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When Transparency Backfires: The Complex Relationship Between Algorithmic Transparency and Gig-Worker Resistance

Year: 2025

Type: article

Abstract: Algorithmic transparency (AT) plays a key role in the gig economy, where platforms rely on algorithms for decision-making. While AT is intended to build fairness and trust, it can sometimes increase worker resistance. Using the elaboration likelihood model (ELM), this study explores when and why transparency may backfire and examines factors such as worker involvement, algorithmic familiarity, and information quality. A field survey of 480 gig workers will test the model, offering insights to help organizations implement AT effectively while minimizing resistance.

Source: Journal of the Association for Information Systems

Authors: Zohrabi, Mahsa, Johnson, Richard

Institution: Washington State University

Language: English

Topic: Digital Economy and Work Transformation

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDGs: Peace, justice, and strong institutions, Decent work and economic growth, Reduced inequalities

Open Access status: green

OpenAlex ID: W7016101174

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