ReDDDoT Phase 1: Planning Grant - Bridging Past and Future: Fostering Community-Researcher Synergy through Planning
INSTITUTION
Regents of the University of Michigan - Ann Arbor, MI
PRINCIPAL INVESTIGATOR
Tawanna R Dillahunt
FUNDING
$300K
YEAR
2024
MOONBASE SCORE
Still being scored
LOADING MOONBASE SCORE
Abstract
The project seeks to design, develop, and deploy Artificial Intelligence (AI) responsibly. Rapid technological growth has often overlooked the importance of community input. To address this, this project uses an approach that recognizes community members as experts with valuable insights. The project uses human-computer interaction to change how communities are involved in developing AI. The project will explore these changes and develop new ways to include community voices in AI design. This project will foster AI application and methodological advancements through established community-based partnerships. Focus areas include public health, education, and work. Investigating how AI impacts these areas will help solve important social problems. It will also improve research on responsible technology development. Using methodologies such as Community-Based Participatory Research and participatory design, this research focuses on residents of the east side of Detroit to investigate community members’ priorities for Artificial Intelligence (AI) technologies. This project also employs educational sessions, reflective surveys, and the innovative Choosing All Together (CHAT) deliberative tool to co-create planning processes with academic researchers and community members that account for technological advances and societal impacts. In collaboration with community members, the project will investigate how to use Large Language Models (LLMs) like ChatGPT. It will uncover their benefits as well as potential harms while focusing on applications pertinent to the context. The objectives are to: (1) Establish a baseline understanding of AI, its current use, and its impact on communities; (2) Shift towards more responsible, community-focused research and development in AI; (3) Identify and prioritize the most critical areas for future investigation; and (4) Move toward responsible AI integration within community-engaged research. 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.
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