Going green with artificial intelligence: The path of technological change towards the renewable energy transition

• Authors: Hua-Tang Yin , Jun Wen , Chun-Ping Chang

Abstracts

EN

Research background: The twin pressures of economic downturn and climate change faced by countries around the world have become more pronounced over the past decade. A renewable energy transition is believed to play a central role in mitigating the economic-climate paradox. While the architectural and computational power of artificial intelligence is particularly well suited to address the challenges of massive data processing and demand forecasting during a renewable energy transition, there is very scant empirical assessment that takes a social science perspective and explores the effects of AI development on the energy transition. Purpose of the article: This paper aims to answer two key questions: One is, how does AI software development promote or inhibit the shift of energy consumption towards renewables? The other is, under what policy interventions does AI software development have a more positive effect on promoting renewable energy consumption? Methods: We employ a dataset of 62 economies covering the period 2011–2020 to analyze the impact of AI software development on the energy transition, where possible confounders, including political and economic characteristics and time-invariant elements, are controlled using fixed-effects estimation along with specified covariates. Findings & value added: AI software development can promote the energy transition towards renewables. There is suggestive evidence that the core mechanism linking such a positive relationship tends to lie in improving innovation performance in environmental monitoring rather than in green computing. Government support for R&D in renewable energy technologies is found to be significantly beneficial for harnessing the positive impact of AI software development on the energy transition. Compared to non-market-based environmental policies, market-based environmental policies have a more significant positive moderating effect on the relationship between AI software development and energy transition.

Keywords

EN

AI software development; energy transition; innovation; environmental monitoring; environmental policy

• Publisher: Instytut Badań Gospodarczych
• Journal: Oeconomia Copernicana
• Year: 2023
• Volume: 14
• Issue: 4
• Pages: 1059-1095

Dates

published

2023

Contributors

author

Hua-Tang Yin

• Xi'an Jiaotong Univeristy

• https://orcid.org/0000000228349867

author

Jun Wen

• Xi'an Jiaotong Univeristy

• https://orcid.org/0000000275441076

author

Chun-Ping Chang

• Shih Chien University

• https://orcid.org/0000000317824551

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Identifiers

DOI

10.24136/oc.2023.032

Biblioteka Nauki

39829199