ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. AI for Human Learning and Behavior Change
This article is part of the Research TopicAI and ResilienceView all 7 articles
Resilience through resistance: The role of worker agency in navigating algorithmic control
Provisionally accepted
- International Labour Organization, Geneva, Switzerland
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The business model of multi-sided digital labor platforms relies on maintaining a balance between workers and customers or clients to sustain operations. These platforms initially leveraged venture capital to attract workers by providing them with incentives and the promise of flexibility, creating lock-in effects to consolidate their market power and enable monopolistic practices. As platforms mature, they increasingly implement algorithmic management and control mechanisms, such as rating systems, which restrict worker autonomy, access to work and flexibility. Despite limited bargaining power, workers have developed both individual and collective strategies to counteract these algorithmic restrictions. This article employs a structured synthesis, drawing on existing academic literature as well as surveys conducted by the International Labour Office (ILO) between 2017 and 2023, to examine how platform workers utilize a combination of informal and formal forms of resistance to build resilience against algorithmic disruptions. The analysis covers different sectors (freelance and microtask work, taxi and delivery services, and domestic work and beauty care platforms) offering insights into the changing dynamics of worker agency on platforms.
Keywords: algorithmic management, control resistance relationship, digital labor platforms, resilience, worker agency, worker contestation, worker resistance
Received: 25 Mar 2025; Accepted: 10 Dec 2025.
Copyright: © 2025 Williams and Rani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Morgan Williams
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