Artificial intelligence, household financial fragility and energy resources consumption: Impacts of digital disruption from a demand-based perspective

Abstract

Ensuring access to affordable energy for all is laid out among the 17 Sustainable Development Goals and it remains an important open question as to how the popularity and widespread application of artificial intelligence (AI) in the workforce impact household energy resources consumption. To systematically investigate the impacts of the application of artificial intelligence in the workforce on household energy consumption in China, empirical analysis is conducted using data from the China General Social Survey (CGSS) from May to September 2022. The findings are as follows: (1) AI significantly reduces household energy consumption. Controlling other factors constant, for a one-standard-deviation increase in the impact of AI, household energy consumption drops by an average of 10.751%. Robustness and endogeneity tests, including dealing with missing values, using different energy consumption and AI indicators, as well as applying instrumental variable method, placebo test and penalized regressions, confirm this conclusion. (2) Mechanism analysis shows that AI reduces energy consumption by lowering household income and increasing their financial fragility. (3) AI's impacts on different types of energy consumption are heterogeneous. Its negative effects are mainly observed in the significant reduction of electricity and gas consumption. Furthermore, it increases the probability of using solid fuels such as honeycomb coal, coal lumps, traditional biomass, etc., thereby increasing the reliance on low-grade energy resources and raising the risk of energy poverty. (4) AI has greater negative effects on those who do not have access to energy subsidies and households with poor energy security and stability, lower income and inadequate social security. Besides, its impacts on regions with higher levels of technological development are more prominent. (5) Feasible pathways to mitigate the adverse effects of AI are explored. It is found that improving labor protection can help alleviate its adverse consequences on energy consumption. This paper provides evidence on the impacts of technological disruption from a demand-based perspective. It highlights the need for better policies on energy, social security, income distribution and labor protection to weaken AI's effects on household energy consumption and prevent them from falling into energy poverty.