An impossible driver for energy justice? Exploring the impact of artificial intelligence on China's energy transition

Abstract

The contemporary energy transition is driven not only by the imperative to improve energy efficiency in response to environmental constraints but also by concerns over the unequal distribution of benefits and costs within the existing energy system. Departing from traditional efficiency-oriented perspectives, this paper examines the impact of artificial intelligence (AI) on just energy transition (JET) for the first time based on provincial-level industrial robot data in China from 2007 to 2017, using Bartik-style instrumental variable causal identification strategy. The empirical results indicate that AI has a negative impact on just energy transition. This conclusion remains valid after IV estimation, a placebo test, and a series of robustness tests. Mechanistic analyses suggest that AI can negatively affect the JET by widening the income gap, weakening the redistributive function of taxation, and increasing the consumption of non-renewable energy sources. By incorporating government governance and human capital into the analytical framework, we find that the impact of AI on the JET is moderated by the quality of government governance and human capital. That is, improvements in government governance and human capital can mitigate the negative impact of AI on the JET. The findings of this study have important theoretical and policy implications, contributing to a more comprehensive understanding of AI's impact on the energy transition and informing more effective strategies to manage and adapt to its creative destruction effects.