Technological Convergence of Artificial Intelligence Based on Multi-level Networks
LIU Xiaoyan1, SUN Li'na1, QIU Jingwen2, SHAN Xiaohong1
1. College of Economics and Management, Beijing University of Technology, Beijing 100124, China; 2. College of Information Management, Nanjing University, Nanjing 210023, China
Abstract：In order to better formulate policies for the development of artificial intelligence, this paper analyzes the technology convergence mechanism in the field of artificial intelligence by constructing the technology convergence network model. Based on the patent data from 2010—2019 of artificial intelligence field, combined with technology and organization dimension, this paper tries to analyzes from three aspects of technical characteristics, organization technical characteristics and organization relationship characteristics. The results show that: In the field of artificial intelligence, organization cooperation is sparse, fusion technology is relatively scattered, organization and technology have obvious core-edge structure characteristics. On the level of technical characteristics, similar technologies are easier to be converged, and technologies that have already been converged will promote new convergence; On the level of organizational technical characteristics, the common technologies owned by the orgnization will negatively affect the occurrence of convergence with other technologies; On the level of organizational relationship characteristics, the effect of cooperation between organizations on technological convergence is closely related to the development stage of the field, and the "circle of buddies" inhibits technology convergence.
刘晓燕, 孙丽娜, 裘靖文, 单晓红. 基于多层网络的人工智能领域跨界技术融合[J]. 复杂系统与复杂性科学, 2022, 19(1): 45-51.
LIU Xiaoyan, SUN Li'na, QIU Jingwen, SHAN Xiaohong. Technological Convergence of Artificial Intelligence Based on Multi-level Networks. Complex Systems and Complexity Science, 2022, 19(1): 45-51.
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