Achtung:

Sie haben Javascript deaktiviert!
Sie haben versucht eine Funktion zu nutzen, die nur mit Javascript möglich ist. Um sämtliche Funktionalitäten unserer Internetseite zu nutzen, aktivieren Sie bitte Javascript in Ihrem Browser.

AI for the working world of the industrial middle class

The technology "artificial intelligence" (in short: AI) is associated with far-reaching potentials and opportunities for transforming industrial value creation. AI is still perceived as a predominantly technical option. An understanding of AI in the working context as a comprehensive socio-technical challenge is established to some extent. To date, however, there is a lack of a holistic approach to work research in the context of AI that is close to SMEs and provides solution and application knowledge. This discrepancy is addressed in this project.  The basis for this is a comprehensive approach to the topic by connecting people - organization - technology and a solution and transfer-oriented focus in the implementation. The goal is a regional competence center "AI in the working world of medium-sized industrial companies" (KIAM). It is to function as a contact point for companies and all other actors in the industrial working world.

The project is carried out within the context of the technology cluster it's OWL and is funded by the Federal Ministry of Education and Research. The support amount is 10.7 million Euro.

Competence management, employee participation and technology acceptance

Artificial intelligence will fundamentally change the world of work: AI systems support work processes, take over tasks and create new fields of work. The identification of possible applications and the development of concrete solutions pose challenges, especially for small and medium-sized companies, such as a lack of skilled workers or unclear organizational and technological requirements. The Competence Center KIAM brings together findings from labour research in this future field. Main topics are, for example, workplace design, competence development and change management. In lighthouse projects, research institutions and companies develop concrete solutions in which AI technologies are made available for different fields of application.

Transfer to medium-sized businesses

The results and experiences from the lighthouse projects are to be made available to small and medium-sized enterprises. To this end, an information platform will be set up, good examples will be prepared, and events and workshops will be held. In further training courses, employees will be qualified for the use of AI technologies. In transfer projects, companies can use new AI technologies in cooperation with a research institution to solve concrete challenges in their company. Transfer partners of the Competence Center, such as owl maschinenbau and OstWestfalenLippe GmbH, provide support.

Contribution of the Chair of Organizational Behavior

Our chair is primarily involved in the project in three ways.  First, we investigate how organizational design changes through the use of AI-based solutions. Influences on organizational design as well as effects of the changed organizational design are investigated in detail. In addition, this work package investigates which measures and methods make AI more transparent and comprehensible for the employees.

Furthermore, we are involved in a lighthouse project with the goal of developing a user-centered, AI-based framework, whose components are the basis for the development of AI-based scalable, adaptive assistance services for different application scenarios in industrial production (e.g. system setup, system conversion, system malfunction, etc.) The aspects of user adaptability, collaborative solution finding between humans and assistance services as well as the content-related further development and learning ability of the overall system using artificial intelligence form the central cornerstones of the approach.

Besides, we are working in another lighthouse project to develop measures that enable the operational use of AI in sales, i.e. in the interface between employees* and customers. The aim is to measure acceptance for the use of AI-supported support processes and to learn best practices for creating employee and customer acceptance. It also examines how employees can be empowered to participate in the design of complex systems without having to become experts in the technology themselves.

 

 

The University for the Information Society