人工智能与全球价值链重构:理论机制与中国对策  

Artificial Intelligence and the Reconstruction of Global Value Chains:Theoretical Mechanisms and China’s Countermeasures

作　　者：何宇 陈珍珍 盛三化[1] HE Yu;CHEN Zhenzhen;SHENG Sanhua(School of Economics and Management,China Three Gorges University,Yichang 443002,China)

机构地区：[1]三峡大学经济与管理学院,湖北宜昌443002

出　　处：《西安财经大学学报》2024年第4期3-14,共12页Journal of Xi’an University of Finance and Economics

基　　金：国家自然科学基金青年项目“人工智能技术加剧全球价值链非平衡发展的形成机理与中国对策研究”(72303127)。

摘　　要：人工智能作为引领新一轮科技革命和产业变革的战略性技术,正在对社会生产方式和全球价值链分工格局产生广泛而深刻的影响,在此背景下,探索人工智能技术对全球价值链分工的影响机理,是值得深入研究的前沿科学问题.与已有文献将人工智能技术作为自动化技术或者具体计算机算法技术不同,本文基于对人工智能技术的经济学本质特征探索,提出“人工智能技术是数据要素驱动的自动化技术”,将数据要素纳入人工智能经济学模型.借鉴新结构经济学的要素禀赋结构理论,通过构建“要素禀赋结构技术利用结构要素利用结构”逻辑框架,进一步探索人工智能技术影响全球价值链重构的理论机制和中国对策.研究发现:(1)要素禀赋结构是决定一国的企业进行适宜性技术选择的重要因素,发达国家和发展中国家的要素禀赋结构存在异质性,这导致各国对于人工智能技术的适应性也存在差异,进而导致发展中国家和发达国家的全球价值链分工差距持续扩大;(2)数据要素具有高时效性和高折旧率特征,导致数据要素存量主要由当期数据要素流量决定,而当期数据要素流量又与数字化、智能化生产和应用的规模正相关,因此市场规模是决定数据要素存量的重要因素,这意味着通过发挥市场规模优势促进数据要素积累,优化面向数字化和智能化生产场景下的要素禀赋结构,是发展中国家抢抓人工智能技术发展机遇和实现人工智能技术“弯道超车”的重要路径;(3)政策上一方面应该着力推进优化传统要素禀赋结构政策加上对结构性失业的配套补救政策,另一方面应该利用中国超大规模市场优势促进中国数据资源向数据要素转化,以优化面向数字化和智能化时代的要素禀赋结构.As a strategic technology leading a new round of technological revolution and industrial transformation,AI is widely and deeply influencing the mode of social production and the global value chain division of labor.Against this backdrop,exploring the impact mechanism of AI technology on the global value chain division of labor is a cuttingedge scientific issue worthy of indepth research.Unlike existing literature that views AI technology as automation technology or specific computer algorithm technology,this article explores the economic essence of AI technology and proposes that“AI technology is datadriven automation technology”.By incorporating data factor into the AI economic model,it builds a logical framework of“factor endowment structuretechnology utilization structurefactor utilization structure”and further explores the theoretical mechanism of AI technology’s impact on global value chain restructuring and China’s response.The study found that:(1)Factor endowment structure is an important factor determining a country’s enterprises to make appropriate technological choices.There are differences in factor endowment structures between developed and developing countries,which leads to differences in the adaptability of AI technology in different countries,thus widening the gap between developing and developed countries in global value chain division of labor;(2)Data factor have high timesensitivity and high depreciation rates,resulting in data factor mainly determined by current data factor flows,which are positively correlated with the scale of digital,intelligent production and application.Therefore,market size is an important factor determining data factor stock,which means that developing countries should take advantage of market size advantages to promote data factor accumulation,optimize factor endowment structure for digital and intelligent production scenarios,and seize AI technology development opportunities and achieve“overtaking”in AI technology development;(3)Policies should focus

关 键 词：人工智能 全球价值链 要素禀赋 数据要素 数字经济 

分 类 号：F424[经济管理—产业经济] TP18[自动化与计算机技术—控制理论与控制工程]