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Transforming disaster risk reduction with AI and Big Data: Legal and interdisciplinary perspectives

Chun, Kwok; Octavianti, Thanti; Dogulu, Nilay; Tyralis, Hristos; Papacharalampous, Georgia; Rowberry, Ryan; Fan, Pingyu; Everard, Mark; Francesch-Huidobro, Maria; Migliari, Wellington; Hannah, David M.; Marshall, John Travis; Calasanz, Rafael Tolosana; Staddon, Chad; Ansharyani, Ida; Dieppois, Bastien; Lewis, Todd R.; Ponce, Juli; Ibrean, Silvia; Ferreira, Tiago Miguel; Peliño-Golle, Chinkie; Mu, Ye; Delgado, Manuel Davila; Espinoza, Elizabeth Silvestre; Keulertz, Martin; Gopinath, Deepak; Li, Cheng

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Authors

Profile image of Kwok Chun

Dr Kwok Chun Kwok.Chun@uwe.ac.uk
Lecturer in Environmental Managment

Nilay Dogulu

Hristos Tyralis

Georgia Papacharalampous

Ryan Rowberry

Pingyu Fan

Mark Everard Mark.Everard@uwe.ac.uk
Associate Professor in Ecosystem Services

Maria Francesch-Huidobro

Wellington Migliari

David M. Hannah

John Travis Marshall

Rafael Tolosana Calasanz

Profile image of Chad Staddon

Chad Staddon Chad.Staddon@uwe.ac.uk
Professor/Associate Head of Department: Research and Scholarship

Ida Ansharyani

Bastien Dieppois

Todd Lewis Todd.Lewis@uwe.ac.uk
Senior Lecturer in Ecology and Environmental Technology

Juli Ponce

Silvia Ibrean

Tiago Miguel Ferreira

Chinkie Peliño-Golle

Ye Mu

Manuel Davila Delgado Manuel.Daviladelgado@uwe.ac.uk
Associate Professor - AR/VR Development with Artificial Intelligence

Elizabeth Silvestre Espinoza

Martin Keulertz

Cheng Li



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.

Journal Article Type Article
Acceptance Date Mar 20, 2025
Online Publication Date Apr 14, 2025
Publication Date Jun 30, 2025
Deposit Date Mar 28, 2025
Publicly Available Date Apr 23, 2025
Journal Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Electronic ISSN 1942-4795
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 15
Issue 2
Article Number e70011
DOI https://doi.org/10.1002/widm.70011
Keywords artificial intelligence, interdisciplinary, law, disaster risk reduction, public engagement
Public URL https://uwe-repository.worktribe.com/output/14149803
This output contributes to the following UN Sustainable Development Goals:

SDG 6 - Clean Water and Sanitation

Ensure availability and sustainable management of water and sanitation for all

SDG 8 - Decent Work and Economic Growth

Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all

SDG 9 - Industry, Innovation and Infrastructure

Build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation

SDG 13 - Climate Action

Take urgent action to combat climate change and its impacts

SDG 17 - Partnerships for the Goals

Strengthen the means of implementation and revitalize the global partnership for sustainable development

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