Gaming the Algorithm: Collective Resistance in China’s Platform Economy
Hong Kong Sociological Association Annual Conference, Hong Kong
My current project investigates collective action among gig workers in China through a mixed-methods approach. The project has so far resulted in two twin papers (and more to come):
David Su. (2025). “Gaming the Algorithm: Tactical Innovation and Collective Resistance in China’s Platform Economy.” Under review.
2026 Thompson Paper Award, ASA OOW 2026 Mayer Zald Award, ASA CBSM 2026 Herbert Blumer Prize, UC BerkeleyAbstract. Existing scholarship often portrays algorithmic control as a “digital cage” that undermines gig workers’ capacity for collective resistance. This paper argues that the gamification of platform work has produced a regime of hegemonic algorithmic control that paradoxically enables workers to develop tactical innovations and gain bargaining leverage during strikes. Based on 65 in-depth interviews and four months of ethnographic fieldwork in Guangdong, China, I trace labor activism among food-delivery and ride-hailing workers in two cities after wage cuts. Extending the concept of algorithmic literacy to collective action, I use the term to capture workers’ cognitive capacity to interpret opaque algorithms and recognize opportunities to exploit them strategically. Although unable to access the algorithm directly, top players, gig workers with a high algorithmic literacy, increase their bargaining leverage through three mechanisms: algorithmic manipulation, which shapes inputs to influence outputs; algorithmic deception, which bends the rules while avoiding detection; and algorithmic non-correction, which withholds corrective labor to intensify disruption. These tactics, developed in the everyday labor process, can scale up to coordinated disruption during strikes when deployed collectively. The paper shows how algorithmic control can backfire and identifies a new kind of structural power rooted in gig workers’ collective efforts to interpret, decode, and contest opaque algorithmic rules.
Keywords: Collective Action, Labor Movement, Platform Work, Algorithmic Control, China
David Su. (2025). “The Platforms of Contention: Algorithmic Organization of Work and Gig Worker Strikes in Post-Pandemic China.” In progress, presented at ASA 2025, Future of Work panel.
Dr. C.F. Koo & Cecilia Koo Chair Fellowship, IEASTreating gig worker strikes in China as deviant cases that challenge prevailing theoretical expectations, I examine the conditions under which platform algorithms inadvertently facilitate strike mobilizations. I also explore how the gamification of work, designed to discipline labor, can instead give rise to a new kind of bargaining power that allows gig workers to exert leverage.
My previous research employs computational methods to analyze social networks and the dynamics of embedded inequality. My previous project, Cov-Netps (inspired by the UC Nets project), examined population health in Wuhan, China, during and after the lockdown. This work revealed how the pandemic deepened health inequalities in a unique and extreme setting — where disparities in resources and connections could become, quite literally, a matter of life and death.
Su*, Xu*, and Duan. (2026). “Embedded Inequality.” Network Science 14, 1–18. (*Joint First Author).
I am exploring a new study reexamining the history of Chinese migration in the United States and the contentious performances of Chinese migrant communities, 1880s–1940s — a history that has been previously overlooked in the literature.
Hong Kong Sociological Association Annual Conference, Hong Kong
Social Science History Association Annual Meeting, Nazism and the Holocaust Session, Chicago, IL
American Sociological Association Annual Conference, Organizations, Occupations, and Work — Future of Work Panel, Chicago, IL
American Sociological Association Annual Conference, Asia and Asian American, Roundtable, Los Angeles, CA