Enhancing AI-Centered Social Cybersecurity Education through Learning Platform Design

Artificial Intelligence (AI) technologies have become increasingly pervasive in our daily lives. Recent breakthroughs such as large language models (LLMs) are being increasingly used globally to enhance their work methods and boost productivity. However, the advent of these technologies has also brought forth new challenges in the critical area of social cybersecurity. While AI has broadened new frontiers in addressing social issues, such as cyberharassment and cyberbullying, it has also worsened existing social issues such as the generation of hateful content, bias, and demographic prejudices. Although the interplay between AI and social cybersecurity has gained much attention from the research community, very few educational materials have been designed to engage students by integrating AI and socially relevant cybersecurity through an interdisciplinary approach. In this paper, we present our newly designed open-learning platform, which can be used to meet the ever-increasing demand for advanced training in the intersection of AI and social cybersecurity. The designed platform, which consists of hands-on labs and education materials, incorporates the latest research results in AI-based social cybersecurity, such as cyberharassment detection, AI bias and prejudice, and adversarial attacks on AI-powered systems, are implemented using Jupyter Notebook, an open-source interactive computing platform for effective hands-on learning. Through a user study of 201 students from two universities, we demonstrate that students have a better understanding of AI-based social cybersecurity issues and mitigation after doing the labs, and they are enthusiastic about learning to use AI algorithms in addressing social cybersecurity challenges for social good.