The powers that artificial intelligence (AI) have developed are impressive, with recent success in leveraging human expertise at various stages of model development. However, AI can only attain its full potential when it actively teams with humans to co-create solutions. This study introduces a Human-AI Convergence (HAC) system for flood evacuation decision-making. The goal is to develop a unique, computationally effective HAC system for flood evacuation decision-making that integrates AI with transportation geospatial data, a river hydraulic model, and human data from X. The HAC system is smartly designed to forecast flood stage levels using AI across the US Geological Survey gauging stations, visualized in a web-based Google Earth architecture. HAC has been tested in the Lowcountry of South Carolina, where previous floods caused considerable damage to the transportation networks and increased traffic on evacuation routes. The system stands to advance the frontier of human-AI collaboration for real-time flood management. • A Human-AI Convergence (HAC) system is developed for flood evacuation decisions. • HAC integrates AI with a river hydraulic model and human data from X for evacuation decisions. • HAC is efficient in determining disruption to the transportation networks and evacuation routes.
Karanjit et al. (Sun,) studied this question.