The use of data and algorithmic processes for decision-making are a growing part of social life. Digitally monitoring, tracking, profiling as well as predicting human behaviour and social activities is at the core of the information order often described as surveillance capitalism. Increasingly, it also determines decisions that are central to our ability to participate in society, such as welfare, education, crime, work, and if we can cross borders. How can we grasp what is at stake in such developments?
Whilst much debate on this datafication of society has focused on the need for efficient and supposedly more objective responses to social problems on the one hand and a concern with individual privacy and the protection of personal data on the other, it is becoming increasingly clear that we need a broader framework for understanding these developments. This is one that can account for the disparities in how different people might be implicated and that recognises that the shift to a datafied society is not merely technical but has implications for social justice. Such a framework, referred to here as ‘data justice’, pays particular attention to the ways in which data processes are uneven, can and do discriminate, create new social stratifications of ‘have’ and ‘have nots’, and advance a particular politics based on a logic of prediction and preemption that caters to certain interests over others.
In this project, we have taken stock of these concerns, and drawn on a number of different case studies across contentious areas of governance and control, including work, law enforcement, and migration that look at the implementation of algorithmic processes in practice. In analysing these case studies, the project has explored how practices are changing with the implementation of data-driven systems and with what implications for the lives of different communities, the protection of social and economic rights, and the advancement of social justice. The overall objective has been to advance conceptual and empirical research on the relationship between social justice and datafication, with a view to enhance public understanding of data developments, broaden the debate on data collection, minimise data harms, and find ways to mobilise civil society around data justice.
