Algorithmic Management and Occupational Safety: The End Does not Justify the Means

The fourth industrial revolution has greatly impacted the domain of occupational safety and health. Advanced data-driven techniques, such as reliability engineering and predictive based safety, can be of great help in reducing workplace accidents. Data-driven techniques in the workplace can also be used to automate management tasks, judge performance and dictate the workflow of employees. This practice is called algorithmic management and, when used to reduce workplace accidents, is indistinguishable from advanced, professional predictive based safety. Algorithmic management is often used to attain greater productivity and can lead to a level of work intensity that is dangerous for the safety and health of employees. Thus, algorithmic management can be used to reduce workplace accidents, but also pose a risk for the overall health of employees. In this article, three guidelines are given that ensure algorithmic management helps worker safety, instead of endangering it, namely: algorithmic management should only be used for the goal of worker safety, it should never be used to grade the performance or discipline employees. The system should be transparent and understandable for every employee that it is applied to. These guidelines are illustrated by examples of algorithmic management and a discussion of the current laws and regulations. The article concludes with the implications for policy and further research.

Authors: Zoomer, T., Beek, D. van der, Gulijk, C. van, Kwantes, J.H.

Source: Springer, Reliability Engineering and Computational Intelligence for Complex Systems: design, Analysis and Evalution