Scenario 3: Inadmissible Performance Control of Employees

AI systems can relieve the burden of tedious or repetitive tasks and help workers avoid mistakes. By continuously collecting and analyzing data from the work process, collaborative systems adapt to workers and their routines. For example, self-learning robotic tools in production will in the future record step sequences and work techniques of skilled workers and be able to assist them at the appropriate time. By also processing physical parameters such as employees' stress levels, fatigue or concentration, AI systems further optimize collaboration and can provide indications of excessive or insufficient demands. On an aggregated level, individual job satisfaction and the efficiency of the company can thus be increased.

However, AI systems can also be misused to monitor employee performance. How this can be prevented is outlined in the following example of a company that uses self-learning and interconnected robotic tools in production.

The question of which measures are suitable for effectively preventing misuse of AI systems is also addressed in the white paper Protecting AI systems, preventing misuse by the IT Security, Privacy, Law and Ethics working group.