sustainability Article Preventing Patent Risks in Artificial Intelligence Industry for Sustainable Development: A Multi-Level Network Analysis Xi Yang 1,* and Xiang Yu 2 1 Center for Studies of Intellectual Property Rights, Zhongnan University of Economics and Law, Wuhan 430073, China 2 School of Management, Huazhong University of Science and Technology, Wuhan 430074, China;
[email protected] * Correspondence:
[email protected]; Tel.: +86-181-6273-0019 Received: 26 September 2020; Accepted: 16 October 2020; Published: 19 October 2020 Abstract: In recent years, assessing patent risks has attracted fast-growing attention from both researchers and practitioners in studies of technological innovation. Following the existing literature on risks and intellectual property (IP) risks, we define patent risks as the lack of understanding of the distribution of patents that lead to losing a key patent, increased research and development costs, and, potentially, infringement litigation. This paper aims to propose an explorative approach to investigating patent risks in the target technology field by integrating social network analysis and patent analysis. Compared to previous research, this study makes an important contribution toward identifying patent risks in the overall technological field by employing a patent-based multi-level network model that has not appeared in existing methodologies of patent risks. In order to verify the effectiveness of this approach, we take artificial intelligence (AI) as an example. Data collected from the Derwent Innovation Index (DII) database were used to build the patent-based multi-level network on patent risks from market, technology, and assignee perspectives. The results indicate that the lack of international collaborations among assignees and industry–university–research collaboration may lead to patent collaboration risks.