The Federal Ministry of Labour and Social Affairs (BMAS) is promoting operational Innovation Spaces for AI learning and experimentation as part of the New Quality of Work Initiative (INQA). Here, companies and employees can test the introduction and use of operational AI solutions. The focus is on the human-centric use of AI developed through social partnerships.
The use of Artificial Intelligence (AI) will play a decisive role in determining the competitiveness of companies worldwide over the next few years. The German corporate sector is therefore increasingly focusing on the development and use of AI systems. As part of the national AI strategy, the Federal Government is promoting the development of human-centric AI applications providing benefits for the common good. As the use of AI poses challenges for small and medium-sized enterprises in particular, BMAS is promoting operational Innovation Spaces for AI learning and experimentation. These are spaces or processes that recreate realistic conditions and tangibly test how AI can be used successfully in different sectors and areas of activity. At the same time, companies and their employees are assisted in their joint efforts to shape the use of AI technologies.
11 projects – 50 companies
Since the end of 2020 the operational Innovation Spaces for AI learning and experimentation have been supporting 11 innovative projects; this assistance will last for up to three years. Around 50 small and large companies from different sectors – from the trades to nursing care and mechanical engineering – have been involved alongside numerous universities, research institutes and other organisations. You can track their progress on the project website.
Projects as diverse as the economy
The projects in the Innovation Spaces for AI learning and experimentation cover a wide range of economic sectors. The DiCo project is looking at how AI applications can assist nursing care professionals in their work. AIXPERIMENTATIONLAB is helping service staff to make good decisions based on data. KARAT records the individual stress load of professional drivers, helping them to reduce its effects. MeKIDI is developing human-centric AI-based process digitalisation for the energy industry. KI-Café is testing an interactive roll-out strategy for an AI system in manufacturing. KIDD is exploring ways of including different perspectives in the design process of AI systems and how people with a variety of backgrounds can be involved.
Examples of operational practice
The Innovation Spaces for AI learning and experimentation are a practice-oriented approach aimed at sustainably boosting the human-centric and socially oriented use of AI for companies and employees. All the experimentation spaces require employees and their representatives to be involved throughout the course of the project. The aim is to test possible applications in operational practice that can be transferred to other companies and sectors. For this reason, all projects are being monitored by scientific experts and their results are documented and published.