Human-Centered Automation in Sustainable Finance
持続可能な金融における人間中心の自動化 (AI 翻訳)
Vandana Gaur, Neeta Gupta, Sujata Gupta
🤖 gxceed AI 要約
日本語
本論文は、持続可能な金融における人間中心の自動化のパラダイムシフトを提唱する。AIと自動化システムを導入する際、人間の価値観や幸福を中心に据え、効率性や利益最大化は副次的なものとする。ESGデータ処理、グリーンウォッシング検出、規制順守チェックなどのデータ集約的タスクにAIを活用し、人間が説明可能なインターフェースと協調的意思決定ツールを通じて結果を検証する手法を提案する。
English
This paper advocates for a paradigm shift in sustainable finance towards human-centered automation, where AI and automated systems are implemented with human values, needs, and well-being at the core, rather than pure efficiency and profit maximization. It focuses on augmentation: AI processes data-intensive tasks like ESG data crunching, greenwashing detection, and compliance checks, while humans remain in control via explainable interfaces and collaborative decision-making tools.
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
日本でもサステナブルファイナンスの枠組みが拡大しており、ESGデータの信頼性やグリーンウォッシング防止が課題となっている。本論文の人間中心の自動化アプローチは、日本の金融機関がAIを導入する際の倫理的枠組みとして参考になる可能性がある。
In the global GX context
As global sustainable finance regulations like SFDR and upcoming ISSB standards demand robust ESG data handling, this paper offers a human-centered automation framework that addresses greenwashing and compliance. It is relevant for practitioners designing AI systems that enhance, rather than replace, human judgment in sustainability reporting.
👥 読者別の含意
🔬研究者:A conceptual framework for studying AI augmentation in sustainable finance, highlighting the need for explainability and human oversight.
🏢実務担当者:Guidance for implementing AI tools in ESG data processing and greenwashing detection while maintaining human control.
🏛政策担当者:Insights into designing regulations that encourage human-centered automation in sustainable finance for ethical compliance.
📄 Abstract（原文）
The notion of human-centered automation of sustainable finance is a paradigm shift in which artificial intelligence and automated systems are instituted, implemented and regulated with people at the heart of the systemic nature-people-values-needs-agency-and-well-being and the pure efficiency and maximization of profits are considered peripheral to all other human considerations. In contrast to conventional automation where it frequently replaces human labour directly, this strategy focuses on augmentation: AI can be used to process data-intensive jobs such as crunching large volumes of ESG (Environmental, Social, and Governance) data, detecting greenwashing in corporate reports and green investment portfolios, and automate compliance checks of regulations such as the Sustainable Finance Disclosure Regulation or other forthcoming global standards. This model ensures that ethical considerations are used to derive the results by keeping humans in the loop by providing explainable interfaces, collaborative decision-making tools and oversight mechanisms
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.4018/979-8-2600-1308-3.ch005first seen 2026-05-14 23:18:22
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