🤖 AI Summary
研究提出一个整合AI对排放、产出和气候损害影响的框架，分析AI加剧气候变化的问题，区分ICT类和工业革命类AI前景，发现减缓措施与AI发展相辅相成。
📝 Abstract
Artificial intelligence (AI) interacts with climate in various ways, while a unified analytical framework of this intricate interplay is lacking. To align AI investment with climate policy, we propose such a framework integrating AI's impact on emissions, output, and climate damages into the DICE model. We distinguish between ICT-like and Industrial Revolution (IR)-like AI prospects. Calibrated to the best available evidence, we find that AI development is net polluting. Under current low abatement, ICT-like AI adds 0.1 degree C to 2100 warming, while IR-like AI adds 0.8 degree C. The associated climate costs offset roughly one-fifth and one-quarter of AI's economic gains, respectively. Meeting the 2 degree C target saves the optimal ICT(IR)-like AI investment rate by 2100 from 3.3% (5.1%) under the low-abatement scenario to 3.7% (12.7%), indicating that mitigation is complementary to AI development. We further show that the investment trade-off between AI and abatement is driven primarily by AI's economic prospects, not by its emissions footprint.