EAGER: Advancing AI Workforce Development and Community Engagement: CAHSI's NAIRR-Based Initiatives for Hispanic-Serving Institutions

This project seeks to improve AI workforce development and community involvement in Hispanic Serving Institutions (HSIs) through a collaboration between the Computing Alliance of Hispanic Serving Institutions (CAHSI) and the NAIRR pilot program. The project hosts an ideation laboratory and community gathering promoting cross-discipline collaborations and proposal writing which are using NAIRR resources.

A gap analysis is identifying if the resources effectively support underrepresented groups. The importance of this project is in its potential to advance AI literacy and research and promote diversity in the AI workforce. The dissemination occurs through competitive research proposals and a comprehensive report to the NSF's Office of Advanced Cyberinfrastructure (OAC), with broader impacts that include strengthening AI-related community involvement, workforce training, and contributions to national economic and technological growth.

The goals of the project are to promote cross-disciplinary AI research that address socio-economic and infrastructural challenges faced by underserved communities and to review the NAIRR catalog data, educational materials, training tools, and user support mechanisms to support AI research, education, and responsible AI for HSIs. CAHSI is well positioned to impact and contribute significantly in generating relevant collaborative research in AI.

CAHSI follows the ideation laboratory model that has been replicated several times to generate competitive proposals. The gap analysis includes identifying community problems, leaders, researchers, and educators for participating in the analysis, a framework and pathways model training for participants to assess materials, and collecting and analyzing discussions to include in a report to ensure inclusivity in AI research opportunities.

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.