I am a senior researcher at Data & Society, focused on qualitative research for the Algorithmic Impact Methods Lab (AIMLab) and a research fellow with Siegel Family Endowment. I also help guide research ethics at the Data & Society (D&S) Research Institute and sustain equity in collaborative research practices both internally and with external partners.
My work broadly examines the everyday experiences of people subject to data-driven practices. Most people find themselves at the receiving end of data-driven systems, but this does not mean they have no agency. I am particularly interested in following the ordinary ethics of exercising this human agency in navigating everyday struggles of dealing with data-driven systems.
My research sits at the intersection of data infrastructures, majority world scholarship, and public policy for data-driven systems, and uses methods of interview-based qualitative sociology and multi-sited ethnography.
Email: ranjit [at] datasociety [dot] net.
and topics that my work considers and explores
AI Infrastructures
Matters of scale in infrastructuring AI into everyday life.
Majority World
Mapping how majority world scholars engage with data and AI.
Public Policy
Impact assessments as a regulatory regime for algorithmic systems.
Storytelling
The craft of storytelling and the practice of listening.
Ordinary Ethics
Grounding ethics in everyday experiences of living with data.
Research Equity
Reciprocity of care in equitable collaborations.