Algorithmic management at work beyond the gig-economy: from practices to theory (and regulation)

Abstract: In recent years, practices of algorithmic management have been widely adopted to analyse how applicants behave during job interviews, monitor remote work, rate workers’ performance and set wage adjustments. Simultaneously, the condition of subjection to the upstream authority of managers has been intensified. By adopting a qualitative empirical approach, this presentation maps the experiences of a group of private-sector employees with digitised human resources management (HRM) practices. It gathers testimonies on how companies are organising, monitoring and recruiting their workforce, and explores which methods are adopted by managers in “ordinary” employment settings and industries.

Employment protection legislation recognises the need to curb the unilateral discretionary power of the dominant contractual party by deploying several controlling factors. However, the traditional guardrails have now been displaced by the transformative impetus exerted by data-driven technologies. Therefore, by embracing a multidimensional, anticipatory and participatory approach, this presentation addresses the consequences of power augmentation on workplace bargaining and informational dynamics. 

Using examples from the field of strategic litigation, I discuss the mutually reinforcing relationship between the General Data Protection Regulation’s provisions and anti-discrimination measures, thanks to which automated decisions can be rendered explainable and contestable. I also call for the involvement of worker representatives in co-designing HRM policies, thereby closing power gaps and eradicating algorithmic biases.​