中国人工智能研究热点与趋势 ——基于中文社会科学引文索引（CSSCI）论文的分析

Research frontiers and trends of artificial intelligence research in China -- an analysis based on CSSCI database

摘要:

人工智能对伦理、创新、教育和法律带来的影响日益凸显，但传统上关于人工智能的研究多以定性为主、少有数据分析，少数定量研究关注的维度较为单一，为更准确地把握人工智能研究的前沿热点，对发表于中文社会科学引文索引（CSSCI）数据库中2017－2023年有关人工智能的文献进行计量分析和系统评述。运用文献分析软件，对文献发表时间、出版期刊、核心作者、发文机构等方面进行可视化分析和知识图谱分析，识别出关于人工智能研究领域的热点。结果发现：中国人工智能的有关研究在2017年进入发展期，2018年进入爆发期，主要从哲学、管理学、教育学和法学的角度开展；人工智能伦理、管理方式变革、教育管理与政策以及人工智能的法律规制成为当前人工智能研究的主要内容；未来人工智能的热点前沿主要包括人工智能与数字经济的结合、人工智能发展的伦理困境、人工智能机器的地位辨析和人工智能对劳动力市场的影响等议题；未来学术界关于人工智能的研究重点会随着技术的进一步迭代和政策的持续深化而变化，研究主题会更为集中且向纵深发展，从识别一般规律到探寻具体对象的可操作化路径，研究路径从理论探索到实践指引演化。

Abstract:

The impact of artificial intelligence (AI) on ethics, innovation, education, and law has become increasingly prominent, but traditionally the research on AI is mostly qualitative, with little data analysis, a few quantitative studies focus on a relatively single dimension. In order to more accurately grasp the frontier hotspot of artificial intelligence research, this paper conducts quantitative analysis and systematic review on relevant literature of AI from 2017 to 2023 published in the Chinese Social Science Citation Index (CSSCI) database. Visualization analysis and knowledge graph analysis are conducted from the aspects of publication time, journals, core authors, and publishing institutions, to identify the hotspots in the field of artificial intelligence research. The results find that the relevant studies on AI in China have entered a period of development in 2017 and exploded in 2018, mainly conducted from the perspectives of philosophy, management, pedagogy, and law, the main contents of current research include ethical issues, transformation of management methods, educational management and policies, as well as legal regulation, and the hotspots and frontiers in the future mainly involve the integration of AI and digital economy, ethical dilemmas in AI development, the status of AI machines, and the impact of AI on the labor market. In the future, academic research on AI will change with further technological iteration and continuous deepening of policies, with research topics becoming more focused and developing in depth, from identifying general laws to exploring operable paths for specific objects, and from theoretical exploration to practical guidance.