新质生产力视域下的人工智能自动化：双重生产力叠加效应与新经济增长

张永林; 刘李俪; 胡小莉

doi:10.19979/j.cnki.issn10082689.2025070101

新质生产力视域下的人工智能自动化：双重生产力叠加效应与新经济增长

doi: 10.19979/j.cnki.issn10082689.2025070101

1.
北京师范大学统计学院，北京 100875
2.
中国教育科学研究院教育财政研究所，北京100036
3.
中国传媒大学经济与管理学院，北京 100024

基金项目: 国家社会科学基金重点项目“人工智能信息生产力模型系统构建研究”（编号：20AJY001）；教育部人文社会科学规划基金项目“人工智能生产力理论模型与经济应用研究”（编号：18YJA790110）。

详细信息

作者简介:
张永林（1959—），男，黑龙江哈尔滨人，北京师范大学统计学院教授

刘李俪（1995—），女，北京人，中国教育科学研究院教育财政研究所助理研究员

胡小莉（1993—），女，北京人，中国传媒大学经济与管理学院副教授

中图分类号: F299.27
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- 被引次数: 0
出版历程
- 收稿日期: 2025-07-27
- 刊出日期: 2026-06-01

Artificial Intelligence Automation from the Perspective of New Quality Productive Forces: The Superposition Effect of Dual Productivity and New Economic Growth

1.
School of Statistics, Beijing Normal University, Beijing 100875, China
2.
Institute of Education Finance, China National Academy of Educational Sciences, Beijing 100036, China
3.
School of Economics and Management, Communication University of China, Beijing 100024, China

摘要

摘要: 文章解释了新质生产力视域下的人工智能自动化概念的内涵、特征和意义。人工智能自动化不同于机械自动化，是组织和行为的自主生成性。其本质特征是自我优化机制、自主组织机理和自动行为机能。人工智能自动化的这些特质和特性，使其产生直接和间接两方面的双重生产力。人工智能自动化的直接生产力与间接生产力复合叠加，产生技术创新增长率大于资本积累增长率效应、资本生产率增长×技术生产率增长叠加效应和经济增长奇点效应。文章通过对新质生产力视域下人工智能自动化的深入分析，目的在于解释人工智能与经济增长的关键问题，研究人工智能自动化是什么特征、特质和特性的生产模型，产生什么样的生产力，如何产生的，有什么意义，为中国人工智能创新与经济发展提供智力支持。
- 人工智能自动化 /
- 双重生产力 /
- 生产力叠加效应 /
- 新经济增长
Abstract: This paper explains the connotation, characteristics and significance of the concept of artificial intelligence automation from the perspective of new quality productive forces. Artificial intelligence automation is different from mechanical automation; it is the autonomous generation of organization and behavior. Its essential features are self-optimization mechanism, autonomous organization mechanism, and automatic behavior function. These traits and characteristics of artificial intelligence automation enable it to produce dual productivity in both direct and indirect aspects. The direct productivity and indirect productivity of artificial intelligence automation are compounded, generating effects such as a technology innovation growth rate exceeding the capital accumulation growth rate, the superimposed effect of capital productivity growth × technological productivity growth, and the economic growth singularity effect. Through an in-depth analysis of artificial intelligence automation from the perspective of new quality productive forces, this article aims to explain the key issues between artificial intelligence and economic growth, study the production model of artificial intelligence automation in terms of its characteristics, qualities, and traits, the type of productivity it generates, how it is generated, and its significance, providing intellectual support for China’s artificial intelligence innovation and economic development.
- artificial intelligence automation /
- dual productivity /
- productivity superposition effect /
- new economic growth
注释:

1) 1在以下行文中，资本K与要素X同义等价。小写亦然。前者为货币形态，后者为实物形态。

2) 2算法实现的信息处理过程

3) 3包括但不限于从传感器、图像、视频和不同类型的文档中获得的数据。

4) 4人工智能自动化过程的贴现因子不完全等同于时间贴现。

5) 5智能系统的扩张实现的生产水平比例大于100%。

6) 6到现在，研究智能经济、生产力和增长等，主流方法是构建全要素生产力模型，或者是拓展为所谓的要素替代常数广义模型。（Aghion et al., 2017; Jones & Liu, 2024）

HTML全文

图 1 人工智能自组织框架

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图 2 智能自动生成系统

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图 3 人工智能自我优化

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图 4 双重生产力叠加产生指数大于1的非线性增长

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参考文献(38)

[1]	SHI W, LI J, CHEN Z, et al. Smart mine: The role of artificial intelligence in modern coal extraction [C]// 2024 IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). Bangkok: IEEE, 2024: 874-879.
[2]	JAVAID M, HALEEM A, KHAN I H, et al. Understanding the potential applications of artificial intelligence in agriculture sector [J]. Advanced Agrochem, 2023, 2(1): 15-30. doi: 10.1016/j.aac.2022.10.001
[3]	AUTOR D H, LEVY F & MURNANE R J. The skill content of recent technological change an empirical investigation [J]. Quarterly Journal of Economics, 2003, 118(4): 1279-1333.
[4]	GOTTINGER H W. Artificial intelligence and economic modelling [J]. Expert Systems, 1991, 8(2): 99-105. doi: 10.1111/j.1468-0394.1991.tb00257.x
[5]	AGHION P, JONES B F & JONES C I. Artificial intelligence and economic growth [R/OL]. National Bureau of Economic Research (2017-09-17)[2025-07-16]. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=3053718.
[6]	EKBIA H R. Fifty years of research in artificial intelligence [J]. Annual Review of Information Science and Technology, 2010, 44(1): 201-242. doi: 10.1002/aris.2010.1440440112
[7]	ACEMOGLU D & RESTREPO P. Automation and new tasks: How technology displaces and reinstates labor [J]. Journal of Economic Perspectives, 2019, 33(2): 3-30.
[8]	PATEL K, BEERAM D, RAMAMURTHY P, et al. Ai-enhanced design: Revolutionizing methodologies and workflows [J]. International Journal of Artificial Intelligence Research and Development, 2024, 2(1): 135-157.
[9]	AGRAWAL A, MCHALE J & OETTL A. Finding needles in haystacks: Artificial intelligence and recombinant growth [C]//The Economics of Artificial Intelligence: An Agenda. Cambridge, MA: National Bureau of Economic Research, 2018: 149-174.
[10]	DECANIO S J. Robots and humans: Complements or substitutes? [J]. Journal of Macroeconomics, 2016, 49(1): 280-291.
[11]	陈琳, 高悦蓬, 余林徽. 人工智能如何改变企业对劳动力的需求?——来自招聘平台大数据的分析[J]. 社会科学文摘, 2024(9): 82-84.
[12]	HUI X, RESHEF O & ZHOU L. The short-term effects of generative artificial intelligence on employment: Evidence from an online labor market [J]. Organization Science, 2024, 35(6): 1977-1989.
[13]	SACHS J D & KOTLIKOFF L J. Smart machines and long-term misery [R/OL]. (2012-12-01)[2024-12-03]. https://www.nber.org/papers/w18629.
[14]	AGRAWAL A, GANS J & GOLDFARB A. The simple economics of machine intelligence [J]. Harvard Business Review, 2016, 17(1): 2-5.
[15]	DIMA J, GILBERT M H, DEXTRAS-GAUTHIER J, et al. The effects of artificial intelligence on human resource activities and the roles of the human resource triad: Opportunities and Challenges[J/OL]. (2024-06-03)[2024-12-03]. https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2024.1360401/full.
[16]	杨善林, 李霄剑, 张强, 等. 人工智能与管理变革[J]. 中国管理科学, 2023, 31(6): 1-11. doi: 10.3969/j.issn.1006-9860.2025.11.028
[17]	CREMER D D, BIANZINO N M & FALK B. How generative ai could disrupt creative work [J]. Harvard Business Review, 2023, 13: 1-12.
[18]	JONES B F & LIU X. A framework for economic growth with capital-embodied technical change [J]. American Economic Review, 2024, 114(5): 1448-1487. doi: 10.1257/aer.20221180
[19]	胡乐明, 杨虎涛. 产业发展战略选择的内在逻辑——一个连接演进的解析框架[J]. 经济研究, 2022, 57(6): 45-63.
[20]	CHANG Y T & FAN N H. A novel approach to market segmentation selection using artificial intelligence techniques [J]. The Journal of Supercomputing, 2023, 79(2): 1235-1262. doi: 10.1007/s11227-022-04666-2
[21]	CALVANO E, CALZOLARI G, DENICOLÒ V, et al. Artificial intelligence, algorithmic pricing, and collusion [J]. American Economic Review, 2020, 110(10): 3267-3297.
[22]	戴军, 窦一凡, 黄丽华, 等. 智能系统软件的定价模式: 数据驱动升级视角[J]. 管理科学学报, 2022, 25(9): 1-14. doi: 10.19920/j.cnki.jmsc.2022.09.001
[23]	HANSEN K T, MISRA K & PAI M M. Frontiers: Algorithmic collusion: Supra-competitive prices via independent algorithms [J]. Marketing Science, 2021, 40(1): 1-12.
[24]	JOHNSON J P, RHODES A & WILDENBEEST M. Platform design when sellers use pricing algorithms [J]. Econometrica, 2023, 91(5): 1841-1879. doi: 10.3982/ECTA19978
[25]	张永林. 智能创新生产力理论与中国经济发展深层思考[J]. 管理科学学报, 2017, 20(10): 116-126. doi: 10.3969/j.issn.1007-9807.2017.10.009
[26]	ABBASI A, PARSONS J, PANT G, et al. Pathways for design research on artificial intelligence [J]. Information Systems Research, 2024, 35(2): 441-459. doi: 10.1287/isre.2024.editorial.v35.n2
[27]	张永林. 互联网、信息元与屏幕化市场——现代网络经济理论模型和应用[J]. 经济研究, 2016, 51(9): 147-161.
[28]	BLUME L, EASLEY D, KLEINBERG J, et al. Introduction to computer science and economic theory [J]. Journal of Economic Theory, 2015, 156: 1-13. doi: 10.1016/j.jet.2014.11.002
[29]	江小涓, 宫建霞, 李秋甫. 数据、数据关系与数字时代的创新范式[J]. 社会科学文摘, 2024(12): 81-83.
[30]	GRAETZ G & MICHAELS G. Robots at work [J]. Review of Economics and Statistics, 2018, 100(5): 753-768. doi: 10.1162/rest_a_00754
[31]	JONES K S. The role of artificial intelligence in information retrieval [J]. Journal of the American Society for Information Science, 1991, 42(8): 558-565. doi: 10.1002/(SICI)1097-4571(199109)42:8<558::AID-ASI4>3.0.CO;2-4
[32]	LUDWIG J & MULLAINATHAN S. Machine learning as a tool for hypothesis generation [J]. The Quarterly Journal of Economics, 2024, 139(2): 751-827. doi: 10.1093/qje/qjad055
[33]	RESTREPO P. Automation: Theory, evidence, and outlook [J]. Annual Review of Economics, 2024, 16(1): 1-25.
[34]	RIBEIRO J, LIMA R, ECKHARDT T, et al. Robotic process automation and artificial intelligence in industry 4.0—a literature review [J]. Procedia Computer Science, 2021, 181: 51-58.
[35]	VERMA S, SHARMA R, DEB S, et al. Artificial intelligence in marketing: Systematic review and future research direction [J]. International Journal of Information Management Data Insights, 2021, 1(1): 100002.
[36]	NORDHAUS W D. Are we approaching an economic singularity? Information technology and the future of economic growth [J]. American Economic Journal: Macroeconomics, 2021, 13(1): 299-332. doi: 10.3386/w21547
[37]	ABRARDI L, CAMBINI C & RONDI L. The economics of artificial intelligence: A survey [R]. Florence: Robert Schuman Centre for Advanced Studies, 2019.
[38]	JUMPER J, EVANS R, PRITZEL A, et al. Highly accurate protein structure prediction with alphafold [J]. Nature, 2021, 596(7873): 583-589. doi: 10.1038/s41586-021-03819-2