Artificial Intelligence and Machine Learning in Crisis Communication: A Management Information System Perspective

Muhammed Zakir Hossain, Nasrin Akter, Latul Hasan, Muhim Bepari and Samia Sultana
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Muhammed Zakir Hossain: Associate Professor, Department of Business Studies, State University of Bangladesh, Bangladesh
Nasrin Akter: Stanton University, United States of America
Latul Hasan: International American University, United States of America
Muhim Bepari: Pacific States University, United States of America
Samia Sultana: Southern California State University, United States of America

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Abstract: This paper investigates the function of Artificial Intelligence (AI) and Machine Learning (ML) in augmenting crisis communication, analyzing their applications, efficacy, and obstacles to their implementation. Utilizing a mixed-methods approach that encompasses case studies of significant crises such as the COVID-19 pandemic, Hurricane Katrina, and the Australian bushfires, alongside expert interviews and a survey of professionals, the research underscores how AI/ML tools enhance decision-making speed, public sentiment analysis, and real-time communication during crises. Nonetheless, the study also reveals considerable impediments, including ethical dilemmas, data privacy concerns, and the necessity for human oversight in AI-driven decision-making. The research concludes that although AI and ML possess substantial potential to transform crisis communication, addressing these challenges necessitates meticulous integration, ethical frameworks, and improved infrastructure.

Keywords: Decision Support Systems (DSS); Management Information Systems (MIS); Machine Learning (ML); Artificial Intelligence (AI); Crisis Communication (CC) (search for similar items in EconPapers)
Date: 2025-04-22
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Published in European Journal of Innovative Studies and Sustainability, 2025, 1 (3), pp.149-163. ⟨10.59324/ejiss.2025.1(3).12⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05736603

DOI: 10.59324/ejiss.2025.1(3).12

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