Data-driven Innovation or Innovation-driven Data Generation?

With the emergence of artificial intelligence (AI), data-driven innovation has become a new paradigm in innovation management. As these solutions are increasingly integrated into complex, safety-critical systems, data becomes crucial in these contexts. However, safety-critical applications require high-quality and verified data in areas where sometimes only sparse data is available. This paper explores the role of data in these contexts and sheds light on data and innovation in complex intelligent systems (CoIS). The findings reveal that a lack of available data may hinder the innovation process and that the necessary training data must be generated through the innovation itself. The results thus show that the emerging data-driven innovation paradigm needs to be complemented with a focus on understanding innovation-driven data generation in the context of systems with safety-critical applications.