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‘I am not a number’: Conceptualising identity in digital surveillance
Technology in Society, Volume: 67, Start page: 101772
Swansea University Author: John Tucker
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Surveillance, now a commonplace phenomenon in everyday life, has been explored from various disciplines over three decades. Today's surveillance practices depend primarily upon many software technologies that collect, store and process personal data for the purposes of influence, management, pr...
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Surveillance, now a commonplace phenomenon in everyday life, has been explored from various disciplines over three decades. Today's surveillance practices depend primarily upon many software technologies that collect, store and process personal data for the purposes of influence, management, protection or detection. The identification and categorisation of data have thus emerged as the technical signature of surveillance. An individual has many identities belonging to different contexts of his/her life, but in this paper, we explore the relationship between surveillance and identity in virtual contexts only. We argue that an understanding of identity purely as data is fundamental to understanding surveillance. We propose abstract general definitions of surveillance and identity that together create a conceptual framework, capturing key features common to many disparate surveillance situations. Our work concludes that the essence of surveillance is that of a surveillance context, which is precisely and solely defined by the availability of data about the behaviour and identity of its entities. The data that distinguishes the entities of the context we call identifiers; we explore the creation, provenance, comparison and transformation of identifiers. Abstractly, surveillance is a process that tests for properties of data, and sorts identifiers into categories.
Accepted author manuscript available at https://researchportal.port.ac.uk/en/publications/i-am-not-a-number-conceptualising-digital-identity-in-digital-sur
Surveillance; Identifier; Monitoring; Software; Social sorting; Digital society
Faculty of Science and Engineering
This research was partially supported by the EPSRC project Data Release - Trust, Identity, Privacy and Security (EP/N028139/1, 2016–2020 and EP/N027825/1, 2016–2020).