[论文解读] The environmental impact of ICT in the era of data and artificial intelligence

François Rottenberg, Thomas Feys+1 more|arXiv (Cornell University)|Jan 7, 2026

Green IT and Sustainability被引用 0

一句话总结

该论文通过检视 ICT 相关排放，特别是数据中心，分析 AI 的净环境影响，并提出一个评估直接与间接效应及降低 AI Footprint 的良好实践框架。

ABSTRACT

The technology industry promotes artificial intelligence (AI) as a key enabler to solve a vast number of problems, including the environmental crisis. However, when looking at the emissions of datacenters from worldwide service providers, we observe a rapid increase aligned with the advent of AI. Some actors justify it by claiming that the increase of emissions for digital infrastructures is acceptable as it could help the decarbonization of other sectors, e.g., videoconference tools instead of taking the plane for a meeting abroad, or using AI to optimize and reduce energy consumption. With such conflicting claims and ambitions, it is unclear how the net environmental impact of AI could be quantified. The answer is prone to uncertainty for different reasons, among others: lack of transparency, interference with market expectations, lack of standardized methodology for quantifying direct and indirect impact, and the quick evolutions of models and their requirements. This report provides answers and clarifications to these different elements. Firstly, we consider the direct environmental impact of AI from a top-down approach, starting from general information and communication technologies (ICT) and then zooming in on data centers and the different phases of AI development and deployment. Secondly, a framework is introduced on how to assess both the direct and indirect impact of AI. Finally, we finish with good practices and what we can do to reduce AI impact.

研究动机与目标

• 从一般 ICT 出发放大到数据中心和 AI 部署阶段，评估 AI 的直接环境影响。
• 澄清透明度、市场干扰与方法论缺口导致量化 AI 净环境影响的不确定性。
• 引入一个框架，用以评估 AI 的直接与间接环境影响。
• 提供良好实践和可操作步骤，以降低 AI 相关的环境足迹。

提出的方法

• 从 ICT/AI 能源使用和排放的自上而下分析，覆盖 ICT 到数据中心再到 AI 生命周期。
• 为评估 AI 的直接与间接环境影响而开发框架。
• 讨论测量方法中的不确定性与标准化挑战。
• 提出降低 AI 环境足迹的良好实践与减排策略。

实验结果

研究问题

• RQ1 AI 在 ICT 与数据中心生态系统中的直接环境影响是什么？
• RQ2 如何在开发与部署生命周期中量化 AI 的直接与间接环境效应？
• RQ3 哪些不确定性与方法学差距阻碍了对 AI 净环境影响的清晰量化？
• RQ4 哪些做法可以降低 AI 与 ICT 的环境足迹？

主要发现

• 论文识别出数据中心排放随着 AI 出现而快速增长的趋势。
• 认为数字基础设施的去碳化收益存在不确定性且依赖情境。
• 提供一个框架来评估 AI 的直接与间接环境影响。
• 强调透明度缺失与非标准化方法等不确定性。
• 提出良好实践与实际行动以降低 AI 相关的环境影响。