Data Justice in Digital Social Welfare: A Study of the Rythu Bharosa Scheme

TL;DR

This study examines data justice issues in India's Rythu Bharosa digital welfare scheme, highlighting design, informational, and structural inequalities that affect farmers' access and fairness in subsidy distribution.

Contribution

The paper introduces a structural data justice perspective, revealing how landowner approval conditions reproduce social inequalities in digital social welfare.

Findings

Biometric mismatches lead to subsidy denial.

Lack of information causes confusion among recipients.

Landowner approval reproduces caste and class inequalities.

Abstract

While digital social protection systems have been claimed to bring efficacy in user identification and entitlement assignation, their data justice implications have been questioned. In particular, the delivery of subsidies based on biometric identification has been found to magnify exclusions, imply informational asymmetries, and reproduce policy structures that negatively affect recipients. In this paper, we use a data justice lens to study Rythu Bharosa, a social welfare scheme targeting farmers in the Andhra Pradesh state of India. While coverage of the scheme in terms of number of recipients is reportedly high, our fieldwork revealed three forms of data justice to be monitored for intended recipients. A first form is design-related, as mismatches of recipients with their registered biometric credentials and bank account details are associated to denial of subsidies. A second form is informational, as users who do not receive subsidies are often not informed of the reason why it is so, or of the grievance redressal processes available to them. To these dimensions our data add a structural one, centred on the conditionality of subsidy to approval by landowners, which forces tenant farmers to request a type of landowner consent that reproduces existing patterns of class and caste subordination. Identifying such data justice issues, the paper adds to problematisations of digital social welfare systems, contributing a structural dimension to studies of data justice in digital social protection.