Rodrigo De La Fabián, Álvaro Jiménez-Molina, Francisco Pizarro Obaid
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引用次数: 1
Abstract
This article critically examines the emergence and uses of digital phenotyping in contemporary psychiatry. From an analysis of its discourses and practices, we show that digital phenotyping diffusion is directly related to its promise to solve some of the major impasses of the so-called "neuro-turn" in contemporary psychiatry. However, more than a new tool to address old objects of pre-digital psychiatry, we consider digital phenotyping as participating from a new onto-epistemological matrix, the “neuro-digital complex,” which entails the redefinition of psychiatric objects (e.g., brain and mind), diagnostic categories and procedures, subjectivities (e.g., users of mental health apps), and the emergence of a new regime of truth which promises to reveal the neuropsychological core at the individual scale. Despite this techno-utopia, digital phenotyping does not produce neutral mirrors for self-knowledge. We show that it resorts to population statistics, grounded truth data sets built with pre-digital neuropsychological assumptions, and human categorization processes. Nevertheless, we propose not to approach this gap as a misleading ideological fact but to emphasize its productive possibilities. From this perspective, the gap becomes the measure between whom we think we are and who we really are, working as a guide to conduct our lives in neuropsychological terms. Thus, we conclude that, rather than providing personalized diagnoses and treatments, digital phenotyping produces individualized pathways to normalization and neuropsychologization.
期刊介绍:
Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government.
BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices.
BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.