Remembering by Design: Memory Practices in Digital Identification (Ranjit Singh)

23. Jun

The Centre for Digital Cultures (CDC) invites you to the upcoming talk by Ranjit Singh (Data & Society, New York).

Tuesday, June 23 / 2 – 4 pm / C40.530
Registration is not necessary.

In this talk, I argue that debates about digital welfare too often reduce “data for services” to a bargain: privacy traded for access. Using India’s Aadhaar identification infrastructure as a case, it reframes that bargain through memory practices: the technical, formal, and social routines through which the state commits citizen data to record, maintains it, and makes it available for recall as an administrative fact. Aadhaar was designed as a federated system that, in principle, avoids centralizing transaction histories, making cross-domain collation difficult and placing legal friction in the path of surveillance. Yet the same distributed architecture also produces its own administrative weakness: a form of forgetting in which fragmentation and short life of records can make it harder for citizens to re-establish their existence in state systems when things go wrong. I follow how “remembering” is operationalized through Aadhaar’s infrastructural processes — enrollment, seeding, and authentication — and how these processes enact forms of clearance and erasure that discard older documentary infrastructures while raising the competence demanded of citizens in ordinary encounters with welfare offices. The result is a shift in where responsibility sits: when authentication fails, the burden often falls on individuals to assemble a pattern of failure before the evidence expires, and to do so across multiple sites that each hold only partial traces. By tracing how inclusion and efficiency are themselves evaluated through archives of citizen data, the talk closes with a governance problem that privacy regimes are not designed to resolve: not only what the state remembers, but what it refuses to record, what it cannot easily retrieve, for how long, and with what consequences for accountability.

Ranjit Singh is the director of Data & Society’s AI on the Ground program, where he oversees research on the social impacts of algorithmic systems, the governance of AI in practice, and emerging methods for organizing public engagement and accountability. His own work focuses on how people live with and make sense of AI, examining how algorithmic systems and everyday practices shape each other. His work draws on majority world scholarship, public policy analysis, and ethnographic fieldwork in settings ranging from scientific laboratories and bureaucratic agencies to public services and civic institutions. At Data & Society, he has previously led projects mapping the conceptual vocabulary and stories of living with AI in/from the majority world, framing the place of algorithmic impact assessments in regulating AI, and investigating the keywords that ground ongoing research into the datafied state.