Artificial Intelligence at the crossroads: Productivity J-curve and carbon trade-offs in the global economy
岐路に立つ人工知能：世界経済における生産性Jカーブとカーボントレードオフ (AI 翻訳)
Soumyajit Bhunia, Sneha Dey, Priya Mondal
🤖 gxceed AI 要約
日本語
本研究は、AI導入が生産性と炭素排出に与える影響を、OECD諸国のパネルデータ（2013-2020年）を用いて分析。生産性Jカーブ仮説を支持し、初期段階では生産性成長が鈍く、組織的適応が重要であることを示す。また、民主主義システムは環境規制の実施に遅れが生じる可能性がある。
English
This study examines the impact of AI adoption on productivity and carbon emissions using panel data from OECD countries (2013-2020). It supports the productivity J-curve hypothesis, showing slow initial productivity growth and the need for organizational adaptation. It also finds that democratic systems may delay environmental regulation enforcement.
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政策において、AI導入と脱炭素の両立は重要な課題。本論文の知見は、日本の企業や政府がAI投資と炭素削減目標を統合する際のバランスを考える上で示唆に富む。
In the global GX context
This paper provides empirical evidence on the trade-off between AI-driven productivity gains and carbon emissions, relevant for global climate policy. It highlights the need for organizational adaptation and the political challenges in implementing environmental regulations in democratic systems.
👥 読者別の含意
🔬研究者:The productivity J-curve and SURE estimation method offer a novel approach to analyzing AI's environmental impact.
🏢実務担当者:Organizations should invest in complementary changes to realize AI productivity gains while managing carbon emissions.
🏛政策担当者:Democracies may need to design regulations that balance economic growth and environmental protection without undue delay.
📄 Abstract（原文）
Artificial intelligence functions as an engine for increasing the productivity and economic growth of a nation. At the same time, it creates economic inequalities. The rapid development of the AI sector has profoundly transformed global systems, fundamentally altered operational paradigms, and paved novel pathways for economic growth. This study is trying to examine the intricate relationship between AI and economic growth, particularly on both the productivity gains and economic inequalities associated with AI adoption. We frame this scenario through the lens of productivity J-curve analysis. Using a panel of selected OECD countries spanning a period of eight years (2013-2020), the present study seeks to shed some light to examine the association among technological, political, and environmental factors, particularly AI patents and robot installation and their effects on productivity, measured by Total Factor Productivity (TFP). Furthermore, this study also focuses on the complex relationship between political factors, specifically democracy and political stability, and their impact on environmental degradation, measured by carbon emissions. To assess this relationship, we apply a novel econometric technique, the Seemingly Unrelated Regression Equation (SURE) estimation approach. Findings from our empirical study support the productivity J-curve hypothesis, where AI adoption at the early phase exhibits slower productivity growth, and the organizational changes catch up over time. It highlights the necessity for sustained organizational adaptation, realizing the full productivity gain of emerging technologies. Democratic systems frequently face delays in enacting and enforcing stringent environmental regulations due to political negotiations. Governments may prioritize economic development, often postponing environmental regulations to boost economic growth.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.31235/osf.io/tmjxw_v1first seen 2026-06-23 05:26:47
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
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。