Datafying anti-poverty programmes: implications for data justice
journal contributionposted on 10.04.2019, 13:06 authored by Silvia Masiero, Soumyo Das
This paper seeks to illuminate the significance of datafication for anti-poverty programmes, meaning social protection schemes designed specifically for poor people. The conversion of beneficiary populations into machine-readable data enables two core functions of social protection, those of recognising entitled beneficiaries and assigning entitlements connected to each anti-poverty scheme. Drawing on the incorporation of Aadhaar, India’s biometric population database, in the national agenda for social protection, we unpack a techno-rational perspective that crafts datafication as a means to enhance the effectiveness of anti-poverty schemes. Yet at the same time, narratives collected in the field show multiple forms of data injustice on recipients, underpinned by Aadhaar’s functionality for a shift of the social protection agenda from in-kind subsidies to cash transfers. Based on such narratives the paper introduces a politically embedded view of data, framing datafication as a transformative force that contributes to deep reform of existing anti-poverty schemes.
- Business and Economics