Projects that currently occupy my time

Algorithmic Impact Methods Lab (AIMLab)

(since May 2023)

AIMLab’s core activity will be developing, piloting, and promulgating impact assessment methods. By foregrounding the communities that are most impacted by algorithmic harms, AIMLab aims to devise empirically grounded assessment methods that serve the public interest, and to make them readily accessible and widely available. 

Research Team: Tamara Kneese, Meg Young, Briana Vecchione, Emnet Tafesse, Ranjit Singh, and Jacob Metcalf

Red-Teaming in the Public Interest

(since Jun. 2023)

This project is centered on describing the place of red-teaming in the emerging ecosystem of practices for mapping, measuring, disclosing, and mitigating AI harms, ranging from impact assessments and audits to participatory governance measures and incident reporting.

We ask:

  1. What are the constitutive features of red teaming in public interest and what are its limits?
  2. How does red-teaming fit into the emerging regulatory landscape for AI accountability?

Research Team: Ranjit Singh, Borhane Blili-Hamelin, Beth Duckles, Emnet Tafesse, and Jacob Metcalf

Illustrative Publications: 

[Journal Article] Jacob Metcalf and Ranjit Singh, 'Scaling Up Mischief: Red-Teaming AI and Distributing Governance,' in Harvard Data Science Review (2024). DOI: 10.1162/99608f92.ff6335af.

[Policy Brief] Sorelle Friedler, Ranjit Singh, Borhane Blili-Hamelin, Jacob Metcalf, and Brian J. Chen, 'AI Red-Teaming Is Not a One-Stop Solution to AI Harms: Recommendations for Using Red-Teaming for AI Accountability', (New York: Data & Society Research Institute, October 2023), 10 pages. URL:

Organizational Accomplishment of Responsible Artificial Intelligence

(since Mar. 2023)

When does Artificial Intelligence (AI) become responsible? This project investigates the ongoing transformation of ethics into responsibility within technology companies and how this responsibility is organized in understanding the impacts of AI and mitigating its harms.

We ask: 

  1. How is RAI organizationally accomplished in technology companies? Who are the people tasked with doing and managing RAI work and how do they describe it?
  2. What are the industry practices of measuring RAI work? How is it incentivized and/or discouraged? 
  3. How is the relationship between RAI work and the real-world impacts of AI practically established? What are “good” metrics and proxies for preventing harm in doing RAI work?

Research Team: Ranjit Singh, Emanuel MossElizabeth Anne Watkins, Samir Passi, and Jacob Metcalf

AI in/from the Majority World

(since Dec. 2020)

Through empirical work and partnerships, this project invigorates existing efforts to reframe the “Global South” as home to the majority of the human population — and to investigate and understand the diverse ethics, politics, and everyday experiences of living with data and AI.

The project is oriented towards:

  1. Mapping the discourse of AI in/from the majority world (concepts and keywords).
  2. Curating a multiformat and multilingual anthology of stories narrated by experts, activists, practitioners, and data subjects on everyday experiences of living with data (parables).
  3. Exploring the craft of storytelling as a crucial resource for engaging with ordinary ethics of living with data and AI in/from the majority world (research methods and analytic strategies).

Research Team: Ranjit Singh, Rigoberto Lara Guzmán, and Sareeta Amrute.

Illustrative Publications: 

[Article] Ranjit Singh, 'Ordinary Ethics of Governing AI' (Washington, DC: The Technology and International Affairs Program, Carnegie Endowment for International Peace, April 2024). URL:

[Edited Volume] Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison, (eds.) 'Parables of AI in/from the Majority World: An Anthology' (New York: Data & Society Research, December 2022), 191 pages. DOI: ssrn.4258527. URL:

[Primer] Sareeta Amrute, Ranjit Singh, and Rigoberto Lara Guzmán, 'A Primer on AI in/from the Majority World: An Empirical Site and a Standpoint' and 'Una guía para entender la inteligencia artificial (IA) en/desde el mundo mayoritario: un lugar empírico y un punto de vista' (New York: Data & Society Research Report, September 2022), 44 pages. DOI: ssrn.4199467. URL:


Projects that used to occupy my time.

Exploring the Datafied State

(Mar. 2022 - Apr. 2024)

The Datafied State is one remade by the data sources and infrastructures, computational tools and techniques that are now being adopted across government just as they are in the private sector. There is not an absolute distinction between public and private sectors in the Datafied State, but more of a blurred boundary.

We ask:

  1. How datafied is the State today? How algorithmic? How automated? How can we find out?
  2. How does the drive to feed data to algorithms or the ease of acquiring data end up altering the way the State functions, violating or operating in a gray area of civil liberties?
  3. How do citizens secure and claim representation in accordance with the core data categories used to organize government services? Or conversely, how do they strategically disappear from data systems that constitute their relationship to the State?

Research Team: Jenna Burrell, Ranjit Singh, and Patrick Davison

Illustrative Publications: 

[Edited Volume] Jenna Burrell, Ranjit Singh, and Patrick Davison, (eds.) 'Keywords of the Datafied State' (New York: Data & Society Research Institute, April 2024), 231 pages. DOI: ssrn.4734250. URL:

[Blog Series]: Towards a Mindful Digital Welfare State

This curatorial project focuses on inviting researchers, activists, investigative journalists, and thinkers to write about their own perspective on the mindful appropriation of digital technologies for welfare distribution in different parts of the world.

Curatorial Team: Ranjit Singh, Emnet Tafesse, Seth Young, and Eryn Loeb

Algorithmic Impact Assessments

(Oct. 2020 - Jan. 2023)

This project mapped the challenges of constructing algorithmic impact assessments (AIAs) by analyzing impact assessments in other domains—from finance and environment to human rights and privacy. We focus on existing impact assessment processes to showcase how “impacts” are evaluative constructs that enable institutions to act; why it is necessary to always attend to how impacts get constructed; and occasions when the impacts measured do not capture the actual harms experienced by people.

Research Team: Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Emnet Tafesse, Madeleine Clare Elish, and Jacob Metcalf.

Illustrative Publications: 

[Conference Paper] Jacob Metcalf, Ranjit Singh, Emanuel Moss, Emnet Tafesse, and Elizabeth Anne Watkins. 'Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability', in Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT ’23 (New York, USA: ACM, 2023). pp. 1450–62. DOI: 10.1145/3593013.3594092.

[Research Report] Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Madeleine Clare Elish, and Jacob Metcalf, 'Assembling Accountability: Algorithmic Impact Assessment for the Public Interest' (New York: Data & Society Research Report, 2021).

[Conference Paper] Jacob Metcalf, Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, and Madeleine Clare Elish, ‘Algorithmic Impact Assessments and Accountability: The Co-Construction of Impacts‘, in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, FAccT ’21 (Virtual Event, Canada: ACM, 2021), pp. 735-746. DOI: 10.1145/3442188.3445935.

[Blog Series]: The Social Life of Algorithmic Harms

This series of essays seeks to expand our vocabulary of algorithmic harms — and with it, our capacity to defend ourselves against them.

Curatorial Team: Jacob Metcalf, Emanuel Moss, Ranjit Singh, and Eryn Loeb

Seeing like an Infrastructure: Mapping Uneven State-Citizen Relations in Aadhaar-Enabled Digital India

(Doctoral Dissertation)

(Aug. 2012 – Aug. 2020)

How does a citizen become a data subject? My dissertation research examined on-the-ground problems and practices in building and appropriation of Aadhaar (translation: Foundation), the biometrics-based national identification infrastructure of India. It advanced public understanding of the affordances and limits of biometrics-based data infrastructures in practically achieving inclusive development and reshaping the nature of Indian citizenship.

Committee: Michael LynchSteven Jackson, and Trevor Pinch

Illustrative Publications: 

[Journal Article] Ranjit Singh, 'Intermediaries as infrastructure: Interrogating the phatic labor of state-building,' in Journal of Sociology (2024). DOI: 10.1177/14407833241234675.

[Journal Article] Ranjit Singh, ‘The curious case of tweeting an Aadhaar number: trust/mistrust in security practices of public data infrastructures’, in Journal of Cultural Economy (2023). DOI: 10.1080/17530350.2023.2229360.

[Dissertation] Ranjit Singh, Seeing like an Infrastructure: Mapping Uneven State-Citizen Relations in Aadhaar-Enabled Digital India (Ann Arbor, Michigan: ProQuest Information and Learning, 2020). DOI: 10.7298/sadf-ye74

[Conference Paper] Ranjit Singh and Steven J. Jackson, 'Seeing like an Infrastructure: Low-resolution Citizens and the Aadhaar Identification Project', in Proceedings of the ACM on Human-Computer Interaction, Vol. 5, CSCW2, Article 315 (October 2021). DOI: 10.1145/3476056.

[Journal Article] Ranjit Singh, ‘Give Me a Database and I Will Raise the Nation-State', in South Asia: Journal of South Asian Studies, Vol. 42, no. 3 (2019), pp. 501-518. DOI: 10.1080/00856401.2019.1602810.

Restoring Credit: How people understand and interact with credit scoring systems

(Sep. 2017 – Nov. 2021)

Restoring Credit was a longitudinal qualitative study of the efforts of low-income individuals to improve their creditworthiness within the lending industry in the United States. It traced credit repair journeys of low-income individuals through qualitative interviews and monthly diary entries over a period of one year of select participants in the Finger Lakes Region of New York to understand the implications of credit scoring systems for social and economic inequality.

We asked: How do ordinary consumers make sense of credit scoring systems that appear to be inscrutable?

Research Team: Malte Ziewitz and Ranjit Singh

Illustrative Publications: 

[Book Chapter] Ranjit Singh, ‘The Backend Work of Data Subjects: Ordinary Challenges of Living with Data in India and the US', in Lisa Parks, Julia Velkova, and Sander de Ridder (eds.), Media Backends: The Politics of Infrastructure, Clouds, and Artificial Intelligence (Illinois: University of Illinois Press, 2023). pp. 229-244.

[Journal Article] Malte Ziewitz and Ranjit Singh, ‘Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects', in Big Data & Society, Vol. 8, no. 2 (2021), pp. 1-13. DOI: 10.1177/20539517211061122.

Life of a Tuple: The Assam NRC as an Infrastructure of Reform in Citizen Identification

(Nov. 2016 – Sep. 2020)

This project, hosted by the Center for Internet and Society (CIS), India, followed bureaucratic trails of documents used in updating the National Register of Citizens (NRC) to differentiate between citizens and illegal immigrants in Assam, a state in the north-east of India. Discussions on migration have focused on contests over legal identity of immigrants, making bureaucratic sense of the other. This project contributed to these discussions with ethnographic vignettes of a state-sponsored citizen registration project, which aims to make bureaucratic sense of self (citizenry) in order to differentiate it from the other.

Research Team: Sumandro Chattapadhyay, Khetrimayum Monish Singh, and Ranjit Singh

Back to the Future: Situating ‘Technology’ in ‘Science, and Technology Studies’

(May 2013 – Jun. 2014)

This project explored the historical context within which the discussion paper on Social Construction of Technology (SCoT) emerged and the professional and discursive efforts of STS practitioners to sustain the eventual shift in focus of STS as an academic discipline from socio-cultural explanations of science to those of science and technology.

Supervisor: Michael Lynch

Collaborators: Trevor Pinch and Wiebe Bijker


Award: The Sheila Jasanoff Prize for Academic Excellence in Science Technology Studies for the best graduate student paper within the previous three semesters (May 2015)

Invited Talk [Keynote Speaker]: Ranjit Singh, 'Back to the Future: Situating the 'T' in 'STS'', at the Workshop on Social Construction of Technology Coming of Age: New Challenges and Opportunities Ahead, (Trondheim: Norwegian University of Science and Technology, 3-5 June 2014).

Locating Publics: Co-Production of the Bt Brinjal Controversy and Publics in India

(Jan. – Jul. 2011)

This project traced a sequence of historical events between 2005 and 2010 that led up to the National Consultations on Bt Brinjal in January and February 2010 organized for the Ministry of Environment and Forests (MoEF). Right from the modern Chipko Movement of the early 1970s initiated as a protest against deforestation for industrialization to Narmada Bachao Andolan (Save Narmada Movement) since late 1980s against the construction of Narmada Dam, the public conversations on science in India are marked by distinct peaks of criticism within the generic troughs of belief that development through science is equivalent to progress of the country. In this project, I explored the Bt Brinjal controversy as yet another critique of this belief system around science-led development in India.

Supervisors: Wiebe Bijker and Esha Shah

Illustrative Publication: 

[Master's Thesis] Ranjit Singh, Locating Publics: Co-Production of the Bt Brinjal Controversy and Publics in India (Maastricht: Cultures of Arts, Science, and Technology (CAST), Maastricht University, 2011).

Vaacha: A Tribal HealthCare Management System

(Jan. 2007 – Jul. 2008)

This project focused on building a healthcare information visualization system of patients who came to the health camps organized by Bhasha, an NGO working on the study, documentation, and conservation of marginal languages in the tribal belt of Gujarat. It was an investigation of the circumstances which lead to disease outbreaks in the tribal belt of Gujarat and an intervention in evaluating contexts and devising healthcare policy using data visualization as a tool.

Supervisor: Binita Desai

Illustrative Publications: 

[Journal Article] Ranjit Singh and Ravi Kiran Atluri, 'Democracy and Policy Games: The New Information Panchayats', in Journal of Creative Communications, Vol. 2, no. 3 (2007), pp. 329-344. DOI: 10.1177/097325860700200304.

[Final Year Project] Ranjit Singh, Vaacha: A Tribal HealthCare Management System (Gandhinagar: Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), 2007).