Beginnings: Enabling access for underserved community college computer science students in artificial intelligence with micro internship and industry mentorship

Enabling Access to Artificial Intelligence Careers for Overlooked and Underserved Community College Computer Science Students Using Micro-Internships and Industry Mentorships Artificial Intelligence and Machine Learning (AI/ML) are rapidly evolving technologies that have already found broad applications in most industries, but technology employers report a lack of recent graduates with experience in AI/ML. Although internships and mentorship can help students break into this field, their scalability is hindered by the level of commitment demanded of participants. This expectation denies access to these opportunities for many students, especially non-traditional students enrolled at Career and Technical Colleges (CTCs). This project addresses the need for a more skilled AI/ML workforce by creating micro-internships combined with career mentorship from industry professionals, focused on AI/ML, and integrated with CTC Computer Science programs. The project will build a diverse AI/ML workforce by providing 150 CTC students with practical AI/ML skills. The project will accept three annual cohorts of 50 students each into a guided AI/ML pathway. Each cohort will complete 1-2 micro-internships wherein each student will contribute to an industry-relevant AI/ML open source project, meet monthly with two assigned career mentors over an eight-month period, and attend in cohort workshops and meetings. Project researchers will collaborate with CTC faculty to award academic credit to students as applicable for their participation in experiential learning activities. The project includes a research component that will generate new knowledge on the use and effectiveness of open-source micro-internships and mentoring in AI/ML fields, CTC student job placement assistance in AI/ML, and the perceptions held by industry professionals of CTC students pursuing careers in AI/ML. The interventions developed by this project may be used more broadly to improve workforce readiness for non-traditional, overlooked, and underserved students with unique strengths and backgrounds. 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.