Cyberai innovation: modular AI security education for the public sector workforce

The National Science Foundation Division of Graduate Education awarded Winston-Salem State University $496,376 on September 1, 2026, under the STEM Education program (CFDA 47.076) to develop modular AI security curriculum for the public sector workforce.

The project will embed AI security concepts into four self-contained teaching units integrated into existing healthcare management, education, and computer science courses. The units will cover how AI systems fail or face attack, how to evaluate AI tools before organizational adoption, how to respond when AI systems cause harm or trigger data breaches under HIPAA and FERPA, and what legal and ethical duties govern public-sector AI use. Each unit will be designed for delivery in person or online to accommodate working professionals.

Practitioners from a local school district, regional hospital systems, and a county government agency will co-develop content with real-world case studies. Cisco Systems will validate the curriculum. All materials will be shared freely through faculty workshops and open online channels.

The award runs through August 31, 2029, with performance at Winston-Salem, North Carolina. The project targets healthcare administrators, teachers, and public program managers—many of them Winston-Salem State University graduates—who increasingly manage AI technologies without adequate preparation to recognize system failures, manipulation, or data exposure.

Abstract

Artificial intelligence (AI) tools support critical decisions in hospitals, schools, and government agencies, yet the people who oversee these systems are seldom trained to recognize when an AI tool is failing, being manipulated, or exposing sensitive data. Healthcare administrators, teachers, and public program managers increasingly manage technologies they were never prepared to evaluate. This project will address that GAP at winston-salem state university, whose graduates largely enter healthcare, education, and public service sectors. Over the duration of this grant, the project will embed AI security concepts into courses students already take, so graduates can confidently question the AI systems they will manage. By strengthening a workforce that serves wider communities, the project advances the national interest in a secure digital society and broadens participation in cybersecurity education. The project will create four self-contained teaching units on AI security for existing healthcare management, education, and computer science courses, without new programs or resources. Units will be designed to offer either in person or online so working professionals can participate. The units will explain how AI systems can fail or be attacked; how to evaluate an AI tool before an organization adopts IT; how to respond when an AI system causes harm or a data breach under federal privacy laws such as the health insurance portability and accountability act (hipaa) and the family educational rights and privacy act (ferpa); and what legal and ethical duties govern public-sector AI use. Practitioners from a local school district, regional hospital systems, and a county government agency will CO-develop the content with real-world case studies, and industry partner cisco systems will validate the curriculum. All materials will be shared freely through faculty workshops and an open online repository, allowing other universities to adopt them without a formal partnership. This project is supported by the cyberaicorps scholarship for service (cyberai SFS) program which funds proposals to increase national capacity to educate and train professionals in artificial intelligence (AI) or cybersecurity, and to support their placement and retention in the cyberai mission of government organizations. The scholarship track funds academic institutions to award scholarships to students in exchange for their government service. The innovation track seeks transformative education proposals in the areas of AI, cybersecurity, or the integration of AI and cybersecurity 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.- subawards are not planned for this award.