The Impact of Knowledge Coupling on Technological Generality in AI: The Moderating Role of Collaborative Innovation Network Centralities

Abstract

Artificial intelligence (AI) is widely regarded as a general-purpose technology in both academic and practical domains. One key technological application feature of AI is the varying degree of technological generality across different AI technologies. Drawing on theories of recombinant search and social network, this study explores how knowledge coupling influences AI technological generality. In addition, we examine the moderating effects of collaborative innovation network centralities, i.e., betweenness centrality and closeness centrality. Using a dataset of 10 575 AI patents between 1978 and 2016, our findings reveal an inverted U-shaped relationship between knowledge coupling and technological generality. Moreover, betweenness centrality strengthens the nonlinear relationship, whereas closeness centrality attenuates it. This research has important theoretical and practical significance for AI technological innovation and innovation collaboration strategies.