Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a focus group report

TL;DR

This paper discusses the challenges and opportunities in AI ethics education within cybersecurity, emphasizing the need for comprehensive curricula, ethical frameworks, and improved communication skills to prepare future practitioners.

Contribution

It highlights key educational challenges in AI cybersecurity and proposes integrating technical, ethical, and communication training for effective learning.

Findings

Need for clear ethical principles in AI cybersecurity education

Importance of foundational AI knowledge to address 'black box' issues

Recommendations for curricula that include systems thinking and communication

Abstract

The emergence of AI tools in cybersecurity creates many opportunities and uncertainties. A focus group with advanced graduate students in cybersecurity revealed the potential depth and breadth of the challenges and opportunities. The salient issues are access to open source or free tools, documentation, curricular diversity, and clear articulation of ethical principles for AI cybersecurity education. Confronting the "black box" mentality in AI cybersecurity work is also of the greatest importance, doubled by deeper and prior education in foundational AI work. Systems thinking and effective communication were considered relevant areas of educational improvement. Future AI educators and practitioners need to address these issues by implementing rigorous technical training curricula, clear documentation, and frameworks for ethically monitoring AI combined with critical and system's thinking and communication skills.