The Climate Impact Paradox of Artificial Intelligence: Literature Review and Research Prospects
人工知能の気候影響パラドックス：文献レビューと研究展望 (AI 翻訳)
Zhanming Chen, Qiyang Xiong, Zitong Hu, Shiyu Liu, Jianhong Ma
🤖 gxceed AI 要約
日本語
この文献レビューは、AIが気候変動に対して二重の影響（炭素集約的なエネルギー消費者かつ低炭素移行の促進者）を持つ「気候影響パラドックス」を明確化する。コンピューティングインフラの拡大がエネルギー消費と排出を増加させる一方、AIはエネルギー最適化やグリーン革新で貢献するが、リバウンド効果が脱炭素効果を打ち消す可能性がある。持続可能なガバナンス枠組みの必要性を提唱する。
English
This literature review clarifies the 'Climate Impact Paradox' of AI, which acts as both a carbon-intensive energy consumer and a low-carbon enabler. While AI computing infrastructure increases energy consumption and emissions through operational and embodied carbon, it also offers significant positive externalities in optimizing energy systems and driving green innovation. However, rebound effects often diminish decarbonization benefits, leading to a Jevons Paradox. The review advocates for a comprehensive governance framework including lifecycle carbon accounting and software-hardware synergetic innovation.
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
日本のGX文脈では、AIの電力消費増加が再生可能エネルギー調達やカーボンフットプリント管理の課題を浮き彫りにする。特にデータセンターのグリーン化や、AIを活用した省エネ・排出削減の両面で政策対応が求められる。
In the global GX context
In the global GX context, this paper highlights the tension between AI's growing energy demand and its potential for decarbonization. It informs debates on integrating AI into climate strategies, emphasizing the need for carbon accounting of AI systems and policies to mitigate rebound effects, relevant to TCFD/ISSB disclosures on technology-related emissions.
👥 読者別の含意
🔬研究者:Provides a systematic review of AI's dual climate impact, highlighting rebound effects and the need for lifecycle carbon accounting.
🏢実務担当者:Offers insights for companies deploying AI to consider both energy costs and carbon footprint, and to avoid efficiency rebound.
🏛政策担当者:Suggests that policies should address the full lifecycle emissions of AI and promote green computing infrastructure.
📄 Abstract（原文）
： In the context of global climate governance, Artificial Intelligence (AI) exerts a dual effect on climate change: acting as both a carbon-intensive energy consumer and an enabler of low-carbon transitions, which creates a complex “Climate Impact Paradox.” By conducting a systematic literature review, this paper aims to clarify the relationship between AI, energy consumption, and carbon emissions. The review reveals that the exponential expansion of computing infrastructure not only exacerbates the impact of operational energy consumption on regional power grids but also generates embodied carbon emissions through hardware manufacturing and electronic waste disposal. Although AI demonstrates significant positive externalities in optimizing energy systems, driving green technology innovation, and reshaping supply chains, the rebound effects triggered by efficiency improvements across material, economic, and socio-behavioral dimensions often diminish or even offset its decarbonization benefits, thereby inducing the “Jevons Paradox.” Consequently, this review argues that relying solely on exogenous technological progress is insufficient to mitigate the environmental risks of AI. Instead, it is imperative to construct a comprehensive governance framework that encompasses full life-cycle carbon footprint accounting, software-hardware synergetic innovation, and market-based incentive mechanisms. This pathway aims to achieve the deep integration of computing power and green electricity, positioning AI as a powerful engine for realizing sustainable development goals.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3724/j.issn.2097-4981.jecc-2025-0385first seen 2026-06-29 08:53:34
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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。