The Identification and Prioritization of Key AI Functionalities in Various Stages of Social Crisis Management

Document Type : Original Article

Authors

1 Supreme National Defense University

2 Assistant Professor at Supreme National Defense University

Abstract

Social crises, due to their sudden nature and complexity, have become a serious challenge to national security. Managing these crises requires access to diverse and extensive data as well as rapid processing capabilities that exceed human capacity alone. Artificial intelligence, as a disruptive technology, can play a crucial role in predicting, analyzing, and swiftly responding to social crises. This paper identifies and prioritizes AI functionalities in managing social crises with an emphasis on national security. The research methodology includes a systematic literature review and the use of the fuzzy TOPSIS model to rank these functionalities across the five stages of crisis management. Results indicate that the “prediction” stage holds the highest importance in social crisis management, as early identification and precise analysis at this stage can prevent crisis escalation and reduce public dissatisfaction. At this stage, predicting social unrest is the primary functionality, playing a fundamental role in effective crisis control. Additionally, attention to the “rapid response and emergency management” and “evaluation and learning” stages highlights the importance of prompt reaction and continuous learning from experiences to enhance crisis management strategies. The findings of this study could serve as a foundation for strategic changes in social crisis management and national security, aiding decision-makers in making smarter and more effective decisions during crises.

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protectiv & security researches
Volume 13, Issue 50 - Serial Number 50
summer 2024
August 2024
Pages 7-53

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