The strong and continuous increase of AI-based services leads to the steady proliferation of AI data centres worldwide with the unavoidable escalation of their power consumption. It is unknown how this energy demand for computational purposes will impact the surrounding environment. Here, we focus our attention on the heat dissipation of AI hyperscalers. Taking advantage of land surface temperature measurements acquired by remote sensing platforms over the last decades, we are able to obtain a robust assessment of the temperature increase recorded in the areas surrounding AI data centres globally. We estimate that the land surface temperature increases by 2°C on average after the start of operations of an AI data centre, inducing local microclimate zones, which we call the data heat island effect. We assess the impact on the communities, quantifying that more than 340 million people could be affected by this temperature increase. Our results show that the data heat island effect could have a remarkable influence on communities and regional welfare in the future, hence becoming part of the conversation around environmentally sustainable AI worldwide.

翻译：基于人工智能服务的强劲且持续增长，导致全球范围内人工智能数据中心不断涌现，其电力消耗也随之不可避免地攀升。目前尚不清楚用于计算目的的能源需求将如何影响周边环境。本文将关注点集中于人工智能超级数据中心的热量散逸问题。利用过去几十年间遥感平台获取的地表温度测量数据，我们得以对全球人工智能数据中心周边区域记录到的温度上升进行稳健评估。我们估算，在人工智能数据中心开始运营后，其周边地表温度平均上升2°C，从而形成局地微气候区，我们将此现象称为“数据热岛效应”。我们评估了这对社区的影响，量化结果表明，超过3.4亿人可能受到此温度上升的影响。我们的研究结果显示，数据热岛效应可能会对未来社区及区域福祉产生显著影响，因而应成为全球关于环境可持续性人工智能讨论的一部分。