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Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis
Na Liu1, Philip Shapira2,3, Xiaoxu Yue4
1School of Management, Shandong Technology and Business University, Yantai, China.
Plos One
|December 31, 2021
Summary
This study introduces a novel AI patent search strategy to analyze innovation dynamics. AI patenting shows growth but is concentrated and non-collaborative, with knowledge flow mainly through citations.
Area of Science:
- Computer Science
- Intellectual Property Law
- Innovation Studies
Background:
- Artificial intelligence (AI) is a central technology in political, economic, and societal discussions.
- Understanding AI innovation dynamics is crucial for policy and strategic development.
Purpose of the Study:
- To develop and apply a new AI patent search strategy.
- To analyze the landscape of AI innovation dynamics and technology evolution using patent data.
Main Methods:
- Patent analysis
- Network analysis
- Source path link count algorithms
- Examination of spatial and temporal trends, cooperation, knowledge flow, and technological routes.
Main Results:
- AI patenting is growing but concentrated.
- The development and protection profile for AI is non-collaborative and multi-path.
- Cross-organization knowledge flows primarily rely on interorganizational knowledge citation links.
Conclusions:
- The current AI patent landscape indicates a complex and evolving innovation ecosystem.
- Further research into fostering collaboration within AI patenting may be beneficial.
- The developed search strategy offers a robust method for analyzing AI technology trends.
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