TY - JOUR
T1 - Artificial intelligence and carbon emissions inequality
T2 - Evidence from industrial robot application
AU - Zhao, Congyu
AU - Li, Yongjian
AU - Liu, Zhengguang
AU - Ma, Xiaoyue
PY - 2024/1/20
Y1 - 2024/1/20
N2 - To figure out equitable and inclusive strategy to mitigate inequality of carbon emissions, we investigate the solution to narrowing carbon inequality from the perspective of developing artificial intelligence by using the generalized method of moments model and employing a panel dataset from 74 countries during 2000–2019. The asymmetric impact of artificial intelligence on carbon inequality is also checked. In addition, we examine the moderating and mediating effects in the nexus between artificial intelligence and carbon inequality. We find that (1) artificial intelligence has a negative causal relationship with carbon inequality, which indicates that developing artificial intelligence is essential for narrowing carbon inequality. (2) With the increase of the quantile of carbon inequality, artificial intelligence exerts a more remarkable inhibiting effect on carbon inequality, which implies that when the level of carbon inequality is more severe, the implementation of artificial intelligence proves to be a more potent tool for narrowing the disparity of emissions. (3) With the help of climate finance, artificial intelligence becomes even more effective in reducing carbon inequality, verifying the synergistic effect of climate finance and artificial intelligence on carbon inequality eradication. (4) Energy structure transition and industry structure transition are pathways through which artificial intelligence affects carbon inequality. Some concrete policy implications are drawn from the above main findings.
AB - To figure out equitable and inclusive strategy to mitigate inequality of carbon emissions, we investigate the solution to narrowing carbon inequality from the perspective of developing artificial intelligence by using the generalized method of moments model and employing a panel dataset from 74 countries during 2000–2019. The asymmetric impact of artificial intelligence on carbon inequality is also checked. In addition, we examine the moderating and mediating effects in the nexus between artificial intelligence and carbon inequality. We find that (1) artificial intelligence has a negative causal relationship with carbon inequality, which indicates that developing artificial intelligence is essential for narrowing carbon inequality. (2) With the increase of the quantile of carbon inequality, artificial intelligence exerts a more remarkable inhibiting effect on carbon inequality, which implies that when the level of carbon inequality is more severe, the implementation of artificial intelligence proves to be a more potent tool for narrowing the disparity of emissions. (3) With the help of climate finance, artificial intelligence becomes even more effective in reducing carbon inequality, verifying the synergistic effect of climate finance and artificial intelligence on carbon inequality eradication. (4) Energy structure transition and industry structure transition are pathways through which artificial intelligence affects carbon inequality. Some concrete policy implications are drawn from the above main findings.
U2 - 10.1016/j.jclepro.2024.140817
DO - 10.1016/j.jclepro.2024.140817
M3 - Article
SN - 0959-6526
VL - 438
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 140817
ER -