the strengths and weaknesses of our concept better, uncover sources of potential misunderstandings, find connections to other fields of discussion and identify relevant desiderata. We would also like to thank The American Journal of Bioethics for providing this valuable format of discussion! The critical objections raised by the commentators might be summarized as follows: some commentators address conceptual aspects of the bioethical approach we present. Ploug and Holm (2021) argue that the clinical perspective chosen is too narrow to take all ethically relevant aspects of AI profiling technologies into account. Furthermore, Ranisch (2021) reflects on the relationship between biomedical and digital ethics and notes that while adapting bioethical principles to