8. Delivering Collective Solidarity and the Role of TikTok

This chapter delves into the emerging forms of collective resistance among food-delivery drivers, facilitated by algorithmically powered social media platforms like TikTok. Unlike traditional offline organising, this study highlights how drivers creatively harness machine-learning algorithms to build solidarity and coordinate action. The chapter presents a novel theoretical understanding of algorithmic power in the digital workplace, challenging the dominant perspective that portrays machine-learning algorithms as instruments of despotic control. It argues that these algorithms can be strategically appropriated by workers to resist and subvert managerial control. The study draws on detailed observations of Chinese food-delivery drivers' everyday interactions on TikTok to develop a process model illustrating how drivers forge and sustain new forms of resistance powered by TikTok's algorithmic recommendations. The model identifies three primary functionalities of algorithmic recommendations within the digital labour process: datafication and connection, agglomeration and bonding, and discipline and amplification. These functionalities work in a cyclical manner, facilitating a dynamic resistance process that begins with the visualisation of anger and grievance, moves through digital unionisation and solidarity, advances to collective mobilisation, and culminates in antagonistic actions that directly challenge the exploitative conditions of platform labour. The chapter also explores how drivers leverage TikTok's algorithmic recommendations to organise strikes and video protests, demonstrating the platform's role in fostering collective action and challenging platform dominance. The analysis underscores the potential for articulating workers' power of resistance within digital spaces and calls for policy reforms to institutionalise digital labour unions in the contemporary digital workplace.