Bulletin of Chinese Academy of Sciences (Chinese Version)
Keywords
generative artificial intelligence; future industry; paradigm shift; advancement strategies
Document Type
Deep Integration Development of Technological and Industrial Innovation
Abstract
Generative AI, as the core engine triggering a paradigm shift in future industrial innovation, is propelling the next generation of artificial intelligence toward a “new qualitative state” characterized by deep thinking and long-chain reasoning. This study, grounded in the emerging attributes of generative AI-driven future industrial innovation, examines the mutually constitutive relationship between generative AI and industrial innovation in the digit-intelligence era. Through three analytical dimensions, namely, AI-driven transformation of knowledge production paradigms, the reconstruction of technological agency spaces, and the unleashing of new qualitative factor values, it thoroughly deciphers the paradigm evolution driven by generative AI. Furthermore, it proposes advancement strategies from three critical perspectives: breakthroughs in core technologies, construction of tiered talent ecosystems, and trustworthy governance of generative AI technologies.
First page
820
Last Page
827
Language
Chinese
Publisher
Bulletin of Chinese Academy of Sciences
References
1 薛澜, 劳拉·赞诺蒂, 顾嘉伟, 等. 人工智能的全球治理:挑战与进路(笔谈). 探索与争鸣, 2025, (1): 108-121. Xue L, Zanotti L, Gu J W, et al. Global governance of artificial intelligence: Challenges and pathways. Exploration and Free Views, 2025, (1): 108-121. (in Chinese)
2 Engels J, Baek D D, Kantamneni S, et al. Scaling laws for scalable oversight. (2025-04-25)[2025-05-01]. https://arxiv.org/abs/2504.18530v2.
3 Freeman C, Soete L. The Economics of Industrial Innovation. Cambridge: MIT Press, 1997.
4 Mannuru N R, Shahriar S, Teel Z A, et al. Artificial intelligence in developing countries: The impact of generative artificial intelligence (AI) technologies for development. Information Development, 2023: 02666669231200628.
5 龙海波. 未来产业创新生态:框架、实践与动能. 人民论坛·学术前沿, 2024, (12): 29-39. Long H B. Innovation ecology of future industries: Framework, practice and driving force. Frontiers, 2024, (12): 29-39. (in Chinese)
6 陈凯华. 以需求和情景为牵引培育未来产业创新生态. 人民论坛·学术前沿, 2024, (12): 22-28. Chen K H. Cultivating the innovation ecology of the future industries driven by demands and scenarios. Frontiers, 2024, (12): 22-28. (in Chinese)
7 李佳钰, 黄甄铭, 梁正. 工业数据治理:核心议题、转型逻辑与研究框架. 科学学研究, 2023, 41(12): 2216-2225. Li J Y, Huang Z M, Liang Z. Industrial data governance: Core issues, transformation logic and research framework. Studies in Science of Science, 2023, 41(12): 2216-2225. (in Chinese)
8 Tortora L. Beyond discrimination: Generative AI applications and ethical challenges in forensic psychiatry. Frontiers in Psychiatry, 2024, 15: 1346059.
9 丁煌, 卫劭华. 生成式人工智能时代的政策科学研究. 电子政务, 2024, (11): 42-53. Ding H, Wei S H. Policy science research in the era of generative artificial intelligence. E-Government, 2024, (11): 42-53. (in Chinese)
10 Chiarello F, Giordano V, Spada I, et al. Future applications of generative large language models: A data-driven case study on ChatGPT. Technovation, 2024, 133: 103002.
11 姜李丹, 薛澜. 我国新一代人工智能治理的时代挑战与范式变革. 公共管理学报, 2022, 19(2): 1-11. Jiang L D, Xue L. The current challenges and paradigm transformation of new-generation AI governance in China. Journal of Public Management, 2022, 19(2): 1-11. (in Chinese)
12 隆云滔, 刘海波, 许哲平, 等. 关于构建我国人工智能开源创新生态体系的建议. 中国科学院院刊, 2025, 40(3): 453-458. Long Y T, Liu H B, Xu Z P, et al. Suggestions on building China’s artificial intelligence open source innovation ecosystem. Bulletin of Chinese Academy of Sciences, 2025, 40(3): 453-458. (in Chinese)
Recommended Citation
XUE, Lan and JIANG, Lidan
(2024)
"Generative AI-driven paradigm shift for future industrial innovation,"
Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 40
:
Iss.
5
, Article 7.
DOI: https://doi.org/10.3724/j.issn.1000-3045.20250505002
Available at:
https://bulletinofcas.researchcommons.org/journal/vol40/iss5/7