The intersection of artificial intelligence (AI) and cybersecurity is emerging as an important field to ensure the integrity of the economy and critical infrastructure. Industry and government organizations require a workforce that is well-trained in both AI and cybersecurity. Courses and workshops are emerging to meet this need, but there is no published work addressing the content that needs to be taught and how to teach that content to develop a workforce at the intersection of AI and cybersecurity. This project addresses the gap in our understanding of how to prepare the workforce to apply AI to problems in cybersecurity by identifying workforce needs and developing solutions to learning barriers that could prevent broad participation in AI-enhanced cybersecurity. The project will create and disseminate an AI-enhanced cybersecurity course for advanced undergraduate and master's students and contribute new knowledge at the intersection of AI, cybersecurity, and education.

Artificial intelligence (AI) and cybersecurity are in-demand skills. Despite this demand, little is known about what factors influence computer science (CS) undergraduate students’ decisions on whether to specialize in AI or cybersecurity and how these factors may differ between populations. In this study, we interview undergraduate CS majors about their perceptions of the fields of AI and cybersecurity. Qualitative analyses of these interviews show that students have narrow beliefs about what kind of work AI and cybersecurity entail, the kinds of people who tend to work in these fields, and the potential societal impact AI and cybersecurity may have. Specifically, students tended to believe that working in AI requires math and training models, while cybersecurity consists of low-level programming; that innately smart people work in both fields; that working in AI comes with ethical concerns; and that cybersecurity skills are important in contemporary society. Some of these perceptions reinforce existing stereotypes about computing and may disproportionately affect the participation of students from groups historically underrepresented in computing. Our key contribution is identifying beliefs that students expressed about AI and cybersecurity that may affect their interest in pursuing the two fields and therefore may inform efforts to expand students’ views of AI and cybersecurity. Expanding student perceptions of AI and cybersecurity may help correct misconceptions and challenge narrow definitions, which in turn can encourage participation in these fields from all students.

Curriculuar Materials:
This class will be taught Winter 2023. The syllabus is available here.

Publications:
Vidushi Ojha, Christopher Perdriau, Brent Lagesse and Colleen M Lewis. Computing Specializations: Perceptions of AI and Cybersecurity Among CS Students Technical Symposium on Computer Science Education (SIGCSE), 2023. SIGCSE Site

Collaborators:
PIs
Brent Lagesse
Colleen Lewis
PhD Students
Vidushi Ojha
Christopher Perdriau