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Bulletin of Chinese Academy of Sciences (Chinese Version)

Keywords

artificial intelligence；manufacturing；innovation and development；policy suggestion

Document Type

Strategy & Policy Decision Research

Abstract

Artificial intelligence technology has become a key force in driving innovation and development in global manufacturing industries, and its application in production automation, intelligent management, and other areas has become an important trend for innovation and development of manufacturing in all countries. This study comprehensively analyzes the innovation and development trend driven by artificial intelligence in global manufacturing, outlines the policies and measures of major countries in promoting the innovation and development of the manufacturing industries driven by artificial intelligence. It also points out the current situation and problems of the manufacturing’s innovation and development driven by artificial intelligence in China, and relevant policy recommendations are presented. The aim of this study is to promote the innovation and development of China’s manufacturing industry empowered by artificial intelligence through strengthening technical system capabilities, standard leading capabilities, scenario creation capabilities, talent emergence capabilities, and risk governance capabilities.

First page

1329

Last Page

1339

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

1. 卢鹏, 黄媛媛. 人工智能驱动新质生产力形成的生成逻辑、运行机制与实践进路.重庆大学学报（社会科学版）, 2024, 30(4): 144-156. Lu P, Huang Y Y. Artificial intelligence driving the formation of new qualitative productivity: Generative logic, operational mechanisms, and practical approaches. Journal of Chongqing University (Social Science Edition), 2024, 30(4): 144-156. (in Chinese)

2. 周杰琦, 陈达, 夏南新. 人工智能的绿色发展效应：技术赋能和结构优化. 当代经济科学, 2023, 45(5): 30-45. Zhou J Q, Chen D, Xia N X. Green development effects of artificial intelligence: Technology empowerment and structural optimization. Modern Economic Science, 2023, 45(5): 30-45. (in Chinese)

3. 谢伟丽, 石军伟, 张起帆. 人工智能、要素禀赋与制造业高质量发展——来自中国 208个城市的经验证据. 经济与管理研究, 2023, 44(4): 21-38. Xie W L, Shi J W, Zhang Q F. Artificial intelligence, factor endowments and high-quality development of manufacturing industry—Empirical evidence from 208 cities in China. Research on Economics and Management, 2023, 44(4): 21-38. (in Chinese)

4. 任保平, 宋文月. 新一代人工智能和实体经济深度融合促进高质量发展的效应与路径. 西北大学学报（哲学社会科学版）, 2019, 49(5): 6-13. Ren B P, Song W Y. The effect and path of the deep integration of the new generation of artificial intelligence and the real economy to promote high-quality development. Journal of Northwest University (Philosophy and Social Sciences Edition), 2019, 49(5): 6-13. (in Chinese)

5. Kemp A. Competitive advantage through artificial intelligence: Toward a theory of situated AI. Academy of Management Review, 2024, 49(3): 618-635.

6. 李翔, 叶初升, 潘丽群. 人工智能何以提升中国制造业发展质量——索洛悖论在中国制造业的再检验. 兰州大学学报（社会科学版）, 2023, 51(4): 44-58. Li X, Ye C S, Pan L Q. How AI improves the development quality of china's manufacturing industry—Re-examination of Solow Paradox in China’s manufacturing industry. Journal of Lanzhou University (Social Sciences), 2023, 51(4): 44-58. (in Chinese)

7. 唐晓华, 迟子茗. 工业智能化提升工业绿色发展效率的实证研究. 经济学家, 2022, (2): 43-52. Tang X H, Chi Z M. Empirical study on industrial intelligence to improve the efficiency of industrial green development. Economist, 2022, (2): 43-52. (in Chinese)

8. 王文军, 李琪, 刘丹. 论人工智能时代绿色发展的挑战及应对. 西安财经大学学报，2020, 33(1): 30-36. Wang W J, Li Q, Liu D. Challenges and countermeasures of green development in the era of artificial intelligence. Journal of Xi’an University of Finance and Economics, 2020, 33(1): 30-36. (in Chinese)

9. 刘浩, 陈隽伟, 周小良. 数字化智能制造解决方案. (2017-02-27)[2024-07-17]. https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/technology/deloitte-cn-tech-dc-digital-whitepaper-zh-161201.pdf. Liu H, Chen J W, Zhou X L. Digital Intelligent Manufacturing Solutions. (2017-02-27)[2024-07-17]. https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/technology/deloitte-cn-tech-dc-digital-whitepaper-zh-161201.pdf.(in Chinese)

10. Kitain L. Digital Twin-The New Age of Manufacturing. (2018-12-05)[2024-07-17]. https://medium.datadriveninvestor.com/digital-twin-the-new-age-of-manufacturing-d964eeba3313.

11. 孙毅, 罗穆雄. 美国智能制造的发展及启示. 中国科学院院刊, 2021, 36(11): 1316-1325. Sun Y, Luo M X. Development and enlightenment of American intelligent manufacturing. Bulletin of Chinese Academy of Sciences, 2021, 36(11): 1316-1325.(in Chinese)

12. The National Security Commission on Artificial Intelligence. Final report. (2021-03-01)[2024-07-17]. https://assets.foleon.com/eu-central-1/de-uploads-7e3kk3/48187/nscai_full_report_digital.04d6b124173c.pdf.

13. Select Committee on Artificial Intelligence. National artifical intelligence research and development strategic plan 2023 update. (2023-05-23)[2024-07-17]. https://www.nitrd.gov/pubs/National-Artificial-Intelligence-Research-and-Development-Strategic-Plan-2023-Update.pdf.

14. 赵志君, 庄馨予. 中国人工智能高质量发展：现状、问题与方略. 改革, 2023, (9): 11-20. Zhao Z J, Zhuang X Y. High-quality development of artificial intelligence in China: Status, problems and strategies. Reform, 2023, (9): 11-20. (in Chinese)

15. 何积丰. 重视人工智能发展中的安全与治理. 信息安全与通信保密, 2019, (6): 5-8. He J F. Attaching importance to security and governance in the development of artificial intelligence. Information Security and Communications Privacy, 2019, (6): 5-8. (in Chinese)

16. 皮勇, 张明诚. 总体国家安全观视域下人工智能安全风险治理研究. 中国科技论坛, 2023, (6): 86-96. Pi Y, Zhang M C. Research on artificial intelligence security risk management from the perspective of overall national security. Forum on Science and Technology in China, 2023, (6): 86-96. (in Chinese)

17. 陈旭, 江瑶, 熊焰, 等. 关键核心技术“卡脖子”问题的识别及应用：以AI芯片为例. 中国科技论坛, 2023, (9): 17-27. Chen X, Jiang Y, Xiong Yet al. Identification and application of key core technology “stuck neck” problem: Take AI chip as an example. Forum on Science and Technology in China, 2023, (9): 17-27. (in Chinese)

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