Big data and the promise of bureaucratic efficiency

One of the fundamental questions of my PhD thesis has been to conceptualize privacy and surveillance in a way which not only describes the society we live in, but also explains why the current information society with its fetishization of data looks the way it does. I have looked to various theories on surveillance and socio-legal conceptualizations of information privacy to address this question, but I was never really satisfied with the answer.

Michel Foucault’s panopticon deals with the psychological effects of being under visible surveillance, yet does not adequately explain life in the era of databases and electronic surveillance. Philosopher Manuel DeLanda’s excellent War in the Age of Intelligent Machines (1991), addresses the intelligence community’s perverse data collection logic, but does not really expand on the political economy of surveillance. Oscar Gandy does a better job at that, but descriptions and theories based on the US context are not directly applicable in Europe.

Socio-legal theories and some communication research address how people perceive privacy, but it is increasingly difficult to connect ideal notions of privacy to what is actually happening in the world, and the gap between norms of privacy, data practices, and laws of privacy is growing ever wider.

During the past two years I’ve delved into the legislative process of the new data protection law in the EU, the General Data Protection Regulation, which will enter into force in May 2018. One of my earliest observations was the inaccessibility of the language and the complexity of the document that addresses a very basic human need: to be able to choose when one is out of sight. Instead, the end result is an intricate web of rules and exceptions to the collection of personal information with very vague references to actual perceptions of privacy.

After reading David Graeber’s Utopia of Rules I came to an insight that had previously existed only as a side note in my conceptualization of surveillance societies: the role of bureaucracies. Rather than thinking of data collection as an element of discipline in the Foucauldian sense, I started to think of data collection as part of the bureaucratic system’s inherent logic that is independent from the actual power of surveillance.

The utopian promise of big data is not that of control but of efficiency. The present logic of data maximization defies traditional ideals of data minimization according to which data can only be processed for a specific purpose. The collection of data points is such an essential part of modern bureaucracies, private and public alike, that its role in society is treated as a given. This is why attitudes to data collection and privacy are not divided along the public/private or even the left/right spectra but rather along the lines of strange bedfellows such as anarchism and libertarianism versus socialism and fascism. The goals are of course very different, but the means are similar.

By seeing questions of privacy and surveillance through this lens the GDPR’s legislative process started to make more sense to me. The discourses employed by corporate and public lobbyists were not really about control over information flows, nor were they about disciplinary power. They were about the promise of bureaucratic efficiency.

Data power conference (June, 22-23), part 1: Disconnect

I recently attended and presented at “Data Power” in what turns out was an excellent conference organized by the University of Sheffield. The conference had called upon academics to submit papers that approached the question of big data from a  societal (& critical) perspective. That being said, the conference papers were more often than not empirically founded and the presenters refrained from adapting a conspiratorial mindset, which might sometimes be the case when discussing big data.

Here are some of the key points that I picked up from attending the different panels:

Disconnect & Resignation / tradeoff fallacy

Stefan Larsson (Lund University) and Mark Andrejevic (Pomona College) both stressed that there is a disconnect between commercial claims that people happily trade their privacy for discounts and services and how people actually feel. In reality, people feel that they are “forced or bribed” to give up their data in order to access a service. Joseph Turow, Michael Hennessy and Nora Draper have recently published a survey on what they call the “tradeoff fallacy” which supports the disconnect and resignation hypothesis put forth by Larsson and Andrejevic.

Access rights are rarely respected

Clive Norris (University of Sheffield) and Xavier L’Hoiry (University of Leeds) had investigated if companies or the public sector (data controllers) actually respect that people have the right to access their own data according to current data protection legislation. Turns out, they don’t:

• “20 % of data controllers cannot be identified before submitting an access request;
• 43 % of requests did not obtain access to personal data;
• 56 % of requests could not get adequate information regarding third party data sharing;
• 71 % of requests did not get adequate information regarding automated decision making processes.”

Instead, the controllers consulted applied what Norris & L’Hoiry call “discourses of denial”, either questioning the rights themselves (we do not recognize them), falsely claiming that only law enforcement would have access to this data or even claiming that the researches were insane to make such a claim (why would you possibly want this information?). The most common response was, however, none at all. Deafening silence is an effective way to tackle unpopular requests.

Self-management of data is not a workable solution

Jonathan Obar (University of Ontario Institute of Technology & Michigan State University) showed that data privacy cannot possibly be better protected through individual auditing of how companies and officials use your personal data, calling this approach a “romantic fallacy”.

Even if data controllers would respect the so-called ARCO rights (access to data, rectification of data, cancellation of data & objection to data processing), it is far too difficult and time-consuming for regular citizens to manage their own data. Rather, Obar suggests that either data protection authorities (DPAs) or private companies would oversee how our data is used, a form of representative data management. The problem with this solution is of course the significant resources it would require.

There is no such thing as informed consent in a big data environment

Mark Andrejevic emphasized that data protection regulation and big data practice are based on opposing principles: big data on data maximization and data protection on data minimization. The notion of relevance does not work as a limiting factor for collecting data, since the relevance of data is only determined afterwords by aggregating data and looking for correlations. This makes informed consent increasingly difficult: what are we consenting to if we do not know the applications of the collection?