SCC-PG: The Prospects for Artificial Intelligence in Urban Planning

点击翻译按钮获取中文摘要

The breadth of artificial intelligence (AI) applications has grown significantly, particularly over the last decade, increasing productivity and efficiency across numerous sectors. Cities have become the primary sites of data collection and algorithm deployment, but the professional field of urban planning lacks a comprehensive evaluation of how AI can/should be used to improve analytical processes. Urban planning anticipates and guides the future physical and social conditions of communities to improve quality of life – all with a heavy reliance on increasingly large and varied datasets, which suggests the untapped potential of AI if the field were to develop robust frameworks for ethical deployment. This project examines and seeks to address the tension between improving the efficiency of public service provision and enhancing redistributive and procedural equity within urban decision-making. As AI’s role in society grows, so do the concerns that it may reproduce racial bias, deepen “digital divides,” infringe on privacy, and do little to address the “wicked problems” at the heart of complex social issues. In addition, it may shed light on broader impacts of automation in urban life, such as workforce displacement, lifestyle changes, and future developments in public service professions.This project is a partnership between Virginia Tech, the American Planning Association (APA), and Arlington County, Virginia’s Departments of Community Planning, Housing and Development (DCPHD Planning Division) and Technology Services (DTS). As part of this planning grant, the partnership will survey members of the APA and conduct feasibility analysis workshops and focus group sessions with DCPHD. The objective is to assess a broad range of tasks performed by County planners and determine which of these have the highest likelihood of being assisted and improved by AI technologies. This includes county-level responsibilities for comprehensive planning, land use, infrastructure, environment, housing, parks, and transportation. This project expects that each of these areas has the potential for more advanced data and analytical capabilities. The approach partners researchers, planning professionals, and community members will focus on the explainability and transparency of AI-based planning activities. This relates to the equitable deployment of AI methods and will also address concerns about trust in the use of data and analytical processes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.