Aesthetics of algorithmic care: Designing alternative human-AI collaboration practices for digital phenotyping

Emergent technology of digital phenotyping (DP) for mental health promises to serve as a window to the lived experiences of patients through the collection and analysis of passive and interaction data from personal mobile devices and wearables. However, the need for standardization, formalization, and interoperability requires DP algorithms to employ generalizable digital biomarkers that convert culturally and socially specific expressions of health, well-being, and illness into uniform, detectable, and quantifiable measurements. Authors critical of DP usually employ ethical and epistemological critique, which often either delegating responsibility or provide limited suggestions. Design and HCI are notably lacking from these conversations and practices. I argue that pragmatic aesthetics, which is focused on experience and perception, could be a generative bridge between philosophy and design for DP. Moreover, newly emerged aesthetics of care could be conducive to developing a more beneficial sensibility of how posthuman (i.e. algorithmic) care could support people with mental distress. These aesthetic theories are inherently intersubjective, thus requiring establishing new collaborative alliances between doctors, patients, and technologies, as well as cultivating new care practices and mind-body-technology relations.