生成式人工智能、就业变动与收入不平等

Generative Artificial Intelligence,the Change of Employment and Income Inequality

基于生成式人工智能迅速发展、就业和收入分配问题愈发凸显的现实背景,文章建立了一个包含异质性主体的职业选择模型,通过分析生成式人工智能如何影响不同居民的就业选择和收入,探究生成式人工智能对居民收入不平等的影响及机制。研究发现:生成式人工智能对收入不平等具有双刃剑效应。一方面,尽管生成式人工智能提高个体居民的人力资本,但会降低就业市场对劳动力的需求,导致失业率上升,经济陷入“内卷”。同时,生成式人工智能可能使一部分企业家被排斥出信贷市场,降低居民收入水平,最终加剧收入不平等。另一方面,生成式人工智能通过促进技术创新增加企业的预期经营利润,激励更多居民创业以及更多企业家进入信贷市场并扩大生产,由此增加企业人力资本需求,降低失业率,增加居民收入水平,最终缓解收入不平等。总体而言,生成式人工智能能否缓解收入不平等,取决于其人力资本渠道和技术创新渠道相互抵消后的净效应。异质性分析发现,在居民财富分布差距更大、企业生产的资本份额更低以及信贷市场的金融摩擦更大情况下,生成式人工智能更容易扩大收入不平等。政策分析发现,相较于普惠贷款类型的货币政策,针对企业减税的财政政策更有助于改善生成式人工智能对收入不平等的影响,但两者协调配合能够发挥更好的收入分配效果。

Generative artificial intelligence(Generative AI),represented by ChatGPT,is gaining prominence in fields such as autonomous driving,speech recognition,and image recognition,and is increasingly scrutinized for its impact on employment and income distribution.This paper constructs a vocational selection model to analyze how Generative AI influences the employment and incomes of diverse residents,thereby affecting income inequality.In our model,generative artificial intelligence reveals a dual effect on income inequality.On one hand,while it enhances the human capital of individual residents,it also reduces labor demand in the job market,leading to higher unemployment rates.Furthermore,generative AI excludes certain entrepreneurs from accessing credit markets,thereby reducing residents'income and exacerbating income inequality.On the other hand,generative AI increases enterprise profits through technological innovation,encouraging more entrepreneurs to enter the credit market and expand production.This stimulates demand for human capital,raises wages,reduces unemployment,and ultimately mitigates income inequality.Overall,the extent to which generative AI alleviates income inequality hinges on the combined impact of its human capital and technological innovation channels.Heterogeneity analysis shows that generative AI is more likely to exacerbate income inequality in conditions where wealth distribution is more unequal,capital's share in production is lower,and there are larger financial frictions in the credit market.Additional policy analysis indicates that fiscal policies aimed at lowering taxes for businesses are more effective in mitigating the impact of generative artificial intelligence on income inequality compared to inclusive lendingoriented monetary policies.Nonetheless,a coordinated approach combining both strategies can achieve more substantial improvements.The conclusions point to several policy implications:(1)Promote the development of artificial intelligence,with a focus on generative AI,to accelerate the modernization of traditional sectors.(2)Enhance the employment security system and implement various measures to stabilize the job market.(3)Foster innovation in high-tech industries and encourage entrepreneurship.This paper contributes to the existing literature in three key ways:(1)Unlike previous studies that focus primarily on the impact of artificial intelligence,this paper specifically examines the economic effects of the latest generative artificial intelligence.It develops a theoretical model that links generative AI to resident incomes,offering a new quantitative framework for analyzing the income impacts of generative AI.(2)While existing research typically explores AI's impact through physical capital,this paper shifts the focus to how generative AI influences income inequality through human capital and technological innovation mechanisms.(3)The paper also provides a discussion on optimizing the effects of generative AI on income inequality from the perspectives of monetary and fiscal policy.This offers theoretical insights for policymakers on managing the impact of emerging technologies like generative AI on the labor market.