Documents Abraha, Halefom 2 results

"The promise—and perils—of algorithmic management are increasingly recognised in the literature. How should regulators respond to the automation of the full range of traditional employer functions, from hiring workers through to firing them? This article identifies two key regulatory gaps—an exacerbation of privacy harms and information asymmetries, and a loss of human agency—and sets out a series of policy options designed to address these novel harms. Redlines (prohibitions), purpose limitations, and individual as well as collective information rights are designed to protect against harmfully invasive data practices; provisions for human involvement ‘in the loop' (banning fully automated terminations), ‘after the loop' (a right to meaningful review), ‘before the loop' (information and consultation rights) and ‘above the loop' (impact assessments) aim to restore human agency in the deployment and governance of algorithmic management systems."

"The regulation of algorithmic management falls under the purview of multiple legal domains including but not limited to labour law, non-discrimination law and data protection law. While labour law does not have explicit provisions to adequately protect workers from algorithmic harms, existing non-discrimination and data protection laws can address some aspects of these harms. This article examines the extent to which the GDPR offers the necessary tools to protect workers from harm stemming from algorithmic management. It argues that while the provisions tailored to automated decision-making (ADM) and the rest of the GDPR provide workers with some limited protections, significant gaps remain. It then suggests some policy options on how the existing protections under the GDPR can be further complemented, particularised, and strengthened through a combination of legislative and non-legislative measures."