Machine Learning (ML) is the key technology for cognitive systems based on Artificial Intelligence (AI) and thus one of the decisive factors for global economic development. A fact-based discussion of AI- and ML-based technologies is fundamental to Germany's and Europe's sustainable positioning in international competition.
There is hardly any area that is not being decisively transformed by ML- and AI-based technologies: from goods production to logistics to medical technology. The sheer number of possible applications is one reason for the public interest. However, the debate is often characterized by half-knowledge, assumptions and myths. Clarification is needed, because social acceptance is of central importance for the further spread of machine-based learning methods.
This is where the study "Machine Learning – Competencies, Applications and Research Needs" comes in, which was conducted in the context of a project funded by the German Federal Ministry of Education and Research (BMBF). The project was carried out by the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, the Fraunhofer Center for International Management and Knowledge Economy IMW, and the headquarters of the Fraunhofer-Gesellschaft. The study provides a compact introduction to the most important concepts and methods of Machine Learning, an overview of challenges and new research questions. Furthermore, it provides an overview of actors, application fields and socio-economic framework conditions of research with a focus on Germany as a location.