Surveillance After Snowden by David Lyon

Author:David Lyon [Lyon, David]
Language: eng
Format: epub, azw3
Publisher: Wiley
Published: 2015-10-18T21:00:00+00:00

Big Data Capacities

The term ‘big data’ suggests that size is its key feature. Massive quantities of data about people and their activities are indeed generated by big data practices and many corporate and government bodies – not least the NSA, GCHQ and the rest – wish to capitalize on what is understood as the big data boom. However, the prominent idea of large size both yields important clues and, on its own, can mislead. While the capacities of big data practices (including the use of metadata) intensify surveillance by expanding interconnected datasets and analytical tools, this tells only a part of the story.

First, where does that ‘big’ data come from? Information researcher Rob Kitchin distinguishes between three kinds, each of which may be applied in surveillance contexts: directed, automated and volunteered.28 In the first, a human operator obtains the data, obvious examples being CCTV systems or an intelligence agency seeking, say, vehicle ownership records. In the second, the data are gathered without a human operator intervening; traces are recorded routinely from transactions with banks or consumer outlets and communications, using cellphones above all. As we have seen, there are several examples of this in NSA work. In the third, data are in a weak sense ‘volunteered’ by the user, who gives out information on social media sites and the like. Of course, social media users do not necessarily think of their activities in terms of volunteering data to third parties,29 but this is an accurate way of understanding surveillance data gathering in this context.

Understood this way, the capacities of big data surveillance take on some new meanings. The enthusiasm for commercial uses of big data is shared by those in the security field, thus stimulating further integration of these activities. In a big data intelligence context, the same data, gathered by internet companies for marketing, is increasingly used for different purposes, such as tracking terror suspects or environmental protesters. The change of context might well alter how social media users (the ‘data subjects’ in regulation-speak) might construe their privacy or how legal limits on secondary use might be stretched. But beyond this, the same commercial data may be given new meanings in the security realm, combined and connected in novel ways.

What the Snowden revelations show is that big data practices allow operators to infer individual or group characteristics relating to security from a context of consumer marketing. Data researcher Louise Amoore calls this kind of reasoning ‘data derivatives’.30 In the security-surveillance context such associations and links, however trivial and improbable, may be given new meanings that are cut off from the values that once made sense of them, and of course from the people whose activities generated them in the first place.

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