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Paper short abstract:

Here we argue for the importance of the deep history of data justice. Where the horizons of data justice research are widened beyond datafication processes, researchers can better bring into focus how long-term legacies of inequality, discrimination and oppression are drawn into present data work.

Paper long abstract:

Over the last decade, much of the growing academic literature on digital rights and data justice has been characterised by a near-sighted focus on “the big data revolution,” the “second machine age,” and the rise of “surveillance capitalism”. Such a cramped temporal lens runs the risk of reverting to modes of information-centrism and tech-centered short-sightedness that can impair researchers’ visions of the past, present, and future. It can impair understanding of the past by concealing longer term sociohistorical patterns of inequity that have cascading effects on data innovation ecosystems and that directly and indirectly influence the sociotechnical contexts of data collection and use. It can impair understanding of the present by limiting levels of explanation and analysis to areas circumscribed by the narrow set of normative and social justice issues that are seen to surface specifically in current constellations of data innovation practices. And, it can impair visions of the future by creating a false sense of the insuperability of the revolutionary momentum of current technoscientific change—leaving critics feeling disempowered in the face of a creeping technological determinism.

In this paper we argue for the importance of the deep history of data justice. Where the temporal horizons of the study of data justice are appropriately widened, slower and more subtle patterns of injustice become discernible. This can bring into focus how longer-term legacies of inequality, discrimination, and oppression have both shaped the history of applied statistical and computational techniques of social administration and, ultimately, been drawn into contemporary data work.