Situational Awareness as the Imperative Capability for Disaster Resilience in the Era of Complex Hazards and Artificial Intelligence

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Pak, Hongrak, Mostafavi, Ali
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866909749615788032
author Pak, Hongrak
Mostafavi, Ali
author_facet Pak, Hongrak
Mostafavi, Ali
contents Disasters frequently exceed established hazard models, revealing blind spots where unforeseen impacts and vulnerabilities hamper effective response. This perspective paper contends that situational awareness (SA)-the ability to perceive, interpret, and project dynamic crisis conditions-is an often overlooked yet vital capability for disaster resilience. While risk mitigation measures can reduce known threats, not all hazards can be neutralized; truly adaptive resilience hinges on whether organizations rapidly detect emerging failures, reconcile diverse data sources, and direct interventions where they matter most. We present a technology-process-people roadmap, demonstrating how real-time hazard nowcasting, interoperable workflows, and empowered teams collectively transform raw data into actionable insight. A system-of-systems approach enables federated data ownership and modular analytics, so multiple agencies can share timely updates without sacrificing their distinct operational models. Equally crucial, structured sense-making routines and cognitive load safeguards help humans remain effective decision-makers amid data abundance. By framing SA as a socio-technical linchpin rather than a peripheral add-on, this paper spotlights the urgency of elevating SA to a core disaster resilience objective. We conclude with recommendations for further research-developing SA metrics, designing trustworthy human-AI collaboration, and strengthening inclusive data governance-to ensure that communities are equipped to cope with both expected and unexpected crises.
format Preprint
id arxiv_https___arxiv_org_abs_2508_16669
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Situational Awareness as the Imperative Capability for Disaster Resilience in the Era of Complex Hazards and Artificial Intelligence
Pak, Hongrak
Mostafavi, Ali
Computers and Society
Artificial Intelligence
Human-Computer Interaction
Disasters frequently exceed established hazard models, revealing blind spots where unforeseen impacts and vulnerabilities hamper effective response. This perspective paper contends that situational awareness (SA)-the ability to perceive, interpret, and project dynamic crisis conditions-is an often overlooked yet vital capability for disaster resilience. While risk mitigation measures can reduce known threats, not all hazards can be neutralized; truly adaptive resilience hinges on whether organizations rapidly detect emerging failures, reconcile diverse data sources, and direct interventions where they matter most. We present a technology-process-people roadmap, demonstrating how real-time hazard nowcasting, interoperable workflows, and empowered teams collectively transform raw data into actionable insight. A system-of-systems approach enables federated data ownership and modular analytics, so multiple agencies can share timely updates without sacrificing their distinct operational models. Equally crucial, structured sense-making routines and cognitive load safeguards help humans remain effective decision-makers amid data abundance. By framing SA as a socio-technical linchpin rather than a peripheral add-on, this paper spotlights the urgency of elevating SA to a core disaster resilience objective. We conclude with recommendations for further research-developing SA metrics, designing trustworthy human-AI collaboration, and strengthening inclusive data governance-to ensure that communities are equipped to cope with both expected and unexpected crises.
title Situational Awareness as the Imperative Capability for Disaster Resilience in the Era of Complex Hazards and Artificial Intelligence
topic Computers and Society
Artificial Intelligence
Human-Computer Interaction
url https://arxiv.org/abs/2508.16669