Design Factors of Maestro: A Serious Game for Robust AI Education

Margarita Geleta, Jiacen Xu, Manikanta Loya, Junlin Wang, Sameer Singh, Zhou Li, Sergio Gago Masagué

Abstract: Training tools targeting robust AI are still in their infancy. We present Maestro, an effective open-source game-based platform for robust AI training in higher education, which includes counter- measures and prevention of AI vulnerabilities. Maestro provides goal-based scenarios (GBSs) where students are exposed to challenging life-inspired assignments in a competitive programming environment. The assessment of Maestro showed that its leader-board, a key gamification element, has been crucial for effective student learning. Students who felt the acquisition of new skills in robust AI tended to appreciate highly Maestro and scored highly on material consolidation, curiosity and maestry in robust AI.