Stories of data breaches and privacy violations dot the news landscape on a near daily basis. This week, security vendor Carbon Black published their Australian Threat Report based on 250 interviews with tech executives across multiple business sectors. 89% Of those interviewed reported some form of data breach in their companies. That’s almost everyone. These breaches represent both a business problem and a social problem. Privacy violations threaten institutional and organizational trust and also, expose individuals to surveillance and potential harm.
But “breaches” are not the only way that data exposure and privacy violations take shape. Often, widespread surveillance and exposure are integral to technological design. In such cases, exposure isn’t leveled at powerful organizations, but enacted by them. Legacy services like Facebook and Google trade in data. They provide information and social connection, and users provide copious information about themselves. These services are not common goods, but businesses that operate through a data extraction economy.
I’ve been thinking a lot about the cost-benefit dynamics of data economies and in particular, how to grapple with the fact that for most individuals, including myself, the data exchange feels relatively inconsequential or even mildly beneficial. Yet at a societal level, the breadth and depth of normative surveillance is devastating. Resolving this tension isn’t just an intellectual exercise, but a way of answering the persistent and nagging question: “why should I care if Facebook knows where I ate brunch?” This is often wrapped in a broader “nothing to hide” narrative, in which data exposure is a problem only for deviant actors.
Nothing to hide narratives derive from a fundamental obfuscation of how data works at scale. “Opt-out” and even “opt-in” settings rely on a denatured calculus. Individuals solve for data privacy as a personal trouble when in contrast, it is very much a public issue.
Data privacy is a public issue because data are sui generis—greater than the sum of their parts. Data trades don’t just affect individuals, but collectively generate an encompassing surveillance system. Most individual data are meaningless on their own. Data become valuable—and powerful—through aggregation. Singular datum are thus primarily effectual when they combine into plural data. In other words, my data comes to matter in the context of our data. With our data, patterns are rendered perceptible and those patterns become tools for political advantage and economic gain.
Individuals can trade their data for services which, at the individual level, make for a relatively low cost (and even personally advantageous) exchange. Accessing information through highly efficient search engines and connecting with friends, colleagues, communities, and fellow hobbyists are plausibly worth as much or more than the personal data that a user “pays” for this access and connection. At the individual level, data often buy more than they cost.
However, the costs of collective data are much greater, and include power transfers to state and corporate actors. Siva Vaidhyanathan is excellent on this point. In his book Anti-Social Media: How Facebook Disconnects us and Undermines Democracy Vaidhyanathan demonstrates how the platform’s norm of peer-sharing turns to peer surveillance, turns, though mass data collection, to corporate and state surveillance. Facebook collects our data and gifts it back to us in the form of pleasing News Feeds. Yet in turn, Facebook sells our data for corporate and political gain. This model only works en masse . Both News Feeds and political operatives would be less effective without the data aggregates, collected through seemingly banal clicks, shares, and key strokes.
Individual privacy decisions are thus not just personal choices and risks, nor even network-based practices. Our data are all wrapped up in each other. Ingeniously, big tech companies have devised a system in which data exchange benefits the individual, while damaging the whole. Each click is a contribution to that system. Nobody’s data much matters, but everybody’s data matters a lot.
Jenny Davis is on Twitter @Jenny_L_Davis
Headline Pic Via: Source