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Governance theory, Euro−American practice and optimization of generative AI from agile perspective
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Qian SUN1, Yingying JIA2, Chengyu CUI1, Dong GUO3, *
Science & Technology Review | 2026, 44(15) : 153 - 160
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Science & Technology Review | 2026, 44(15): 153-160
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Governance theory, Euro−American practice and optimization of generative AI from agile perspective
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Qian SUN1, Yingying JIA2, Chengyu CUI1, Dong GUO3, *
Affiliations
  • 1School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China
  • 2School of Public Management, Renmin University of China, Beijing 100872, China
  • 3School of Economics and Management, Communication University of China, Beijing 100024, China
Published: 2026-08-13 doi: 10.3981/j.issn.1000-7857.2025.06.00014
Outline
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As an emerging digital technology, generative artificial intelligence represented by DeepSeek and ChatGPT has given birth to new scenes, new formats and new markets. However, the uncertainty risk of emerging technologies has also brought the impact of traditional governance structure and paradigm, posing new challenges to governance capacity and governance system. Facing the requirements of "good governance" and combining with the theory of agile governance, this paper puts forward the framework of agile governance of generative artificial intelligence, which can provide reference for the future selection of governance concept and tool mode of generative artificial intelligence in China. Based on the theory of governance, this paper systematically analyzes the international governance practices of generative artificial intelligence in the United States and the European Union, and explores the consensus indicators and differences of international governance concepts of artificial intelligence from four aspects: governance objectives, governance subjects, governance means and governance relations. The optimization ideas of the governance of generative artificial intelligence in China were put forward, namely, following the flexible hierarchical governance principle, building a multi−agent interactive network governance relationship, and adopting proactive governance ideas, so as to adapt to the dynamic characteristics and uncertain risks of new technologies, actively promote the healthy and orderly development of generative artificial intelligence technology and industry, and realize the technological goodness.

generative artificial intelligence  /  AI risks  /  digital technology governance  /  agile governance
Qian SUN, Yingying JIA, Chengyu CUI, Dong GUO. Governance theory, Euro−American practice and optimization of generative AI from agile perspective[J]. Science & Technology Review, 2026 , 44 (15) : 153 -160 . DOI: 10.3981/j.issn.1000-7857.2025.06.00014
Year 2026 volume 44 Issue 15
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Article Info
doi: 10.3981/j.issn.1000-7857.2025.06.00014
  • Receive Date:2025-06-04
  • Online Date:2026-08-31
  • Published:2026-08-13
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  • Received:2025-06-04
  • Revised:2026-05-06
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Affiliations
    1School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    2School of Public Management, Renmin University of China, Beijing 100872, China
    3School of Economics and Management, Communication University of China, Beijing 100024, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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