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Datafied publics 
Morgan Currie (University of Edinburgh)
Catherine Montgomery (University of Edinburgh)
Karen Gregory (University of Edinburgh)
Gavin Sullivan (The University of Edinburgh)
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Traditional Open Panel

Short Abstract:

This panel focuses on datafied publics: groups that politically mobilise because they are subject to commercial and government data systems that algorithmically govern them but remain opaque. The panel will give datafication in public participation renewed theoretical-empirical attention.

Long Abstract:

Marres’s term ‘material participation’ describes how objects facilitate political action through everyday doing and making (2012). It is a useful theory for thinking about data publics – for instance, people with similar technical interests who come together to work with datasets and software to political ends. We can also use material participation to understand data publics in another way, by considering how data has “the capacities to organize publics” under the gaze of data-intensive systems (Ibid p. 9). We can ask how people politically mobilise when they are subject to commercial and government data systems that algorithmically govern them but remain opaque. Such collectives come together as a particular type of data public – a datafied public – to understand the ways they are sorted, shaped and targeted and to demand greater control over these processes.

How do datafied publics take shape and what forms of participation do they engage in to? What role do calls for transparency and democratic oversight play towards actual, substantive political accountability of these systems (Annany and Crawford 2016)? From health to social security and policing, the role of datafication in public participation demands renewed theoretical-empirical attention.

We welcome panelists who look at a range of datafied publics, such as:

• patient populations ‘enriched’ for inclusion in clinical trials

• workers of digital platforms in the gig economy

• groups who are unduly targeted by risk prediction models in social security and child services

• policing and border control data that target certain communities

• those muted by online platforms for certain content or identities

Ananny, M., & Crawford, K. (2018). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media & Society, 20(3), 973-989.

Marres, N. (2012). Material Participation: Technology, the Environment and Everyday Publics. Palgrave Macmillan.

Accepted papers: