Visual Data Justice? Datafication of Urban Informality in South Africa Using 360° Imaging Technologies
Jonathan Cinnamon
Abstract
Uneven economic development is closely associated with the proliferation of informal settlements in the global South, a process generally understood to harbour injustices according to a resource access view of society. An understanding of social justice in terms of distribution provides a powerful framework for challenging uneven development, however, a key contention of this paper is that further forms of injustice accrue to the residents of these places over and above issues of distribution. With its focus on sociocultural representations, recognition provides a basis for ‘making visible’ further injustices that threaten dignity and self-identification, which may also act as a preliminary step towards advancing socioeconomic justice for informal settlements.
This paper draws on ongoing research into the datafication of informal settlements in South Africa, including interviews with data activists and experiences of conducting a 360° geovisual imagery pilot study in Kya Sands informal settlement in Johannesburg. In first drawing attention to the limitations of quantitative data for representing injustice and the problematic effects of conventional framed photographs of informality from aerial and ground-level perspectives, this paper explores the possibilities of ground-level 360° imagery as a realist, non-reductionist form of representation for informal settlements. Three 360° street views were produced to illustrate key possibilities and limitations for advancing recognition, based on the notion that visibility is essential for recognition. Further, the piece reflexively critiques how – through new advancements in image analytics – informal settlement visibility projects risk further engendering injustices of misrecognition for these highly marginalized urban spaces.
As such, this paper provides a basis for further inquiry into the relationship between visual data and the social justice principle of recognition, towards an emerging research agenda on visual data justice. The paper concludes with recommendations for practitioners and key topics for research. Important items on the agenda include: determining the forms and examples of injustice that can be remedied through datafication, the relationship between misrecognition and maldistribution in the context of datafication, and the acceleration of new injustices due to advances in computer vision applied to ground-level imagery.
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