AI-based Competence Assistants for the Future of Work
The project Kern ("Kompetenzen entwickeln und richtig nutzen") develops new concepts for the intelligent competence management of employees in the digital workplace. The idea of the project is to combine competence models gathered by interviews and surveys with an AI-based approach. Hereby, software-based prototypes should be implemented and tested in lab and field studies. The overall goal is to implement AI-based competence assistance systems in the work environment in order to support employees' competence management.
The project is coordinated by the IISM and carried out in cooperation with B.Braun Melsungen AG, Campusjäger GmbH, SAP SE, and TÜV Rheinland Akademie GmbH. Kern is funded by the German Federal Ministry of Labour and Social Affairs with 1.36 million Euros within the program of the “Initiative Neue Qualität der Arbeit” (INQA) on the basis of a resolution of the German Bundestag.
The solution approach of Kern includes a combination of different modules (see Figure 2 for an overview). Competence models should be collected top-down using established survey instruments and interview methods. These competence models are complemented by competence assistance systems - technical solutions that focus on employees' competence needs and their management. The competence assistance systems follow a bottom-up approach, in which competences are extracted from different data sources, such as usage data or physiological data (see Figure 1 for exemplary wearable devices).
Figure 1: Copyright by Polar GmbH and Empatica Inc.
Figure 2: Overview Kern Project.
Further information is available on the official website of the Kern project at https://kern-kas.org as well as on the INQA Experimental Room pages at https://www.arbeitenviernull.de/experimentierraeume/gefoerderte-projekte/inqa-experimentierraeume/kern.html and https://www.inqa.de/DE/Mitmachen-Die-Initiative/Foerderprojekte/Projektdatenbank/KERN.html.
- Physio-Adaptive Systems- A State-of-the-Art Review and Future Research Directions. Loewe, N.; Nadj, M. 2020. Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference, June 15-17, 2020. doi:10.5445/IR/1000120026
- My Virtual Colleague: A State-of-the-Art Analysis of Conversational Agents for the Workplace . Feng, S.; Buxmann, P. 2020. Proceedings of the 53rd Hawaii International Conference on System Sciences (HICSS), Maui, 07.-10. January 2020. doi: 10.24251/HICSS.2020.020
- Fundamentals of physiological computing. Fairclough, S. 2009. Interacting with Computers, Volume 21, Issue 1-2, January 2009. doi:10.1016/j.intcom.2008.10.011