Lanterna Rally

Author: Ranjit Pal Singh

Publisher:

Published: 2020

Total Pages: 0

ISBN-13:

How does a citizen become a data subject? This dissertation examines on-the-ground problems and practices in building and appropriation of Aadhaar (translation: Foundation), the biometrics-based national identification infrastructure of India. It advances public understanding of the affordances and limits of biometrics-based data infrastructures in practically achieving inclusive development and reshaping the nature of Indian citizenship. Deploying a mix of interview-based multi-sited ethnographic research and documentary analysis, I examine how various Indian bureaucracies-especially, the Public Distribution System that establishes access to food rights for low-income households-are using Aadhaar to distribute welfare. Aadhaar is imbricated with existing practices of identifying and authenticating each eligible citizen's claim to government services. I show how making these claims becomes a matter of making as much of the Indian population as possible visible through Aadhaar. Tracing the sociotechnical, legal, and administrative development of Aadhaar, this dissertation captures the artful blending of the entrepreneurial culture of IT start-ups with the bureaucratic culture of the Indian government. It develops the framework of seeing like an infrastructure to analyze the distributed work of street-level bureaucrats in administering and everyday struggles of low-income citizens in securing welfare benefits. Certain combinations of data provide more comprehensive pictures of citizens than others. Visibility afforded by data infrastructures is not just a method of state control; it also conditions citizens' existence, rights, and participation in state services as data subjects. Drawing inspiration from the optical attribute of resolution, I describe how the Indian state zooms in and out of the lives of citizens in (re)configurations of the registration, circulation, and interpretation of their data. The spectrum of this resolution embeds multiple meanings of citizenship. A low-resolution citizen faces challenges of data-driven marginalization; a high-resolution citizen must often contend with invasion of privacy and surveillance. In emerging regimes of data-driven governance, the work of resolving citizens through data is simultaneously a social and a moral problem: social, because making up and interpreting a population as data requires so much work, organization, and discipline; moral, because using data records to represent citizens inevitably involves responding to demands of fairness, accountability, and social justice.