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msg is participating in the

msg is participating in the "KIDD" project funded by the German Federal Ministry of Labor and Social Affairs

msg is participating in the "KIDD" project funded by the German Federal Ministry of Labor and Social Affairs

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29/07/2021

With the product "msg.ProfileMap", msg is participating in the research project "AI at the Service of Diversity" (KIDD) of the German Federal Ministry of Labor and Social Affairs (BMAS). The aim of the project is to develop standardized processes and criteria for the fair, non-discriminatory use of human-centered, AI-based systems in an operational context.

Eight companies and partner organizations are part of the KIDD consortium, which is implementing the research project over a period of three years (until September 2023). msg is one of them and is testing the personnel planning system msg.ProfileMap within a learning and experimentation space. This is an AI-based system that uses natural language understanding to check employees for their skills, potential and availability. Based on this, it enables optimized project and offer matching and thus an optimization of project assignments and workloads. In the course of the project, msg is further developing the product with financial support from the BMAS under the umbrella of the “Initiative New Quality of Work” (Initiative Neue Qualität der Arbeit (INQA)) and is gaining significant experience in order to eliminate discriminatory biases.

"Diversity panel" tests systems for discrimination potential

To prevent the potential of discrimination in used data, it is important to accompany and control the processes when introducing and using digital systems. For this, it is crucial to consider different perspectives and to actively involve people with diverse backgrounds in the process development of systems. To this end, a key task for each of the research projects is to pilot and test the processes of the system with the involvement of a "diversity panel." This panel is made up of as diverse a group of employees and experts as possible. The experience gained from this will serve as the basis for standardized processes and criteria that can also be applied in other operational contexts and issues relating to digital and AI-based systems.