AI in Social Good: LLM powered Interventions in Crisis Management and Disaster Response

<p>Large Language Models (LLMs) have emerged as transformative tools in crisis management and disaster response, offering real-time decision support, multilingual communication and rapid data synthesis for emergency responders and affected communities. This review examines the evolving landscape of LLM-based interventions in disaster scenarios, analysing their role in early warning systems, situational awareness, misinformation mitigation and humanitarian aid coordination. We provide a systematic evaluation of state-of-the-art models, including GPT-4, Claude and Mistral, highlighting their capabilities for processing unstructured crisis data from social media, satellite imagery and sensor networks. Additionally, we explore applications in emergency call triage, dynamic resource allocation and the automation of crisis communications to bridge information gaps in high-stakes environments.</p>

Authors

Publication Details

Journal
Journal of Artificial Intelligence Machine Learning and Data Science
Published
2025-02-20
DOI
https://doi.org/10.51219/jaimld/oluwatimilehin-odubola/510
Citations
6
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
13.70
Controls
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article

AI in Social Good: LLM powered Interventions in Crisis Management and Disaster Response

T. O. Adeyemi, Oluwatimilehin Odubola, Olaonipekun Olaitan Olajuwon, Nwaamaka Pearl Iduwe et al.
6 citations
Journal of Artificial Intelligence Machine Learning and Data Science
Big Data and Business Intelligence
13.70
article

AI in Social Good: LLM powered Interventions in Crisis Management and Disaster Response

T. O. Adeyemi, Oluwatimilehin Odubola, Olaonipekun Olaitan Olajuwon, Nwaamaka Pearl Iduwe, Aniema Inyang, Taiwo Odubola
article en
6 citations

Abstract

<p>Large Language Models (LLMs) have emerged as transformative tools in crisis management and disaster response, offering real-time decision support, multilingual communication and rapid data synthesis for emergency responders and affected communities. This review examines the evolving landscape of LLM-based interventions in disaster scenarios, analysing their role in early warning systems, situational awareness, misinformation mitigation and humanitarian aid coordination. We provide a systematic evaluation of state-of-the-art models, including GPT-4, Claude and Mistral, highlighting their capabilities for processing unstructured crisis data from social media, satellite imagery and sensor networks. Additionally, we explore applications in emergency call triage, dynamic resource allocation and the automation of crisis communications to bridge information gaps in high-stakes environments.</p>

Journal of Artificial Intelligence Machine Learning and Data ScienceVol. 3(1)
Climate action
Openalex Percentile: Top 2%
Big Data and Business Intelligence
13.70
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