FELICIA JING

POLITICAL THEORY + AI RESEARCHER

 


Trained as a political theorist, my research pursues the history of computing as a history of political struggle. Currently, I am a visiting fellow at the NYU Remarque Institute and a PhD Candidate at Johns Hopkins University. From 2022-2025, I was a full time research member of the IBM Thomas J. Watson Research Center. 

My first book project, titled AI and Revolutionary Desire, locates untimely algorithms across the history of political and economic thought, with a focus on the 20th century utopian political imagination through debates on state calculation and  planning. The first chapter is forthcoming in Political Concepts: A Critical Lexicon.

In addition to my dissertation research, I have also published on workplace AI in Catalyst: Feminism, Theory, and Technoscience, and have articles accepted to special issues of Social Text on the colonial studies of the platform and Big Data & Society on the sound of AI infrastructure. As part of my work at IBM, I also published empirical studies on AI systems for venues in information science and human-computer interaction like ACM FAccT and ACM CSCW. 

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

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

DISSERTATION 






  • (defense expected May 2026)
AI and Revolutionary Desire: Futurity and Political Thought through the Technological Imagination
    
My dissertation project begins from the premise that ‘the algorithm’ is a collective speculation toward utopia. More than a set of technoscientific practices, material infrastructures, or forces of production, the algorithm is also a collection of desires that has mediated political imagination since at least the socialist calculation debates. Tracing an unconventional genealogy of the concept, I depart from typical narrations of its history as a progression of scientific inventions from the 1950s-present. I instead center a technological imaginary of the 1910-40s, one forged between socialists and neoliberals to answer the question of central planning. That the promise of AI rings so hollow today, I suggest, owes to our inheritance of the political unconscious of these debates. The concept of the algorithm was forged within a fundamentally elite discourse, one that imagined utopia as a rational economic order (whether realized by technocratic management or by spontaneous coordination) that will always disqualify popular and proletarian modes of economic planning. In this way, I reframe the history of computing as a history of political struggle.

TEACHING 

    



  • Instructor of Record
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.