Exploring the Intersection of Data Center Expansion and Generative Artificial Intelligence via an Equity Impact Assessment

<p style="font-weight: 400;">This work provides an in-depth analysis of the impacts of data center expansion with the understanding that the need for large data centers is growing due to the introduction of generative AI. The author adapted the structure of an Equity Impact Assessment to complete the work. The author completed this analysis using material from PubMed, SCOPUS, Nexus Uni, and advanced Google searches with a domain limited to &ldquo;gov&rdquo;.&nbsp;&nbsp; These searches yielded perspectives from governmental agencies, community members surrounding the data centers, and academic leaders. The findings of this work include environmental justice concerns, unequal hiring practices, strain on energy grids, and an increase in cost to local communities. These concerns are likely to compound with existing environmental injustices like the impacts of concentrated animal farm operations and solid waste landfills, both of which disproportionately negatively impact communities of color, rural communities, and people with low socio-economic status. This work can inform future public health endeavors in practice and research. Key recommendations include examining the hiring practices and the environmental impacts associated with large data centers. It is essential to involve community members in the research process, given the current lack of information from their perspectives. Additionally, decisions about land use and energy alternatives must incorporate input from community members and environmental justice leaders, who are often excluded. The evaluation of existing programs, such as incentives and community college training programs also offer opportunities to prepare communities for introduction of large data centers. <em style="font-weight: 400;">Keywords</em><span style="font-weight: 400;">: data center(s), generative artificial intelligence, environmental impact(s), equity impact assessment</span>