Transforming Disaster Risk Reduction With AI and Big Data: Legal and Interdisciplinary Perspectives

Chun, Kwok P. and Octavianti, Thanti and Dogulu, Nilay and Tyralis, Hristos and Papacharalampous, Georgia and Rowberry, Ryan and Fan, Pingyu and Everard, Mark and Francesch‐Huidobro, Maria and Migliari, Wellington and Hannah, David M. and Marshall, John Travis and Calasanz, Rafael Tolosana and Staddon, Chad and Ansharyani, Ida and Dieppois, Bastien and Lewis, Todd R. and Ponce, Juli and Ibrean, Silvia and Ferreira, Tiago Miguel and Peliño‐Golle, Chinkie and Mu, Ye and Delgado, Manuel Davila and Espinoza, Elizabeth Silvestre and Keulertz, Martin and Gopinath, Deepak and Li, Cheng (2025) Transforming Disaster Risk Reduction With AI and Big Data: Legal and Interdisciplinary Perspectives. WIREs Data Mining and Knowledge Discovery, 15 (2). ISSN 1942-4787

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Abstract

Managing complex disaster risks requires interdisciplinary efforts. Breaking down silos between law, social sciences, and natural sciences is critical for all processes of disaster risk reduction. It is essential to explore how AI enhances understanding of legal frameworks and environmental management, while also examining how legal and environmental factors may limit AI's role in society. From a co‐production review perspective, drawing on insights from lawyers, social scientists, and environmental scientists, principles for responsible data mining are proposed based on safety, transparency, fairness, accountability, and contestability. This discussion offers a blueprint for interdisciplinary collaboration to create adaptive law systems based on AI integration of knowledge from environmental and social sciences. When social networks are useful for mitigating disaster risks based on AI, the legal implications related to privacy and liability of the outcomes of disaster management must be considered. Fair and accountable principles emphasize environmental considerations and foster socioeconomic discussions related to public engagement. AI also has an important role to play in education, bringing together the next generations of law, social sciences, and natural sciences to work on interdisciplinary solutions in harmony. Although emerging AI approaches can be powerful tools for disaster management, they must be implemented with ethical considerations and safeguards to address concerns about bias, transparency, and privacy. The responsible execution of AI approaches, based on the dynamic interplay between AI, law, and environmental risk, promotes sustainable and equitable practices in data mining.

Item Type:	Article
Identification Number:	10.1002/widm.70011
Dates:	Date Event 20 March 2025 Accepted 14 April 2025 Published
Uncontrolled Keywords:	artificial intelligence, disaster risk reduction, interdisciplinary, law, public engagement
Subjects:	CAH17 - business and management > CAH17-01 - business and management > CAH17-01-01 - business and management (non-specific)
Divisions:	Business School > Management, Business and Marketing
Depositing User:	Gemma Tonks
Date Deposited:	09 Mar 2026 11:20
Last Modified:	09 Mar 2026 11:20
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16913

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