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Towards data justice? Reframing the datafication debate
Dr Lina Dencik

This event took place on 22nd February 2017 at 11:30am (11:30 GMT)
Knowledge Media Institute, Berrill Building, The Open University, Milton Keynes, United Kingdom, MK7 6AA

This presentation explores the meaning of social justice in an age of datafication. It is premised on two significant developments: 1) the shift to a focus on the collection and processing of massive amounts of data across social life and 2) the increasing concern with the societal implications of such processes. The technical ability to turn vast amounts of activity and human behaviour into data points that can be tracked and profiled has led to significant changes across government, business and civil society. Whilst the documents revealed by Edward Snowden led to important questions being asked about what this means for individual rights to privacy and the protection of personal data, concerns with datafication are now increasingly shifting towards a more explicit engagement with power (Dow 2016, Sylvia IV 2016). These concerns emphasise that data processes are not ‘flat’ and do not implicate everyone in the same way, but, rather, are part of a system of ‘social sorting’ (Lyon 2003) creating new categories of citizens (Ansorge 2016) that are premised on a new order of ‘have’ and ‘have nots’ between data profilers and data subjects (Citron and Pasquale 2014). In such a context, questions of social justice come to the fore in discussions of datafication and require detailed study. I frame this research agenda around the notion of ‘data justice’. This is the focus of a newly established collaborative research initiative at Cardiff University called the Data Justice Lab. The term ‘data justice’ is intended to connote the intricate relationship between datafication and social justice by foregrounding and highlighting the politics of data-driven processes. In this presentation I will introduce some ideas as to what such an agenda might look like.


The webcast was open to 1000 users



(75 minutes)

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