AI Meets Natural Hazard Risk: A Nationwide Vulnerability Assessment of Data Centers to Natural Hazards and Power Outages
Miguel Esparza, Bo Li, Junwei Ma, Ali Mostafavi

TL;DR
This study assesses the nationwide vulnerability of US data centers to natural hazards and power outages, identifying areas at risk and pinpointing low-vulnerability regions using spatial analysis methods.
Contribution
It introduces a comprehensive spatial analysis of data center vulnerabilities to natural hazards and power outages across the US, highlighting high-risk areas and low-risk counties.
Findings
Many data centers are in non-vulnerable areas.
Earthquakes, hurricanes, and tornadoes pose significant risks.
Three counties identified with minimal vulnerabilities.
Abstract
Our society is on the verge of a revolution powered by Artificial Intelligence (AI) technologies. With increasing advancements in AI, there is a growing expansion in data centers (DCs) serving as critical infrastructure for this new wave of technologies. This technological wave is also on a collision course with exacerbating climate hazards which raises the need for evaluating the vulnerability of DCs to various hazards. Hence, the objective of this research is to conduct a nationwide vulnerability assessment of (DCs) in the United States of America (USA). DCs provide such support; however, if an unplanned disruption (like a natural hazard or power outage) occurs, the functionality of DCs are in jeopardy. Unplanned downtime in DCs cause severe economic and social repercussions. With the Local Indicator of Spatial Association (LISA) test, the research found that there are a large…
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Taxonomy
TopicsInfrastructure Resilience and Vulnerability Analysis
