Flooding the landscape of knowledge: perspectives on transitions to artificial intelligence in industry

Abstract

The progress in artificial intelligence (AI) technology is advancing at an unprecedented pace and its applications increasingly impact economic actors and society at large. As the world enters the fourth industrial revolution, the integration of AI technology into industries promises to become a crucial determinant of economic performance and qualitative change within the economy. It also requires to discuss the roles of humans and machines in the process of value creation. Against this backdrop, this doctoral dissertation investigates the current state and dynamics of AI transitions, with a pronounced focus on industrial regimes. It comprises three empirical studies, each depicting different levels of industrial transitions towards AI—moving from a consideration of micro-level technological niches, to meso-level industrial structures, to macro-level landscape trends. This dissertation contributes to our understanding of socio-technical transitions towards AI by showing that sustainable and just transitions towards AI-based industrial regimes require not only consideration of the technological characteristics, but also the sociomaterial context governing its integration, as well as reversely being altered by the diffusion of the technology itself. The work provides further insights for policymakers, practitioners, and researchers as it emphasizes the need for network-based analyses of complex diffusion dynamics within industries, and the need to integrate systemic socio-economic perspectives into extant concepts of responsible AI.