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<b>The Generative Anthropocene</b><b>: A Policy and Technology Roadmap for Mitigating the Escalating Energy and CO2 Burden of Advanced AI</b>

生成的人新世：高度AIの増大するエネルギー・CO2負荷を軽減するための政策と技術ロードマップ (AI 翻訳)

Daniel Morrell

Figshareプレプリント2026-07-13#政策対象セクター: cross_sector
DOI: 10.6084/m9.figshare.32975819
原典: https://doi.org/10.6084/m9.figshare.32975819

🤖 gxceed AI 要約

日本語

生成AIの推論段階における電力・CO2負荷が気候対策上の重大な課題となっている。本稿は量子計算や核融合などの技術的ブレークスルーと、炭素フリー電力への投資義務化や「Tonne-by-Tonne」枠組み等の政策により、AIのCO2負荷を市場で説明可能な問題へ転換する二段階ロードマップを提唱する。

English

This paper highlights the escalating energy and CO2 burden of generative AI's inference phase and proposes a two-track roadmap: technological discontinuities (quantum computing, nuclear fusion) and institutionalized responsibility (mandatory CFE investment, the 'Tonne-by-Tonne' beyond-offset framework). It reframes AI's climate impact as a market-accountable governance problem.

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

日本でもデータセンター立地と電力需要増がGX戦略の論点であり、本稿のCFE投資義務や原子力活用の議論は日本の電源構成政策と接続しうる。また、AI事業者のカーボンフリー電力調達が今後の投資家対応や開示で重要になる可能性を示唆する。

In the global GX context

At a global level, this paper contributes to the emerging debate on AI's climate disclosure and energy governance, complementing frameworks such as ISSB/CSRD by proposing concrete mandates for carbon-free energy procurement. It offers a policy template for integrating AI infrastructure into net-zero transition planning.

👥 読者別の含意

🔬研究者:Provides a framing for AI's energy/CO2 burden as a policy and technology research gap, and a basis for future empirical studies.

🏢実務担当者:Cloud and AI operators should monitor the proposed CFE investment mandates as a signal of future procurement and disclosure expectations.

🏛政策担当者:Presents actionable policy mechanisms (e.g., Tonne-by-Tonne, CFE mandates) that could be adapted into national AI and climate strategies.

📄 Abstract（原文）

The exponential proliferation of <b>Generative Artificial Intelligence (GAI)</b>, specifically its resource-intensive inference phase for applications such as high-fidelity video synthesis, constitutes a critical and largely unaddressed challenge to global climate mitigation efforts. This paper presents a granular analysis of the burgeoning CO2 burden and proposes a comprehensive, two-track mitigation roadmap: <b>Technological Discontinuity</b> and <b>Institutionalized Responsibility</b>. On the technological frontier, we detail the radical efficiency gains projected from <b>Quantum Computing (QC)</b> for algorithmic optimization and the potential for <b>Commercial Nuclear Fusion</b> to provide non-intermittent, carbon-free baseload power, thereby realizing the <b>Energy-as-Technology (EaT) paradigm</b>. On the policy front, we propose <b>Mandates for Dedicated Carbon-Free Energy (CFE) Investment</b> and <b>Evolving Technology Utilization</b> by hyper-scale AI operators. Crucially, we present the <b>‘Tonne-by-Tonne’ Mandate</b>—a novel policy framework institutionalizing a verifiable, <b>Beyond Offset (Three-Pillar) model</b> for all unavoidable emissions, holistically addressing climate breakdown, biodiversity loss, and poverty. This framework is buttressed by a diplomatic strategy leveraging the <b>Nationally Determined Contributions (NDCs)</b> network at the Conference of the Parties (COP). Finally, this approach is activated by the <b>Creative Community Action Mandate</b>, which utilizes the <b>Desktop Action Terminal</b> for real-time impact visibility, empowering creators to use their <b>purchasing power</b> to demand adherence to the mandated <b>Green Balance Standard</b> from AI companies. This shift transforms GAI’s CO2 burden into a structured, market-accountable problem.

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