Data Work in the Public Sector

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The focus of this panel is the work that goes into producing and putting data into action. This data work provides the basis for the process of datafication of social lives, organizations, and society, as well as the much-hyped projects of Big Data and Artificial Intelligence (AI). ‘Data work’ can be applied as a sensitizing concept to direct our attention to the efforts involved in making data: From data generation, accumulation, filtering, analyzing, visualization, (re)contextualizing and putting into action. While some occupations such as data scientists have received attention, other occupations and people doing data work tend to be invisible. Within healthcare, for example, the occupation of medical secretaries and their work of coding medical charts and validating data is largely going unnoticed outside of their own departments. Most likely, other occupations doing data work are similarly unnoticed, and the work and tasks involved in producing and managing data is subsumed under traditional job titles, which makes the scope, importance, and volume of data work invisible. In turn, this produces an image of datafication, Big Data and AI as self-propelling processes that have a life of their own. Just like the invisibility of technicians produces an impoverished understanding of science, as Shaping argued in his paper “The invisible Technician” (1989), the invisibility of data work leads, we argue, to an impoverished understanding of the central and important developments within datafication, Big Data and AI. The invisibility of work has a long history within sociology and STS, as exemplified in Daniels’ “Invisible Work” (1987), Star & Strauss’ paper “Layers of Silence, Arenas of Voice” (1989), and more recently Crain et al (2016) “Invisible Labor”. In this panel, we would like to use the opportunity to bring into light the various kinds of data work and tasks conducted within the public sector.
Periode2 jun. 2022
PlaceringAarhus Universitet, DanmarkVis på kort