Digital Phenotyping as Felt Informatics: Designing AI-Based Mental Health Diagnostic Tools Through Aesthetics

With psychiatry lagging behind other medical fields in terms of innovation in instruments and methods, AI provides it an opportunity to catch up. Advocates of digital phenotyping promise to provide an objective tool that detects symptoms by analysing data from personal devices. We argue that digital phenotyping requires a more reflexive and critical approach to its design and an alignment of the clinicians’ interests in generating relevant evidence with the needs of service users who seek tools to manage their condition. We propose a felt informatics approach, situating digital phenotyping design within the problem space of pragmatist aesthetics. Within this perspective, felt life becomes a central object and a site for digital phenotyping design. This paper reveals the ways diagnostic data mediates mental ill health experience, emphasises the cultivation of aesthetic sensibility as a fundamental element of digital phenotyping and includes design considerations for practitioners and researchers.