The Governance of Algorithmic Management: A Comparative Analysis

• In Event: The Global Governance of Artificial Intelligence

Abstract

The use of AI-driven or AI-supported algorithmic management tools in the workplace, such as for shift- and task-assignments of employees, holds enormous promise to increase efficiency, e.g. by reducing errors and waste. It is therefore widely seen as inevitable (even by labor representatives, at least when interviewed off the record). At the same time, it has also prompted great concerns regarding the loss of autonomy, increased stress-levels, decreased motivation, and increased turn-over by workers/employees and corresponding socio-economic losses and political resistance. Recent attempts to govern such AI use (i.e., to algorithmic management) address these concerns to a highly variable extent. They also vary in the balance they strike between trying to prevent harms through restrictions and trying to enable beneficial uses. This paper will analyze the U.S. Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, the EU AI Act, and several private/non-governmental regulatory efforts, such as the AI standards developed by the Joint Committee of the International Organization for Standardization and the International Electrotechnical Committee, to establish and explain the variance observed in how they (seek to) govern AI in algorithmic management

Author

• Tim Buthe, Technical University of Munich (TUM)