Surveillance, Snowden, and Big Data: Capacities, consequences, critique

By David Lyon. Big Data & Society, 2014

612 citations recorded by the source corpus.

The Snowden revelations about National Security Agency surveillance, starting in 2013, along with the ambiguous complicity of internet companies and the international controversies that followed provide a perfect segue into contemporary conundrums of surveillance and Big Data. Attention has shifted from late C20th information technologies and networks to a C21st focus on data, currently crystallized in “Big Data.” Big Data intensifies certain surveillance trends associated with information technology and networks, and is thus implicated in fresh but fluid configurations. This is considered in three main ways: One, the capacities of Big Data (including metadata) intensify surveillance by expanding interconnected datasets and analytical tools. Existing dynamics of influence, risk-management, and control increase their speed and scope through new techniques, especially predictive analytics. Two, while Big Data appears to be about size, qualitative change in surveillance practices is also perceptible, accenting consequences. Important trends persist – the control motif, faith in technology, public-private synergies, and user-involvement – but the future-orientation increasingly severs surveillance from history and memory and the quest for pattern-discovery is used to justify unprecedented access to data. Three, the ethical turn becomes more urgent as a mode of critique. Modernity's predilection for certain definitions of privacy betrays the subjects of surveillance who, so far from conforming to the abstract, disembodied image of both computing and legal practices, are engaged and embodied users-in-relation whose activities both fuel and foreclose surveillance.

Subfields: Epidemiology, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/0e39603bff1d744077596e72920cf14d836f82ae

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Citations in the corpus

Social Injustice in Surveillance Capitalism (2017, background): “Personal data are actually diverted to very earthly data centres—massive, industrial-sized operations not unlike the NSA’s data storage facilities (Lyon 2014).”
Strategic opportunities (and challenges) of algorithmic decision-making: A call for action on the long-term societal effects of 'datification' (2015, background): “…it probably poses more issues for societies given the observed or potential social consequences; for instance, in terms of an individual’s privacy (Lyon, 2014) or in terms of the exploitation of the vulnerable – an issue that IS scholars seem not to have fully addressed as yet. first, (in…”
Digital education governance: data visualization, predictive analytics, and ‘real-time’ policy instruments (2016, positive): “…are becoming govern-mentalized, as ‘ open data ’ on citizens ’ activities contribute to ‘ digital governance ’ (Williamson 2014) and data-driven surveillance (Lyon 2014), while scholarly research is increasingly operationalized through dense ‘ knowledge infrastructures ’ of database technologies…”
Intimate Surveillance: Normalizing Parental Monitoring and Mediation of Infants Online (2017, background): “While the creation and aggregation of data as an amalgam of the surveyed subject has long been part of surveillance practices, the sheer magnitude of surveillance today, both online and offline, has squarely situated surveillance in the realm of big data analytics (Lyon, 2001, 2014).”
Indiscriminate mass surveillance and the public sphere (2016, positive): “The usefulness of such a program is also tied to advances in ‘‘big data’’ analytics, that is, search algorithms that make it possible to perform relatively quick analyses of large amounts of data (Lyon 2014).”
Digital subjectivation and financial markets: Criticizing Social Studies of Finance with Lazzarato (2016, methodology): “As has already been well established, this secrecy leads to normative problems concerning privacy, dataveillance, control creep, etc. (Boyd and Crawford, 2012: 673; Innes, 2001; Kitchin, 2014: 165– 183; Lyon, 2014).”
‘Hypernudge’: Big Data as a mode of regulation by design (2017, neutral): “But, unlike the disciplinary control emphasised by Foucault and epitomised by Bentham’s Panopticon (Lyon, 2014, p. 6), Big Data’s algorithmic control operates in a more subtle yet ‘seductive’ manner (Boyne, 2000) via continuous feedback loops based on an online user’s interactions, configuring…”