Large-scale data systems play a central role in how state bureaucracies come to know and manage citizens. Such systems are endemically uneven in implementation, producing distributed and exclusionary consequences that are among their most important effects. These systems also operate as infrastructures in the rich and complex sense of the term that has been a core contribution of CSCW to the wider computing and social science fields. Building on James Scott's work on 'seeing like a state', we conceptualize 'seeing like an infrastructure' as a more supple analytic perspective that maps the distributed work and uneven consequences through which designers, bureaucrats, and users (here, citizens) assign or claim representation in the consequential data systems that increasingly shape and define citizenship. Drawing on eighteen months of ethnographic fieldwork into Aadhaar, India's biometrics-based identification project, and studies of infrastructure, marginalization, and citizenship in CSCW and allied fields, we argue that this perspective provides crucial insight into the strategies and mechanisms by which effective access to the basic rights and entitlements of citizenship are granted, claimed, and at times undermined. More specifically, we show how challenges in implementing Aadhaar's three key processes-enrollment, seeding, and authentication-give rise to a spectrum of resolution in which the rights and entitlements of 'high-resolution citizens' are expanded, while those of 'low-resolution citizens' are curtailed.?
Seeing Like an Infrastructure: Low-resolution Citizens and the Aadhaar Identification Project
Research Seminar Series presents Ranjit Singh, Researcher at Data & Society Research Institute.
Published Feb. 24, 2022 4:36 PM - Last modified Feb. 24, 2022 4:36 PM