Advancements in conversational artificial intelligence (AI) enable scalable, web-based training environments beyond traditional classroom settings to support learning. In emergency communication centers such as 9-1-1, trainees have limited opportunities to practice diverse call-handling scenarios, as it relies on role-play instruction and constrained instructor availability. We introduce SHIELD (Strengthening Human Intervention in Emergencies through Learning with Data and AI), a framework and online conversational AI system designed to support scenario-based training through interactive simulations, adaptive feedback, and learning analytics. SHIELD integrates AI-generated call simulations with data science techniques to capture fine-grained trainee interaction data, including decision-making behavior, response timing, and corrective actions. These logged interactions are analyzed to provide real-time metacognitive nudges during simulated calls and post-performance feedback through AI-assisted analytics. The framework is informed by principles of self-regulated learning to structure training across planning, execution, and reflection phases. This demo showcases SHIELD as a web-based prototype deployed for emergency call-taker training and discusses design insights from initial testing sessions conducted in collaboration with a public safety communications agency. The system also highlights potential applicability to other high-stakes operational training settings.

Compound threats, in which cyberattacks are targeted in the aftermath of a natural hazard, pose an important emerging threat for critical infrastructure. In this paper, we analyze the system design implications of compound threats for power grid SCADA systems for the first time. We introduce a novel compound threat model and develop a tool for analyzing resilience under this threat model. Using our tool, we compare the resilience of existing fault- and intrusion-tolerant SCADA system architectures in case studies based on two power utilities: Hawaiian Electric (HECO) and Florida Power & Light (FPL). We show that no existing system architecture adequately addresses compound threats, but that it is possible to improve resilience to such threats by explicitly considering natural hazards in the system design and by employing a new out-of-band reconfiguration mechanism for intrusion-tolerant systems. However, an important outcome of our work is that compound threats remain a challenging problem, with no complete solution.