Following Bijker’s suggestions, I have devoted considerable time and space to understanding how Big Data technologies works, and especially to the functions of predictive policing. As noted, several levels of meaning may be assigned to any form of technology. Existing at the most basic level is the technology as a pure material artefact. Here one finds the infamous black box; a technological artefact as advanced as Big Data can seem impenetrable at first sight. In the previous chapters, I have attempted to outline the inner workings of the
algorithms in an understandable manner. My focus in the following analysis, then, will lean towards the other two conceptual levels of technology, concerning myself with the process of technology in the making and the way in which actors and groups identify and constitute themselves in relation to the artefact. Following the SCOT approach, my analysis begins with identifying relevant social groups and the ways in which they relate to the technology. It is
29 This correspondence and meeting helped me attain an overview over the situation of predictive policing in a
Norwegian context (which is, as noted, sparse), and gave me pointers on fruitful ways to approach the technology. As the correspondence was informal, I have not used it as a direct source for my thesis.
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through the perception and meanings assigned by these groups that the different facets, or the interpretative flexibility, of the technology reveals itself.
Bijker recommends taking technologically controversial artefacts as a point of departure, noting that “(…) instability is more revealing about a system’s characteristics than stability” (Bijker 1993, 119). Points of disagreement, not only about solutions, but about which
problems the artefact is meant to solve, is a fertile venue for exploring the process of the social shaping of technology. Since social groups are shaped in their interactions around the artefact, the mapping of prominent actors who are participating in the discussion is a useful first step. In a departure from the SCOT method, I have chosen to focus on the process in which actors form and mobilize through social groups. Drawing on ANT, specifically the theory of group formation presented by Michel Callon, I will identify key actors who act as system builders, and look at how they mobilize in order to shape the debate (and
consequently, the technology itself).
Identifying and exploring the key actors and social groups, meaning those playing important roles in the shaping of predictive policing, will constitute my first research question. For this purpose, I have reviewed papers from criminologists30, professors of law31, public policy researchers32, and communication scholars33. This variety of points of view have allowed me to reach a broader understanding of the different facets and perceived problems of predictive policing, and by paying attention to frequently cited articles, some main actors have revealed themselves. I have also examined articles published in police journals34, press releases and other material from commercial actors35, news articles, and interest groups such as human rights and civil liberties organizations.36 By tracing the different arguments and the ways that social groups mobilize around the technology, I aim to answer my second research question, namely identifying which closure mechanisms are being used in attempt to stabilize or
30 For example Willis and Mastrofski (2011), Byrne and Marx (2011) 31 Zarsky (2011), Ferguson (2012)
32 Yiu (2012)
33 Moses and Chan (2014) 34 Beck (2009), Inderhaug (2013) 35 IBM (2012), PredPol (2014) 36 PrivacySOS (n/d)
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destabilize predictive policing. Finally, I will bring the conceptual level up to a broader political context, drawing on Dewey’s theory of the public, which constitutes itself when conflicting issues arise in a technological artefact. This constitutes my third research question; in which I explore how political issues are embedded in technologies. By answering these three research questions, I will have covered the technological, the social, and the political aspects of predictive policing, demonstrating how they are all constituted around and embedded in the artefact.
6.3.1 Choosing which actors to follow
When analyzing technology as a sociotechnical phenomenon, where actors, technologies, and groups negotiate and co-produce each other, it is easy to become entangled in a problem of extension. Put bluntly, despite the rather broad and expansive concept of “relevant social groups”, an analysis must have a boundary, even if such bounds may be artificial. There will therefore always be some form of reductionism in a sociotechnical analysis, if only because papers must have an end. Although one major aim of studying sociotechnical ensembles is to go beyond the reductive explanations put forward by technological determinism and social reductionism, an analysis with no reductive properties whatsoever will inevitably lapse into indiscriminate empiricism. As Bijker points out, however, reductionism should not be taken as something inherently negative, and when doing an STS analysis, it is not unusual to set aside or bracket some parts of the sociotechnical web, regarding them as fixed entities for the sake of the analysis (Bijker 1993, 127). By leaving these fixed sociotechnical worlds in the background, one can focus on the main objects of interest without getting caught up in an endless descriptive analysis where everything is up for debate. I will therefore regard institutions such as “civil liberties organizations” or “law enforcement” as a more or less coherent organizations with fixed goals, despite this not being a completely accurate reflection of the internal reality of the institution. In other words, when networks have
stabilized as successful entities, they in a sense become a black box themselves. The network or group is represented under the shared flag of the institution itself, which translates its variety of voices and goals into one coherent entity (Callon and Law 1997, 174).
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