When food‐delivery platform workers consent to algorithmic management: a Foucauldian perspective

Abstract

This paper extends research on algorithmic management by examining mechanisms of compliance. Algorithmic management has predominantly been analysed in terms of the exercise of disciplinary power over workers and rational control of labour. Facing algorithms, platform workers would be in a situation of fear, passivity and frustration. In this paper, we utilise the Foucauldian framework of ‘dispositive’ in order to reconceptualise platforms as exerting both rational and normative control. Based on a qualitative case study of the food‐delivery platform Deliveroo, we underscore that algorithmic rational control, although fallible, is being reinforced by techniques of subjectification. Several dispositives on the platform, such as the pay‐per‐delivery and shift picker systems, generate an active mobilisation of workers. Our discussion highlights the governmentality power of algorithmic management, which builds consent by promoting a hyper‐meritocratic ideal of justice.

The intersectional precarity of platform cycle delivery workers

“…This chapter adds to a growing body of literature focusing on the precarious working conditions of food couriers in the gig economy (Briziarelli 2018, Lemozy 2019, Veen et al 2019, Cant 2020, Galière 2020, Gregory 2020, Gregory and Maldonado 2020, Richardson 2020, Woodcock 2020.…”

Algorithms, contexts, governance: An introduction to the special issue

“…The concept of algorithmic governance is arguably the broadest way to conceptualize the power of algorithms. Compared with more focused terms such as algorithmic regulation (Ulbricht and Yeung, 2022), algorithmic governmentality (Harkens, 2018;Rouvroy, 2011), or the business-related algocracy (Aneesh, 2009) and algorithmic management (Galiere, 2020), algorithmic governance has been used to describe a variety of sociotechnical practices aimed at assessing, directing, regulating, and managing the behavior of both human and non-human agents (Danaher, 2016;Katzenbach and Ulbricht, 2019). In these practices, computational calculations, automated recommendation or decisionmaking, and machine learning stand central.…”

Impact of Electronic Monitoring on Employees: A Meta-Analysis

“…The neglect of the importance of electronic monitoring research in these areas is worrisome. More and more employees are affected by electronic monitoring and trends like algorithmic management cannot exist without invasive employee monitoring (Galière, 2020;Möhlmann & Zalmanson, 2017). Beyond that, some scholars argue that monitoring is already the default in nowadays technological systems (Johnson et al, 2014) and thus is not a temporal phenomenon but will accompany employees and organizations for a long time.…”

“…For example, in algorithmic management an algorithm distributes tasks, regulates work processes, and controls performance. This management style is more and more widespread in technology corporations and cannot work without collecting data on employees' behavior (Galière, 2020;Möhlmann & Zalmanson, 2017). This way, monitoring is present in a greater intensity and extent than previously seen.…”