Collaborative Research: CUE-M: LEVEL UP AI: Developing Strategies to Increase Capacity and Inclusion in AI Education

The Computing Research Association (CRA) and New Mexico State University in collaboration with Association for the Advancement of Artificial Intelligence (AAAI), Association for Computing Machinery (ACM), Institute of Electrical and Electronics Engineers Computer Society (IEEE-CS), and several BPC Alliances will convene LEVEL UP AI to build consensus on strategies to increase capacity and diversity in Artificial Intelligence (AI) education and to expand AI curriculum and infrastructure. With the increasing demand for Artificial Intelligence (AI) professionals, faculty, and researchers, there is an imperative to develop a shared vision that includes expectations and plans for an expanded AI curriculum, the infrastructure needed to deliver a quality AI education experience, and the strategies, principles, and resources that are required to ensure access and inclusivity in AI education.

LEVEL UP AI is the Computing in Undergraduate Education effort to mobilize the computing community and build a consensus on strategies to increase capacity and diversity in AI education. LEVEL UP AI builds on the experiences and models developed by the Computing Research Association for visioning and consensus building across broad segments of the computing community around issues of excellence, inclusion, access, and diversity.

The products of LEVEL UP AI will contribute to pathways to broaden participation in AI and promote excellence in AI education.

LEVEL UP AI adopts a 2-phase process: (1) a series of virtual roundtable discussions to gather multiple perspectives around issues of increased capacity and inclusion in AI education, followed by (2) in-person workshops to develop community, consensus, and action. The outcomes of the 2-day in-person workshops are to create community and action for a common vision to mobilize the country to increase both capacity and inclusion in AI education.

The expected outcomes of the project include (1) reports that articulate the vision and its supporting arguments, (2) best practices for strategies to increase capacity and inclusivity in AI education, (3) infrastructure resource categories and types that ensure the democratization of AI education, and (4) processes and metrics for assessing capacity, quality, and inclusivity in AI education.

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.