AI不仅耗能，更通过系统性嵌入基础设施，引发气候、生物多样性和水资源等深层生态风险。
Expert Assessment: The Systemic Environmental Risks of Artficial Intelligence
- 构建三层次框架，分析AI如何通过社会经济系统放大环境危害
- 揭示AI在农业、能源和垃圾管理中的跨领域生态连锁反应
- 适合关注技术伦理与可持续发展的政策制定者和研究者
人工智能常被视为应对气候变化等社会挑战的关键工具，但其环境足迹正持续扩大。本报告聚焦人工智能的系统性环境风险，超越直接的能耗与用水影响。这些风险是新兴的、跨领域的生态与社会损害，涉及气候、生物多样性、淡水系统及更广泛的社会生态系统，主要源于AI深度融入社会、经济与物理基础设施，而非其直接资源消耗。此类风险通过反馈机制传播，导致非线性、不平等且可能不可逆的影响。尽管量化尚不确定，报告基于叙事文献综述，提出一个三层次框架，用于操作化系统性风险分析：识别塑造AI发展的结构性条件、传播环境损害的风险放大机制，以及可观察到的生态与社会后果。框架通过农业与生物多样性、石油天然气、废弃物管理三个领域的专家访谈案例进行阐释。
原文摘要 · Abstract (English)
Artificial intelligence (AI) is often presented as a key tool for addressing societal challenges, such as climate change. At the same time, AI's environmental footprint is expanding increasingly. This report describes the systemic environmental risks of artificial intelligence, in particular, moving beyond direct impacts such as energy and water usage. Systemic environmental risks of AI are emergent, cross-sector harms to climate, biodiversity, freshwater, and broader socioecological systems that arise primarily from AI's integration into social, economic, and physical infrastructures, rather than its direct resource use, and that propagate through feedbacks, yielding nonlinear, inequitable, and potentially irreversible impacts. While these risks are emergent and quantification is uncertain, this report aims to provide an overview of systemic environmental risks. Drawing on a narrative literature review, we propose a three-level framework that operationalizes systemic risk analysis. The framework identifies the structural conditions that shape AI development, the risk amplification mechanisms that propagate environmental harm, and the impacts that manifest as observable ecological and social consequences. We illustrate the framework in expert-interview-based case studies across agriculture and biodiversity, oil and gas, and waste management.
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