Can artificial intelligence achieve carbon neutrality? Evidence from a quasi-natural experiment

Abstract

Introduction: As the global climate crisis worsens, carbon neutrality has attracted the attention of various nations. Methods: Based on panel data from 282 Chinese prefecture-level cities from 2008 to 2019, this research considers the execution of the artificial intelligence strategy as a quasi-natural experiment. It uses the difference-in-differences (DID) model to evaluate the effect of artificial intelligence construction on carbon emission reduction. Results: The findings indicate that implementing the artificial intelligence strategy into practice can lower carbon emissions and advance carbon neutrality, and this conclusion still passes after various robustness tests. The mediating effects reveal that developing green technologies and upgrading the industrial structure are crucial mechanisms for achieving carbon neutrality. The implementation effect varies with time, geographical location, natural resource endowment, and city level. Discussion: This article examines the influence of artificial intelligence on urban carbon neutrality at the city level, adding to the notion of urban carbon neutrality and providing research support for urban development transformation.