In housing and mortgage markets, the increasing ubiquity of digitalization – emerging technologies that include AI, machine learning, and other types of informational automation – raises significant concerns about algorithmic bias, privacy, and the potential that centering data in public and private decision-making exacerbates power disparities. These are important concerns, but at the same time, innovations in digitalization hold promise for advancing civil rights in housing, supporting efforts to detect and remedy bias, as well as potentially offering creative new ways to direct federal, state, and local policies for housing justice.
Housing affordability was a chronic problem in many cities across North America and across the globe well before the global pandemic triggered an unprecedented surge in rents and prices. In this paper, we explore the multiscale challenges of housing affordability and the need for coordinated efforts to undertake planning for meeting broad social goals of improving housing affordability within the United States and Canada. The overall objective of the paper is to explore how housing affordability as a broad challenge is beginning to reshape the information and analysis tools used for policy, planning, project design, and evaluation at every scale from the site to the nation.
This invited commentary for the 2022 Harvard Joint Center for Housing Studies symposium focuses on the need for better data about zoning. It offers insights into the state of zoning data, then discusses the mechanics of creating a national zoning atlas based on the methods used to create the Connecticut Zoning Atlas. The commentary articulates reasons we should invest collective effort into a national atlas. Finally, it invites academics, nonprofits, and governmental bodies to collaborate on zoning data research. A National Zoning Atlas. Why not?