Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis.

Journal: PloS one
PMID:

Abstract

Artificial intelligence (AI) is emerging as a technology at the center of many political, economic, and societal debates. This paper formulates a new AI patent search strategy and applies this to provide a landscape analysis of AI innovation dynamics and technology evolution. The paper uses patent analyses, network analyses, and source path link count algorithms to examine AI spatial and temporal trends, cooperation features, cross-organization knowledge flow and technological routes. Results indicate a growing yet concentrated, non-collaborative and multi-path development and protection profile for AI patenting, with cross-organization knowledge flows based mainly on interorganizational knowledge citation links.

Authors

  • Na Liu
  • Philip Shapira
    Manchester Institute of Innovation Research, Alliance Manchester Business School, University of Manchester, Manchester United Kingdom.
  • Xiaoxu Yue
    School of Public Policy and Management, Tsinghua University, Beijing, China.
  • Jiancheng Guan
    School of Economics and Management, University of Chinese Academy of Sciences, Beijing, China.