From Carbon Accounting to Climate Justice
カーボン・アカウンティングから気候正義へ (AI 翻訳)
Rimi Gusliana Mais, Munir Munir
🤖 gxceed AI 要約
日本語
本研究は、AIをカーボンアカウンティングや排出モニタリング、気候金融に統合し、公共部門の説明責任と気候ガバナンスを強化するフレームワークを提案する。インドネシアの事例を通じて、リアルタイムデータと金融フローを連携させるAI駆動型の仕組みが効果的であることを示す。
English
This study proposes an AI-driven carbon accountability framework integrating real-time emissions data, financial flows, and governance mechanisms. Using Indonesia as a case, it demonstrates how AI enhances transparency and efficiency in climate finance allocation, though institutional coordination remains critical.
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
日本ではSSBJや有報での気候関連開示が進む中、AIを活用した炭素会計の枠組みは今後の実務に示唆を与えるが、本論文の事例はインドネシアに特化している。
In the global GX context
This paper contributes to global GX discourse by linking AI, carbon accounting, and climate finance—relevant to ISSB and TCFD frameworks—and highlights the need for data governance and ethical integration.
👥 読者別の含意
🔬研究者:The AI-driven carbon accountability framework offers a novel integration of technology and sustainability accounting for researchers in climate finance and disclosure.
🏢実務担当者:Public sector and corporate sustainability teams can explore AI tools for real-time emissions monitoring and climate finance tracking.
🏛政策担当者:Policymakers should note the importance of institutional coordination and data governance for effective AI deployment in climate governance.
📄 Abstract（原文）
This study explores the integration of artificial intelligence (AI) in carbon accounting, emissions monitoring, and climate finance to enhance public sector accountability and climate governance. Despite growing attention to digital solutions, existing systems remain fragmented, data-limited, and weakly connected to financial decision-making. This study addresses this gap by proposing an integrated AI-driven carbon accountability framework that links real-time emissions data, financial flows, governance mechanisms, and ethical considerations. Using a conceptual approach supported by an illustrative case study of Indonesia, the study demonstrates how AI enables dynamic monitoring, data-driven policy decisions, and improved transparency in climate finance allocation. The findings highlight that while AI enhances efficiency and responsiveness, its effectiveness depends on institutional coordination, data governance, and ethical integration. This study contributes by advancing sustainability accounting toward a more adaptive, performance-based, and justice-oriented model
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.4018/979-8-2600-2020-3.ch011first seen 2026-06-08 04:41:22
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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。