Tech Helps Planners Weigh Development, Historic Preservation
A University of Pennsylvania project aims to make it easier for city planners to gauge resident preference for preserving historic homes against municipal needs for higher-density housing.
May 28, 2021 •
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MetroLab Network has partnered with Government Technology
to bring its readers a segment called the MetroLab Innovation of the Month Series, which highlights impactful tech, data and innovation projects underway between cities and universities. If you’d like to learn more or contact the project leads, please contact MetroLab at info@metrolabnetwork.org for more information.
In this month’s installment of the Innovation of the Month series, we highlight OurPlan, a project that is gathering and organizing land use preferences from actual residents to help planners better weigh development and preservation options. MetroLab’s Ben Levine and Josh Schacht spoke with the leaders of
By
Ken Steif, Akira Drake Rodriguez, Sydney GoldsteinApril 29, 2021
Alterra s rendering shows a birds-eye view of the mixed-use development planned for land now occupied by city buildings. (Courtesy Alterra Property Group)
Recent controversies in Squirrel Hill, Society Hill, Point Breeze, and just about every other neighborhood in Philadelphia have prompted new debates around land use, equity, and fears of displacement.
The specter of gentrification looms large in the imagination of the average Philadelphian and studies suggest Black and Latinx renters are disproportionately impacted by the city’s rising property values. While the city has recently completed a robust comprehensive and district-level planning process, Philly2035, smaller-scale development, neighborhood change, and new land-use policies require ongoing, real-time capacity to engage communities around emerging development issues.
Metro21 Lunch and Learn: Public Policy Analytics: Code and Context for Data Science in Government
Postponed until a later date.
Join Metro21 as we hear Dr. Ken Steif discuss his project, Public Policy Analytics: Code & Context for Data Science in Government.
How do algorithms in government differ from business? In business, revenue is the only relevant bottom line, but in government algorithms must optimize for several disparate bottom lines like equity, fairness, bureaucracy, politics and more. In his new book, Public Policy Analytics: Code & Context for Data Science in Government , Dr. Ken Steif presents both code examples and an analytical framework for developing algorithms to meet these requirements. In this talk, he will discuss why data science and Planning are one in the same; how certain machine learning algorithms can help governments better allocate their limited resources; and how Algorithmic Governance can help agencies develop data science tools that are bot