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. With a particular focus on research equity, I also help guide research ethics at the Data & Society (D&S) Research Institute and develop equitable research practices both internally and with external partners.
My work broadly examines the everyday experiences of people subject to data-driven practices and follows the mutual shaping of their lives and their data records, aiming to understand how data is increasingly used to imagine and develop new digital solutions for democratizing inclusion.
My research sits at the intersection of data infrastructures, majority world scholarship, and public policy for algorithmic systems, and uses methods of interview-based qualitative sociology and multi-sited ethnography.
Recently, I have been featured in Business Insider's article on AI 100: The top people in artificial intelligence for 2023 under the category of Policy, Ethics and Research.
Email: ranjit [at] datasociety [dot] net.
and topics that my work considers and explores
Matters of scale in building data infrastructures.
Mapping how majority world scholars engage with data and AI.
Impact assessments as a regulatory regime for algorithmic systems.
The craft of storytelling and the practice of listening.
Grounding ethics in everyday experiences of living with data.
Reciprocity of care in equitable collaborations.