Work

Resisting algorithmic control: Understanding the rise and variety of platform worker mobilisations

Year: 2022

Type: article

Abstract: Algorithms are seen as effective for managing workers. Literature focuses mainly on the functioning and impact of algorithmic control on workers' experiences and conditions. The ways in which platform workers have organised collectively to regain control have received far less scholarly attention. This paper addresses this gap by making sense of the mobilisation dynamics of two platform‐work categories: crowdwork ( Amazon Mechanical Turk ) and work on‐demand (food‐delivery couriers). These are salient mobilisation cases, as these workers have resisted algorithmic control by adopting specific organising modes, action repertoires and collective solidarities. By analysing a combination of extant literature and policy reports concerning each category of mobilisation forms at a global level over 5 years, the study elucidates why and how these workers were able to act without the involvement of traditional trade unions by showing that specific supportive communities and political activism traditions were crucial in the rise and variety of mobilisation.

Source: New Technology Work and Employment

DOI: 10.1111/ntwe.12257

Author: Lorenzo Cini

Institution: University College Dublin

Language: English

Topic: Digital Economy and Work Transformation

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

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

Open Access status: hybrid

Estimated APC paid: $3,500