New Jersey needed a way to anticipate homelessness increases before they happened, especially as federal policy and economic conditions became volatile – and a tool that decisionmakers could use, without a data team in the room, to create dynamic, defensible data models and solutions. Our solution: the Homelessness Economic Risk Framework (HERF). Built in-house at the NJ Department of Community Affairs, HERF models risk at the zip-code level, combines dynamic economic risk and fixed structural factors, uses a conversational GPT interface so users can ask questions and run scenarios in plain language, and utilizes publicly available data sources and DCA-specific data. This session will cover how DCA created the HERF and the types of forecasts, economic models and interventions that can be created with generative AI. The session will provide participants with a road map to use data more strategically to engage and persuade stakeholders, no matter what your experience with data and with AI.
Presenters:
Janel Winter
Assistant Commissioner & Director, Housing & Community Resources, NJ Department of Community Affairs
Gavin Rozzi
Director, DHCR Data Center, NJ Department of Community Affairs