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Artificial intelligence and environmental sustainability: a nonlinear analysis of the load capacity factor in OECD
Heng Luo1, LianPing Zhang2, Ying Sun3
1Jilin University of Chemical Technology, Jilin, China.
Abstract:
Amid the rapid expansion of artificial intelligence (AI) and growing concerns over ecological constraints, understanding the environmental consequences of emerging technologies has become increasingly important. This study investigates the nonlinear relationship between AI and environmental sustainability, which is proxied by the Load Capacity Factor (LCF), while considering the moderating effect of trade openness. Based on panel data from OECD countries between 1993 and 2023, the empirical results indicate a significant U-shaped relationship between AI and LCF. Specifically, AI initially reduces LCF but enhances environmental sustainability after exceeding a certain threshold. Moreover, trade openness is shown to flatten the U-shaped curve and shift its turning point. These findings provide meaningful policy insights for integrating digital transformation with sustainable development objectives.
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