Alejandro Hernandez
Research Mentor: Tyler Simko
Mentor Department: Political Science, LSA
Author(s): Alejandro hernandez, PhD Tyler Simko
Session: Session 7 (4:00 PM – 4:50 PM)
Presentation Type: Poster 46
Abstract
Massive, resource-intensive data centers have become a critical component of the infrastructure supporting data-heavy machine learning systems, yet their expansion raises growing environmental, energy, and economic concerns for the communities in which they are proposed. As these projects often require local approval, city governments have emerged as key sites of public debate and community resistance. This project uses data extracted from city council meeting videos and geospatial data on proposed and existing data center locations to examine how data center development is discussed at the local level. We aim to construct a comprehensive dataset mapping existing and proposed data center locations across the state of Michigan, while developing a methodological framework that can be scaled for national analysis. The study applies natural language processing techniques, such as word embeddings, to analyze discourse within city council meetings and identifies political expressions of support and opposition related to proposed construction projects. This study provides the tools for analyzing the intersection of computational infrastructure, local governance, and community impact. Our dataset and planned visualizations seek to contribute to ongoing conversations about the societal costs of data-intensive technologies and the role of local governments in shaping their development.
