Harnessing big data for enhanced equitable disaster resilience: Integrating technology and community-centric approaches

Abstract

Artificial intelligence (AI) stands at the forefront of transforming emergency management, offering unprecedented capabilities in disaster preparedness and response. Recent implementations demonstrate this shift from reactive to proactive approaches, particularly through flood prediction algorithms and maritime search-and-rescue optimization systems that integrate real-time vessel locations and weather data. However, the current landscape reveals a critical challenge: The opacity of AI systems creates a significant trust deficit among emergency responders and communities. Research findings paint a concerning picture of this transparency gap. A comprehensive survey of emergency management AI systems reveals striking statistics: 68 percent lack adequate documentation of their data sources, while 42 percent fail to provide clear justifications for their recommendations. This “black box” phenomenon carries serious implications, particularly when flood prediction models disproportionately affect vulnerable populations or when opaque decision-making processes lead to suboptimal resource allocation during critical rescue operations. Analysis of real-world applications in flood preparedness and search-and-rescue operations exposes systematic communication deficiencies within these essential emergency response frameworks. The research examines how varying levels of AI transparency directly influence emergency responders’ decision-making during crises, exploring the delicate balance between operational openness and security considerations. These findings highlight an urgent need for robust oversight mechanisms and context-specific transparency protocols to ensure ethical AI deployment in emergency management. The evidence points toward a clear solution: developing human-centric approaches that enhance rather than replace human capabilities in emergency response. This strategy requires establishing tailored transparency guidelines and monitoring systems that address current challenges while facilitating effective AI integration. By prioritizing both technological advancement and human oversight, emergency management systems can better serve their critical public safety mission.