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.

翻译：科技行业将人工智能（AI）宣传为解决包括环境危机在内大量问题的关键赋能技术。然而，通过观察全球服务提供商数据中心的排放情况，我们发现其快速增长与AI的兴起同步。部分从业者为此辩护，声称数字基础设施排放的增长是可接受的，因为它可能帮助其他行业实现脱碳——例如使用视频会议工具替代乘坐飞机参加海外会议，或利用AI优化并降低能耗。面对这些相互矛盾的主张与愿景，如何量化AI的净环境影响尚不明确。该问题的答案因多种原因存在不确定性，主要包括：透明度不足、市场预期干扰、缺乏量化直接与间接影响的标准方法，以及模型及其需求的快速演进。本报告针对这些不同要素提供了解答与澄清。首先，我们采用自上而下的方法考察AI的直接环境影响，从广义的信息通信技术（ICT）出发，逐步聚焦于数据中心及AI开发与部署的不同阶段。其次，我们引入一个评估AI直接与间接影响的框架。最后，我们以降低AI影响的最佳实践与可行措施作为总结。