数据中心的碳和水足迹,以及这对人工智能意味着什么
Alex de Vries-Gao1,2,3
1Institute for Environmental Studies, VU, Amsterdam, the Netherlands.
Patterns (New York, N.Y.)
|January 26, 2026
概括
由于数据中心报告不足,很难量化人工智能 (AI) 系统对环境的影响. 需要新的政策来强制要求人工智能的透明度.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 估计人工智能 (AI) 系统的全球电力需求是可行的,但量化它们的碳和水足迹仍然是一个重大挑战.
- 数据中心运营商经常在环境报告中不区分人工智能和非人工智能工作负载,从而妨碍了准确的影响评估.
- 科技公司目前的环境披露经常不足以确定数据中心的整体性能.
研究的目的:
- 突出 AI 工作负载对环境的影响量化的挑战.
- 强调需要提高数据中心环境报告的透明度和额外指标.
- 为了强调由于数据中心环境影响的快速增长,科技行业越来越迫切需要透明度.
主要方法:
- 对估计人工智能电力需求的当前方法的分析.
- 审查数据中心运营商和科技公司现有的环境报告实践.
- 在当前披露指标中识别数据缺口和局限性.
主要成果:
- 人工智能系统的环境足迹难以准确量化,因为缺乏关于人工智能工作负载的具体报告.
- 基于一般数据中心指标的近似值不足以评估人工智能的真正环境影响.
- 人工智能预计的碳足迹:到2025年,人工智能将排放3260万-797万的二氧化碳.
- 预计到2025年,人工智能的水足迹将达到312.5-764.6亿升.
结论:
- 目前的环境披露实践不足以了解AI的影响.
- 强制披露特定指标的新政策对于透明度至关重要.
- 提高透明度至关重要,以应对数据中心和人工智能的快速增长的环境影响.
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