Inheriting Discrimination: Datafication Encounters of Marginalized Workers

Grassroots workers are increasingly subjected to data-driven systems worldwide. While there has been increasing attention to processes of datafication in state sponsored welfare programs, not much attention has been focused on everyday workplace of the poor particularly in global south. In this paper, we examine the datafication experiences of sanitation and domestic workers, marginalized by caste, gender, and income, in India that goes beyond a welfare program setting. We report from interviews with 25 workers and 7 community leaders. Contrary to the modernist narratives around data and development, we find that data-driven systems invisibly inherited discriminatory properties from past institutions. These datafication processes are refracted through lack of access to supporting infrastructure, intentional opacity, and automated oppressive institutional norms.