强度(物理)
碳纤维
资本密集度
工业革命
人口
政府(语言学)
人工智能
产业组织
工程类
经济
人力资本
计算机科学
经济增长
政治学
人口学
法学
哲学
社会学
物理
复合数
量子力学
语言学
算法
作者
Jun Liu,Liang Liu,Yu Qian,Shunfeng Song
标识
DOI:10.1016/j.seps.2020.101002
摘要
Artificial Intelligence (AI) is becoming the engine of a new round of technological revolution and industrial transformation; as such, it has attracted much attention of scholars in recent years. Surprisingly, scarce studies have shed lights on the effects of AI on the environment, especially with respect to carbon intensity. Based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, we use Chinese industrial sector data from 2005 to 2016 to investigate how AI affects carbon intensity. The empirical results show that AI, as measured separately by the adoption of robotics by industry and the number of academic AI-related papers, significantly reduces carbon intensity. The results remain robust after addressing endogenous issues. We find that there are both stages and industrial heterogeneity in the effects of AI on carbon intensity. AI had a more decrease effect on carbon intensity during the 12th Five-Year Plan than the 11th. Compared with capital-intensive industries, AI tends to have a more decrease effect on carbon intensity in the labor-intensive and tech-intensive industries. To enlarge the effects of AI on reducing carbon intensity, the government should promote the development and application of AI and implement differentiated policies in line with the industry characteristics.
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