FELICIA JING

POLITICAL THEORY \ HISTORY OF COMPUTING \ HCI + AI RESEARCH

I am currently a visiting fellow at the NYU Remarque Institute and a PhD Candidate at Johns Hopkins University. In the spring, I will join Brown University as a Postdoctoral Research Associate in the social studies of computational technology. Previously, I was a research scientist at the IBM Thomas J. Watson Research Center in Yorktown Heights, NY.

Trained as a political theorist, my research pursues the history of computing as a history of political struggle. My first book project, titled AI and Revolutionary Desire, is a history of AI and its governance that routes through twentieth century political and economic thought. I focus in particular on debates on state calculation, socialist planning, and the steering of the “intelligence” of the market. The first chapter is forthcoming in Political Concepts: A Critical Lexicon under the “Algorithm” entry.

In addition to my dissertation research, I have written on workplace AI for Catalyst: Feminism, Theory, and Technoscience, and have two articles accepted to special issues of Social Text on the colonial studies of the platform and Big Data & Society on AI infrastructure. As part of my previous work at IBM, I led empirical studies on the social impacts of AI systems as well as technical research on AI evaluation and alignment. These can be found in venues for information science and human-computer interaction like ACM FAccT and ACM CSCW.

My work has been generously supported by grants from the Notre Dame-IBM Tech Ethics Lab, the National Endowment for the Humanities, and the History and Political Economy Project.

[ Curriculum Vitae ]
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ARTICLES

THEORY

Political Concepts: A Critical Lexicon
(forthcoming)

Algorithm

This essay re-politicizes our dominant technical concept of an “algorithm” by tracing its naturalization of capitalist logics. Algorithms, I argue, have today become the Robinsonades of computer science.

Catalyst: Feminism, Theory, and Technoscience (2026)

‘Good Tech’ and Technologies of Elite Capture
An article on the phenomena of “good tech” in the AI industry as a peculiar alliance where entrepreneurs and venture capital conspire toward making globalization “feel good.” Co-authored with Juana C. Becerra.

Social Text
(accepted to special issue)

On Emplotment: Phantom Islands, Synthetic Data, and the Coloniality of Algorithmic Space.

An essay that stages the rise of synthetic data as a colonial recursion of logistical technologies of loss prevention, as an reactive adaptation to organized political struggle along the data production pipeline. Co-authored with Juana C. Becerra and Ranjodh Singh Dhaliwal.

ARTICLES

EMPIRICAL

ACM Fairness, Accountability, and Transparency (2023)

Towards Labor Transparency in Situated Computational Systems Impact Research
A framework for documenting divisions of labor within participatory research, design, and data practices. Co-authored with Sara E. Berger and Juana C. Becerra. *Finalist for Most Impactful Research Paper of 2023, Responsible AI Institute.

ACM Computer Supported Work and Social Computing (2024)

Designing for Agonism: 12 Workers’ Perspectives on Contesting Technology Futures
Findings from pilot studies of practical methods and tools for non-expert participation AI research, design, and development. Co-authored with 11 others.

ACM Journal of Responsible Innovation (2025)

Opportunities and Challenges of Multidisciplinary Algorithmic Impact Assessments.
Methodological insights from the experimental use of multidisplinary, multi-modal methods in AI assessments, evaluations, and audits. Co-authored with Juana C. Becerra, Adriana Alvarado Garcia, Sara E. Berger, Heloisa Candello, and Caitlin Lustig.

For a full list of Felicia's technical, empirical research see her ACM Digital Library Profile

BOOK PROJECT

(in preparation, based on dissertation)

AI and Revolutionary Desire :
Planning, Computation, and Utopia in Twentieth-Century Political Thought

My first book project departs from the typical narration of AI as a story of scientific invention stretching from the mid-twentieth century to the present. AI and Revolutionary Desire traces an alternative lineage in twentieth-century utopian political thought—from scientific socialists and free-market fundamentalists to popular futurists and workers’ councils—who each articulated an early political concept of an algorithm as the imagined technical basis of a future to come. Routed through the writings of Lenin, Weber, Hayek, Luxemburg, and Neurath, the book argues that computational machinery and its purported “intelligence” have long been a site of political antagonism, contested between visions of the future from above and below and, in particular, over competing forms of planning—centralized, decentralized, and popular. Read as the political precursors of figures like von Neumann and Rosenblatt, the present-day politics of AI cannot be understood apart from this history of revolutionary and counterrevolutionary struggle over who, or what, ought to govern the organization of society. AI and Revolutionary Desire returns questions of rule, sovereignty, and insurgency to the history of algorithmic and artificial intelligence—as technologies that threatened to remodel the prevailing divisions between mental and manual labor, instruction and execution, distribution and production.

TEACHING

Instructor of Record

History of Artificial Intelligence (2027)

Postdoctoral Research Associate, Brown Univeresity. This course traces the history of ideas about artificial intelligence—from Aristotle's active intellect and Ada Lovelace's calculus of the nervous system to Marx's general intellect, Haraway's cyborg, and the modern 'black box'—through sources spanning philosophy, sociology, computer science, and film.

Hardware Fundamentals: Materialist Approaches to Computational Machinery (2025)

Part-time Lecturer, The New School Eugene Lang College of Liberal Arts, Faculty of Code as a Liberal Art. A half- critical humanities, half- hands-on lab course that teaches students to disassmble hardware components of digital computers alongside major works in the materialist tradition.

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Teaching Assistant

AI: A Critical Introduction
Second Faculty, The Brooklyn Institute for Social Research. Assistant to Alfred Lee. 2025.

Louis Althusser: Ideology and Repression
Second Faculty, The Brooklyn Institute for Social Research. Assistant to Robyn Marasco. 2024.
Introduction to Political Economy
Graduate Teaching Instructor, Johns Hopkins University, Department of Political Science. Assistant to Samual A Chambers. 2021.
Chinese PoliticsGraduate Teaching Instructor, Johns Hopkins University, Department of Political Science. Assistant to John Yasuda and Andrew Mertha. 2021.