Authors:Florian Irgmaier (Weizenbaum Institute for the Networked Society)
Florian Eyert (Weizenbaum Institute for the Networked Society)
Lena Ulbricht (WZB Berlin Social Science Center)
Rainer Rehak (Weizenbaum-Institut für die vernetzte Gesellschaft)
Paper short abstract:
We investigate the implications of quantification and datafication for regulatory practices. Enriching a well-tried phase model of regulation with insights from STS, we present a conceptual framework that allows to capture empirically the ways in which datafication transforms social ordering.
Paper long abstract:
Although practices of computer-based quantification pervade modern societies, there is little systematic research on how they affect social ordering. A key site of social ordering is regulation, i.e. the intentional attempt (by states, by other organizations or as self-regulation) to alter behaviour in order to reach specified goals (Black 2002). Yeung (2017) has developed a general framework for studying practices of data-based regulation, distinguishing three analytical components: information gathering, standard setting and behaviour modification. In order to grasp more deeply the material dimension of data-based regulation, we enrich this framework with a number of suitable STS concepts.
Information gathering encompasses both the collection of data and its analysis. We interpret digital data as "immutable mobiles" (Latour 1986): information stored in a format that makes unintended changes or losses improbable and facilitates quick transportation, recombination, and aggregation, thus reshaping the political economy of regulation.
Standard setting is the process of defining which goals are to be attained and how. Far from being neutral instruments, technological artifacts always constitute their own politics (Winner 1980) that potentially superposes governance processes.
Behaviour modification refers to the means by which behaviour is influenced. In order to conceptually grasp the increasing importance of technological architectures, we combine insights on "regulation by design" and "regulation by technology" with an ANT perspective (Latour 1990).
As an illustration of how our framework can serve as a ground for comparative studies, we discuss several concrete cases. We conclude that datafication enables more responsive and more comprehensive forms of regulation.
Technologies that count: big data and social order