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Short abstract:

Applying an actor-network theory framework, this paper examines labor exploitation and power imbalances encoded within China's on-demand platform economies by tracing associations between algorithms, interfaces, workers, and platform owners.

Long abstract:

The convenient interfaces and intelligent algorithms powering China's booming platform economy obscure an invisible workforce subjected to economic instability and algorithmic control. Drawing on actor-network theory, this paper critically analyses the dynamics of labour exploitation as firms like Meituan, Didi and others adopt algorithmic management, data-driven dispatching, and integrated AI systems. Architectural mappings initially conceal real workers outside platform boundaries and activities. However, tracing associations reveals human actors driving the training data, content filtering, AI optimisation and microtask execution necessary for advancing automation and machine learning. These overlooked workers haunt projected technological futures, embodying the shadow labour force sustaining digital facades. Sociotechnical arrangements enact power asymmetries as platform owners govern through algorithmic protocols optimised for efficiency, scalability and capital growth over worker welfare. However, recognising points of vulnerability also reveals possibilities for reform through alternative network configurations that distribute definitional authority and economic stability more equitably across gig workforces and the platform owners increasingly dependent on their ghosted work. This paper contributes to research on the sociology of invisible work and global platform economies by highlighting concealed human actors struggling for justice within China’s growing on-demand infrastructure.