Computing Specializations: Perceptions of AI and Cybersecurity among CS Students

Vidushi Ojha, Christopher Perdriau, Brent Lagesse, Colleen M. Lewis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Artificial intelligence (AI) and cybersecurity are in-demand skills, but 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 interviewed undergraduate CS majors about their perceptions 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 work in these fields, and the potential societal impact AI and cybersecurity may have. Specifically, students tended to believe that all work 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 may, therefore, 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.

Original languageEnglish (US)
Title of host publicationSIGCSE 2023 - Proceedings of the 54th ACM Technical Symposium on Computer Science Education
PublisherAssociation for Computing Machinery
Pages966-972
Number of pages7
ISBN (Electronic)9781450394314
DOIs
StatePublished - Mar 2 2023
Event54th ACM Technical Symposium on Computer Science Education, SIGCSE 2023 - Toronto, Canada
Duration: Mar 15 2023Mar 18 2023

Publication series

NameSIGCSE 2023 - Proceedings of the 54th ACM Technical Symposium on Computer Science Education
Volume1

Conference

Conference54th ACM Technical Symposium on Computer Science Education, SIGCSE 2023
Country/TerritoryCanada
CityToronto
Period3/15/233/18/23

Keywords

  • artificial intelligence
  • broadening participation in computing
  • computer science education
  • cybersecurity

ASJC Scopus subject areas

  • Education
  • General Computer Science

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