Computational Redistricting: Drawing the Maps
The 2020 decennial census count will begin on April 1, with results announced by the end of the year. A critical outcome of the count is the number of congressional seats allocated to each state. Once announced, state legislatures set in motion a process to create district maps for their states, with all the associated challenges. This process will impact every voter in the United States, since who represents them in Congress will be determined by this mapping process.
Founder Professor in Computer Science Sheldon H. Jacobson and Industrial and Enterprise Systems Engineering Teaching Assistant Professor Douglas M. King are ready to help meet this challenge. Jacobson and King have launched the Institute for Computational Redistricting (ICOR) to support state decision-makers and commissions responsible for creating district maps.
“Everyone is asking for a fair map. Our research suggests that fair maps do not exist, because there are numerous criteria that define fair maps, which are inherently conflicting.” Jacobson noted. “Our goal is to create a transparent environment where maps can be evaluated and compared.”
PhD students Ian Ludden (CS), Rahul Swamy (ISE), and Kiera Dobbs (ISE) are working to create such an environment. Ludden is exploring how game theory can be used to create and evaluate map designs across multiple criteria. Swamy is using optimization-based AI within a multi-criteria framework to create maps along a Pareto front. Dobbs is using stochastic models to evaluate how state courts are assessing partisan maps.
The team has already received national attention, including articles in Motherboard, Pacific Standard, and Innovators Magazine. More recently, they have worked with the Texas Civil Rights Project to support their efforts in combating gerrymandering in the State of Texas. Jacobson has also been involved with the Big Ten for the Strategic Partnership for Applied Redistricting Knowledge (SPARK) conference, supporting their efforts to reduce gerrymandering across the Big Ten states. A recent paper, “Multi-objective Optimization for Political Redistricting: A Scalable Multilevel Approach” also won first place (amongst 51 papers) in the 2019 INFORMS Best Service Sciences Paper Award competition.
ICOR’s mission is to provide transparent approaches for redistricting grounded in computational methods, which serves the needs and values of the people. Their vision is for governments and legislative bodies to adopt transparent redistricting processes that empower all voters to express their choices for the elected officials who will represent them. As such, to have the greatest impact, ICOR offers its services, at no cost, to any state agency or commission seeking assistance with their redistricting process.
“When legislators pick their voters, rather than voters electing their legislature, we are a weaker nation.” Jacobson noted. “Creating a computational environment for transparent redistricting is a huge leap forward in combating gerrymandering and empowering voters within our democratic system.”