A lack of affordable housing is a major problem in US cities from the Bay Area to Boston. Austin is no exception. In 2015, the Austin-Round Rock metropolitan area was named one of the most economically segregated areas in the country. With more people moving to the region – roughly 3,000 people per month – the disparity will worsen. This research project will develop a values-driven AI system that evaluates historical housing development and helps policymakers shape equitable, inclusive and sustainable plans and regulations. Using deep learning technology and an open data repository with demographic, development, transportation, and energy consumption data, this system will link and study 50 years of Austin housing development figures in an effort to help tackle the future of local housing. More specifically, the project will look at the spatial and demographic relationships between housing, affordability, mobility and energy use over the past 50 years and how likely those patterns are to persist depending on what regulations are put in place. The goal is to build a predictive AI system that will test different regulatory scenarios and inform residential development policies in Austin. The techniques and findings developed from this study can also be applied to many similar cities nationally and internationally. Additionally, the data repository created here will be used to study how environmental and socioeconomic factors have affected the spread of COVID-19 in the city of Austin.
Junfeng Jiao (Principal Investigator, Architecture), Weijia Xu (Texas Advanced Computing Center), Jake Wegmann (Architecture), Katie Pierce Meyer (University of Texas Libraries), Hao Zhu (Electrical and Computer Engineering), Chen Feng (Architecture), Josh Conrad (Architecture), Cara Bertron (City of Austin Planning and Zoning Department), Matt Dugan (City of Austin Planning and Zoning Department), John Clary (City of Austin Transportation Department), Molly Emerick (Austin Energy), Matt Hollon (City of Austin Watershed Protection Department) and Jacquie Hrncir (City of Austin Communications & Technology Management Department)