The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here:

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Photo of Shai Mulinari. Private photo.

Shai Mulinari

Associate Professor | Senior Lecturer

Photo of Shai Mulinari. Private photo.

Short-circuiting biology: Digital phenotypes, digital biomarkers, and shifting gazes in psychiatry


  • Shai Mulinari

Summary, in English

Digital phenotyping is a rapidly growing research field promising to transform how psychiatry measures, classifies, predicts, and explains human behavior. This article advances the social-scientific examination of digital phenotyping’s epistemology and knowledge claims. Drawing on the notion of a “neuromolecular gaze” in psychiatry since the 1960s, it suggests that digital phenotyping concerns a new psychiatric gaze – the “digital gaze”. Rather than privileging neuromolecular explanations, the digital gaze privileges the “deep” physiological, behavioral, and social “truths” afforded by digital technologies and big data. The article interrogates two concepts directing the digital gaze: “digital phenotype” and “digital biomarkers”. Both concepts make explicit an epistemic link between “the digital” and “the biological”. The article examines the soundness and construction of this link to, first, offer a “reality check” of digital phenotyping’s claims and, second, more clearly delineate and demarcate the digital gaze. It argues there is evidence of significant mis- and overstatements about digital phenotyping’s basis in biology, including in much-hyped psychiatric digital biomarker research. Rather than driving the biologization of digital traces, as some have suggested, digital mental health phenotyping so far seems mainly concerned with physiological, behavioral, and social processes that can be surveilled by means of digital devices.


  • Sociology

Publishing year





Big Data and Society

Document type

Journal article


SAGE Publications


  • Psychiatry
  • Information Systems, Social aspects




  • The New Scientific Revolution? AI and Big Data in Biomedicine


  • ISSN: 2053-9517