The green potential of artificial intelligence: revisiting energy consumption, growth, and ecological footprint in the United States
人工知能のグリーン可能性：米国におけるエネルギー消費、成長、エコロジカルフットプリントの再検討 (AI 翻訳)
Mohammad Ridwan, Jeremy Ko, C. Leung, W. Ming
🤖 gxceed AI 要約
日本語
本研究は、1996年から2024年の米国データを用いて、AIイノベーション、エネルギー消費、経済成長、産業化、人口増加がエコロジカルフットプリントに与える影響を分析した。ARDLモデルによる分析の結果、AIイノベーションは環境負荷を軽減する一方、その他の要因は負荷を増加させることが示された。AIがエネルギー効率の最適化やクリーン生産を促進する可能性を実証し、AI主導のグリーン戦略の重要性を提言している。
English
This study examines how AI innovation, energy consumption, economic growth, industrialization, and population affect the US ecological footprint from 1996 to 2024 using ARDL and robustness tests. Results show AI innovation reduces ecological pressure by optimizing energy efficiency and promoting cleaner production, while other factors increase it. The findings highlight AI's potential as a key driver for environmental resilience and support AI-driven green strategies.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
米国データに基づくが、AIを活用した環境負荷低減の実証結果は、日本のGX戦略（GXリーグ、グリーンイノベーション基金等）におけるAI応用の推進にも示唆を与える。特に、AIによるエネルギーマネジメント最適化や排出削減効果の定量評価手法は、日本企業の脱炭素戦略立案に参考となる。
In the global GX context
This paper contributes to the global debate on AI's role in achieving environmental sustainability, reinforcing the potential of AI-driven climate solutions. It provides empirical evidence that can inform international discussions on integrating AI into decarbonization strategies, such as those under the UNFCCC or sustainable development goals.
👥 読者別の含意
🔬研究者:GX researchers can derive empirical evidence on AI's environmental benefits and use similar methodologies for other regions or sectors.
🏢実務担当者:Corporate sustainability teams can apply the findings to justify AI investments for energy efficiency and emission reductions.
🏛政策担当者:Policymakers can use these results to support AI integration into national climate action plans and green innovation policies.
📄 Abstract（原文）
Despite AI’s rapid progress of AI as a tool for equitable growth, little is known about how it can help to slow environmental damage. From 1996 to 2024, this study examined how the US’s ecological footprint is impacted by innovations in AI, energy use, economic development, industrialization, and growing populations. After confirming the mixed order of integration, the study applies the Autoregressive Distributed Lag (ARDL) method to evaluate short-term and long-term trends. Robustness was tested using three techniques: Canonical Cointegration Regression, Dynamic Ordinary Least Squares, and Fully Modified Ordinary Least Squares. The results show that the ecological footprint is positively affected by economic growth, increased energy consumption, industrialization, and population growth, all of which underline the environmental impacts of economic and demographic advancement. In contrast, AI innovation reduces ecological pressure, demonstrating its potential to optimize energy efficiency, encourage cleaner production, and enhance overall environmental quality. These results are consistent across both the short- and long-term calculations and robustness tests. This study contributes to the growing debate on technology and sustainability by positioning artificial intelligence as the key driver of ecological resilience. Policy implications stress the urgency of accelerating AI-driven green strategies, investing in renewable energy, and fostering sustainable industrial practices to balance economic progress with environmental preservation in the United States.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3389/fenvs.2026.1717269first seen 2026-05-18 05:20:18 · last seen 2026-05-20 05:37:39
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。