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Data doxa: The affective consequences of data practices

This paper explores the embedding of data producing technologies in people's everyday lives and practices. It traces how repeated encounters with digital data operate to naturalise these entities, while often blindsiding their agentive properties and the ways they get implicated in processes of...

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Bibliographic Details
Published in:Big data & society 2018-01, Vol.5 (1)
Main Author: Smith, Gavin JD
Format: Article
Language:English
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Summary:This paper explores the embedding of data producing technologies in people's everyday lives and practices. It traces how repeated encounters with digital data operate to naturalise these entities, while often blindsiding their agentive properties and the ways they get implicated in processes of exploitation and governance. I propose and develop the notion of ‘data doxa’ to conceptualise the way in which digital data – and the devices and platforms that stage data – have come to be perceived in Western societies as normal, necessary and enabling. The ‘data doxa’ concept also accentuates the enculturation of many individuals into a data sharing habitus which frames digital technologies in simplistic terms as (a) panaceas for the problems associated with contemporary life, (b) figures of progress and convenience, and (c) mediums of knowledge, pleasure and identity. I suggest that three types of data-based relations contribute to the formation of this doxic sensibility: fetishisation, habit and enchantment. Each of these relations come to mediate public understandings of digital devices and the data they generate, obscuring the multifaceted nature and hidden depths of data and their propensity to double up as technologies of exposure and discipline. As a result of this situation, imaginative educational programs and revamped regulatory frameworks are urgently needed to inform individuals about the contribution of data to the leveraging of value and power in today's digital economies, but also to protect them from experiencing data-based harms.
ISSN:2053-9517
2053-9517
DOI:10.1177/2053951717751551