Berlin, 16 March 2023. ADM systems are used to automatically scan CVs during the hiring process, allocate shifts to employees, conduct work performance evaluations, select employees for educational programs or promotions, and they might even be used to decide who to lay off. With the help of AI applications, underlying structures in data sets at hand can be detected, which allows for predicting future developments. Such predictions can lead to decisions that have far-reaching consequences for the staff.
Due to the opacity of these systems, they further advance the power imbalance between employers and employees. The employees are the ones being subjected to the decisions of these systems while they can’t evaluate if their decisions are fair, just, and based on appropriate data sets. After all, what’s missing is an oversight authority for these systems. “Automated decision-making systems in workforce management undermine established processes that ensure worker participation. Without an insight into these systems, employees exposed to them more often than not remain powerless. For this reason, comprehensive transparency has to be introduced as a standard. Furthermore, employees must be included and have a say in every process concerning their workplace,” the study’s co-author, Dr. Anne Mollen, concludes.
With the AI Act, the European Union currently tries to regulate the use of ADM systems, as they are considered to pose high risks to individuals. This approach, however, only addresses worst case scenarios in the workplace. Further political measures, such as mandatory transparency requirements, are essential to avoid having ADM systems keep levering out traditional forms of employee representation and co-determination.
Co-determination in practice
When ADM workplace management systems are introduced, employees and their representatives should actively attend to their interests during the entire planning, development, implementation, and deployment processes. An exchange with Machine Learning experts could help them get a basic understanding of fundamental systemic connections and ask important questions on a case-by-case basis. This would enable them to look at these systems critically, see their shortcomings, and assess the potential risks that come with them.