Water On My Block: Reflections on Building A Participatory Artificial Intelligence System For Precision Weather With Scientists and An Urban Community

Creating accurate hyper-local climate Artificial Intelligence (AI) models requires neighborhood-level weather measurements and community partnerships. In this paper, we describe a three year case study of using a participatory approach to support the creation of hyper-local climate AI models, or what we term “precision weather.” Using participatory design to involve stakeholders in the climate AI pipeline design process i.e., “participatory AI,” we collaborated with a national laboratory and a community organization in a major metropolitan area in the United States, working with community members and scientists. We held interviews, co-design workshops (“Community Cafes”), and created an app for the community to collect flood reports in their neighborhood for advocacy and to contribute data to the AI model pipeline. We discuss our findings, lessons learned, and implications for future participatory projects to support hyper-local climate AI.