Building centaur responders: is emergency management ready for artificial intelligence?

This article examines the preparedness of emergency management (EM) for addressing questions pertaining to artificial intelligence (AI), encompassing its benefits to EM missions, the potential biases, the societal impacts, and more. We pinpoint two key shortcomings in early EM research on AI: (i) insufficient discussion of both AI's history and evolution; and (ii) a lack of frameworks for organising AI-related knowledge-building efforts. We offer a comprehensive survey of AI that is tailored for EM scholars and practitioners. Then, utilising the case of cyberspace and domain concept development, we explore the challenges of applying legacy ideas to disruptive technologies. We argue that current EM frameworks struggle to align with emerging technologies; as a result, we propose a new framework that bridges EM-specific concerns and broader social science inquiries and AI. This framework aims to facilitate research and practical efforts to navigate the complexities of AI technology within the context of EM.

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Publication Details

Journal
Disasters
Published
2026-04-21
DOI
https://doi.org/10.1111/disa.70054
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
0.00
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article

Building centaur responders: is emergency management ready for artificial intelligence?

Brittany “Brie” Haupt, Christopher Whyte
Disasters
Disaster Management and Resilience
article

Building centaur responders: is emergency management ready for artificial intelligence?

Brittany “Brie” Haupt, Christopher Whyte
article en

Abstract

This article examines the preparedness of emergency management (EM) for addressing questions pertaining to artificial intelligence (AI), encompassing its benefits to EM missions, the potential biases, the societal impacts, and more. We pinpoint two key shortcomings in early EM research on AI: (i) insufficient discussion of both AI's history and evolution; and (ii) a lack of frameworks for organising AI-related knowledge-building efforts. We offer a comprehensive survey of AI that is tailored for EM scholars and practitioners. Then, utilising the case of cyberspace and domain concept development, we explore the challenges of applying legacy ideas to disruptive technologies. We argue that current EM frameworks struggle to align with emerging technologies; as a result, we propose a new framework that bridges EM-specific concerns and broader social science inquiries and AI. This framework aims to facilitate research and practical efforts to navigate the complexities of AI technology within the context of EM.

DisastersVol. 50(3)
Virginia Commonwealth University (US)
Openalex Percentile: Top 5%
Disaster Management and Resilience
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