‘I’ve left enough data’: Relations between people and data and the production of surveillance

Exploring emergent relations between data-producing individuals and their data products, this study aims to contribute to the ongoing scholarly discussion on agencies in data practices. It focuses on shifts in surveillance structure in the era of Big Data, in which the individual becomes both a subj...

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Bibliographic Details
Main Author: Hwankyung Janet Lee
Format: Article
Language:English
Published: SAGE Publishing 2023-01-01
Series:Big Data & Society
Online Access:https://doi.org/10.1177/20539517231173904
Description
Summary:Exploring emergent relations between data-producing individuals and their data products, this study aims to contribute to the ongoing scholarly discussion on agencies in data practices. It focuses on shifts in surveillance structure in the era of Big Data, in which the individual becomes both a subject and an object in the production of data surveillance. Drawing on the concept of the ‘dividual’, the study analyses data practices for a tracing system invented by the South Korean government during the COVID-19 pandemic, with findings from field research conducted with 11 research participants in various urban sites in Seoul. Highlighting how the tracing system positioned surveillance ‘in the hands of citizens’, the study exposes the complexities of the relations that the participants formed with the data they produced, and how they reflexively reappropriated their practices through alterations and deflections on the basis of their tacit knowledge and imaginaries concerning digital data and their constituent positions in the knowledge production system. The resultant expression of surveillance was directly shaped by the evolving relationship between the producers (participants) and products (digital data). The study proposes that an intersectional focus on surveillance and critical data studies, with close attention to ordinary people's relations with data, has the capacity to inquire into the politics of data more fully.
ISSN:2053-9517