“目标-议题-工具”框架下人工智能国家政策解析及发展建议——基于近十年政策文本镜像扫描

ANALYSIS AND DEVELOPMENT SUGGESTIONS FOR NATIONAL POLICIES ON ARTIFICIAL INTELLIGENCE UNDER THE FRAME WORK OF"GOALS-ISSUES-TOOLS"--BASED ON MIRROR SCANNIG OF POLICY TEXT BASEDIN THE PAST DECADE

人工智能是新一轮科技革命和产业竞争的战略制高点,中国政府密集出台政策支持其实现高质量的快速发展。通过对近十年人工智能国家政策文本在“政策目标——政策议题——政策工具”的三维框架下编码,结果发现:人工智能国家政策以构建新兴产业格局、构建科技创新体系为主要政策目标,缺乏对基础设施完善以及高端人才培育的目标关注;政策议题聚焦产业发展和行业应用,并逐步向经济、社会、国防、生态等多领域渗透,呈现出人工智能发展方向的转变,忽视基础研究和技术研发的发展态势;政策工具方面表现出供给型工具远超需求型工具的现象,未形成供给型“推力”与需求型“拉力”的良性互动局面。基于此,文章从成立有效监管机制、厘清战略目标定位、丰富政策工具使用、长期支持基础研发、完善数据生态系统、体现人文关怀等方面提出了促进我国人工智能健康可持续发展的建议。

Artificial intelligence is the strategic commanding point of the new round of technological revolution and industrial competition,and the Chinese government has intensively introduced policies to support its high-quality and rapid development.By encoding the national policy texts on artificial intelligence in the past decade within the three-dimensional framework of"policy goals-policy issues-policy tools",it was found that the main goals of national policies on Artificial intelligence national policies are to build emerging industry patterns and technological innovation systems,lacking attention to the goals of improving infrastructure and cultivating high-end talents;Policy issues focus on industrial development and application,and gradually penetrate into various fields such as economy,society,national defense,ecology,etc.,showing a shift in the development direction of Artificial intelligence development,neglecting the development trend of basic research and technological research and development;In terms of policy tools,there is a phenomenon of supply based tools far exceeding demand based tools,and a positive interaction between supply based"push"and demand based"pull"has not been formed.Based on this,the article proposes suggestions to promote the healthy and sustainable development of artificial intelligence in China from the aspects of establishing an effective regulatory mechanism,clarifying strategic goals,enriching the use of policy tools,long-term support for basic research and development,improving the data ecosystem,and reflecting humanistic care.