Automated Processing of Data on Work Performance and Employee Evaluation: A Case Study of Practices at Amazon Warehouses in Poland

Authors

  • Marta Rozmysłowicz Adam Mickiewicz University https://orcid.org/0000-0001-5961-5075
  • Piotr Krzyżaniak Adam Mickiewicz University

DOI:

https://doi.org/10.6092/issn.1561-8048/18084

Keywords:

Algorithmic Employee Evaluation, Algorithmic Management, Amazon Warehouses, GDPR, Human Intervention

Abstract

The subject of this article is the algorithmic employee evaluation system at Amazon’s warehouses in Poland. A weekly performance review, the evaluation is a measure of productivity and quality, gathered in real time as warehouse associates scan barcodes throughout the working day. Evaluation results instruct on the employment status of individual workers, without any input from supervisors. The article probes the significance of the European General Data Protection Regulation (GDPR) for bolstering job security at workplaces like Amazon, where HR decisions are automated and based on the processing of work performance data. Article 22 of the GDPR lays down a prohibition for decision-making based solely on the automated processing of personal data. In turn, it establishes the right to human intervention, which might allow employees to avoid the adverse effects of an employee evaluation, if it did not ensure significant human input. Departing from a shop-floor level view of Amazon’s employee evaluation system that is reinforced by insight gained through litigation in Polish labour courts, this article argues that the process of evaluating workers is not a purely technical operation that can be consigned to algorithmic management. Employee evaluation must abide by certain legal criteria, which ultimately requires human discretion.

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Published

2023-12-14

How to Cite

Rozmysłowicz, M., & Krzyżaniak, P. (2023). Automated Processing of Data on Work Performance and Employee Evaluation: A Case Study of Practices at Amazon Warehouses in Poland. Italian Labour Law E-Journal, 16(2), 149–164. https://doi.org/10.6092/issn.1561-8048/18084

Issue

Section

Miscellaneous