Confronting algorithmic management using subject access requests: Insights using the case of food deliveries

• Published in: The economic and labour relations review : ELRR Vol. 34; no. 4; pp. 720 - 732
• Main Author: Perrig, Luca
• Format: Journal Article
• Language: English
• Published: London Cambridge University Press 01.12.2023
• Subjects: Algorithms; Automation; Collective action; Collective bargaining; Data; Employment; Field study; Food; Gig economy; Labor law; Labor unions; Management; Personal information; Profiles; Workers; Switzerland
• DOI: 10.1017/elr.2023.55
• ISSN: 1838-2673; 1035-3046

Gig work is defined by a (mostly) automated management, operating remotely through an app. Without human interaction, workers are left with only guesses about the functioning of the algorithms they are subjected to. To better position themselves in their competition for tasks, they try to influence the data profile that platform build about them. Made of performance indicators, personal information, and sensor data, these profiles are an essential part of algorithmic management. This paper will identify data profiles as core sites of the struggle in the gig economy. It will discuss the benefits and limitations of bringing data at the centre stage through a workers’ inquiry of food delivery platforms. The analysis will distinguish three actors in this inquiry and discuss their uses of data profiles: the couriers themselves, as they attempt to make sense of algorithmic management; the researcher, and how they can use personal data in order to reconstitute this field of struggle; and the trade unions, which can provide a way to collectivise data governance and gain better information in building their case in favour of gig workers’ rights.