School of Management, China West Normal University, Nanchong City, 637001, Sichuan Province, China.
College of Economics and Management, China Jiliang University, Hangzhou City, 310018, Zhejiang Province, China.
J Environ Manage. 2024 Sep;367:122080. doi: 10.1016/j.jenvman.2024.122080. Epub 2024 Aug 6.
The rapid advancement of artificial intelligence (AI) in the 21st century is driving profound societal changes and playing a crucial role in optimizing energy systems to achieve carbon neutrality. Most G20 nations have developed national AI strategies and are advancing AI applications in energy, manufacturing, and agriculture sectors to meet this goal. However, disparities exist among these nations, creating an "AI divide" that needs to be addressed for regulatory consistency and fair distribution of AI benefits. Here, we look at the linear effects of AI and the Paris Agreement (AI), as well as their potential interaction on carbon neutrality. We also investigate whether geopolitical risk (GPR) can hinder or enhance efforts to attain carbon neutrality through energy transition (ET). To measure carbon neutrality of G20 countries, we employed a robust parametric Malmquist index combined with the fixed-effect panel stochastic frontier model to account for heterogeneity. Results indicate that from 1990 to 2022, carbon neutrality has improved primarily due to technological advancements. Developed G20 countries led in technological progress, while developing countries showed modest gains in carbon efficiency. Using the Driscoll-Kraay robust standard error method, we found that AI has a positive but insignificant linear effect on carbon neutrality. However, the interaction between PA and AI was positive and statistically significant, suggesting that PA augments AI's potential in accelerating carbon neutrality. Energy transition accelerates carbon neutrality in both developed and developing G20 countries. However, the role of energy transition in achieving carbon neutrality becomes negative when the interaction term between energy transition and geopolitical risk (ET × GRP) is incorporated. Regarding control variables, green innovation positively impacts carbon neutrality, whereas financial development has an insignificant effect. Industrial structure and foreign direct investment both negatively affect carbon neutrality, thereby supporting the pollution haven hypothesis. It is recommended that strategies to bridge the "AI divide" and uphold geopolitical stability are crucial to achieve carbon neutrality.
21 世纪，人工智能（AI）的飞速发展正在推动社会的深刻变革，在优化能源系统以实现碳中和方面发挥着关键作用。大多数二十国集团（G20）国家都制定了国家 AI 战略，并在能源、制造和农业领域推进 AI 应用，以实现这一目标。然而，这些国家之间存在差异，形成了需要解决的“AI 鸿沟”，以实现监管一致性和公平分配 AI 利益。在这里，我们研究了 AI 和《巴黎协定》（AI）的线性效应，以及它们对碳中和的潜在相互作用。我们还探讨了地缘政治风险（GPR）是否会阻碍或增强通过能源转型（ET）实现碳中和的努力。为了衡量 G20 国家的碳中和水平，我们采用了稳健的参数 Malmquist 指数，并结合固定效应面板随机前沿模型来考虑异质性。结果表明，从 1990 年到 2022 年，碳中和水平主要得益于技术进步。发达的 G20 国家在技术进步方面处于领先地位，而发展中国家在碳效率方面取得了适度的提高。通过 Driscoll-Kraay 稳健标准误差方法，我们发现 AI 对碳中和有正向但不显著的线性影响。然而，PA 和 AI 之间的交互作用是正向且具有统计学意义的，这表明 PA 增强了 AI 在加速碳中和方面的潜力。能源转型在发达和发展中 G20 国家都加速了碳中和。然而，当纳入能源转型和地缘政治风险（ET×GRP）之间的交互项时，能源转型在实现碳中和方面的作用变为负面。关于控制变量，绿色创新对碳中和有正向影响，而金融发展的影响不显著。产业结构和外国直接投资都对碳中和产生负面影响，从而支持污染避难所假说。建议采取策略来弥合“AI 鸿沟”并维护地缘政治稳定，这对于实现碳中和至关重要。
