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持续增长，导致全球AI数据中心不断扩张，其电力消耗也随之不可避免的增加。目前尚不清楚这种计算能耗将对周边环境产生何种影响。本研究聚焦AI超大规模数据中心的热量耗散问题。利用过去几十年遥感平台获取的地表温度测量数据，我们能够对全球AI数据中心周边区域的温度升高情况进行稳健评估。据我们估算，AI数据中心开始运营后，其周边地表温度平均升高2°C，并形成局部微气候区，我们将其定义为"数据热岛效应"。通过评估该效应对社区的影响，我们量化发现超过3.4亿人可能受到这种温度升高的影响。研究结果表明，数据热岛效应未来可能对社区及区域福祉产生显著影响，因此应将其纳入全球环境可持续性人工智能的讨论范畴。