A Comparative Study on National Science and Technology Strategic Decision Modes of Artificial Intelligence Between China and the United States——Based on the Perspective of Multiple Decision-Making
Yue Kun1, Fang Chao1,2
1. Qiyuan Lab,Beijing 100095,China; 2. Lab for High Technology,Tsinghua University,Beijing 100084,China
Abstract：Accelerating the modernization of national science and technology strategic decision of artificial intelligence is the requirement to win global science and technology competition externally,improve governance level internally and regulate major risks under complex situations.Meanwhile,diversified decision-making is an important symbol and way to realize decision-making modernization.From the perspective of multiple decision-making,the research analyzes its role in guiding breakthrough innovation and regulating major risks from the time dimension,carries out the comparative analysis of China-US strategic decision-making system from the space dimension,and puts forward some suggestions on improving the multiple decision-making mechanism of Chinese.Firstly,it is necessary to enrich the suggestion channels,highlight the problem-orientation and international vision in the start-up stage.Secondly,enhance the level of interdisciplinary and multidisciplinary decision support in the research and formulation stage.Thirdly,strengthen the multi-dimensional guidance of decision-making in key regions and fields,strengthen the prediction and control of major risks in the feedback stage.The above measures can better support the modernization process of decision-making in the strategic field of science and technology and improve the level of strategic decision-making in frontier fields such as artificial intelligence.
岳昆, 房超. 中美人工智能国家科技战略决策模式比较研究——基于多元决策视角[J]. 中国科技论坛, 2023(1): 170-177.
Yue Kun, Fang Chao. A Comparative Study on National Science and Technology Strategic Decision Modes of Artificial Intelligence Between China and the United States——Based on the Perspective of Multiple Decision-Making. , 2023(1): 170-177.
2023, 
