EAGER: SaTC-EDU: Transformative Educational Approaches to Meld Artificial Intelligence and Cybersecurity Mindsets

Society is becoming increasingly dependent on technology that is susceptible to abuse by bad actors. Artificial Intelligence (AI) and cybersecurity are, like much of computer science, extremely technical fields that continue to advance at rapid rates both in knowledge and application. Computer science often allows a small team to leverage its members' expertise through the use of plug-and-play solutions that require little or no user intervention.

In contrast, it has become obvious that reliance on a limited number of highly skilled people does not work as well for cybersecurity . This inadequacy appears to be addressable through the application of AI concepts and by training individuals who are expert in both AI and cybersecurity. However, the amount of time, focus, and effort required to become highly proficient in both AI and cybersecurity fields is a significant barrier to this solution.

This project strives to explore potentially transformative educational approaches in order to prepare a more robust workforce at the intersection of AI and cybersecurity. Specifically, the project team proposes a collaborative, group-based, and hands-on course that combines students with a specific interest and existing background in either the AI or cybersecurity domain with students with the complementary background. This educational approach will produce students who share a combined AI and cybersecurity mindset.

The fundamental assumption of this project is that students will rarely need to apply a deep, technical understanding of the AI field within the cybersecurity domain. As such, a more viable and succinct approach to producing a workforce competent in both domains is to focus on expanding students’ toolkits and providing them reference-anchors. This approach will enable students to more efficiently collaborate with domain-specific experts and across domain boundaries when they enter the workforce.

In order to explore this approach, the project team proposes to develop a course directed at students with backgrounds in AI or cybersecurity. The course will combine elements from problem-based learning , studio-based learning, and group-based learning. This approach will cultivate students with a melded AI and cybersecurity mindset even though they may lack technical depth in their non-focus domain.

This mindset or awareness will prepare these students to enter the workforce and collaborate across technical disciplines. While a future goal may be combined AI and cybersecurity “natives” it is important first to evaluate the more easily attainable option of instilling technical awareness and a multi-perspective approach.

This project is supported by a special initiative of the Secure and Trustworthy Cyberspace (SaTC) program to foster new, previously unexplored, collaborations between the fields of cybersecurity, artificial intelligence, and education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.

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.