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Causal Models Applied to the Patterns of Human Migration due to Climate Change

2023/11/03 by Kenneth Lai, Lai, Kenneth, Svetlana Yanushkevich +1
Social Sciences · #Artificial Intelligence (cs.AI) #Climate Change, Adaptation, Migration #Computers and Society (cs.CY) #FOS: Computer and information sciences

paper · pdf · doi:10.48550/arxiv.2311.14686

openalex publication_date 2023/11/03 · openalex created_date 2023/11/29 · openalex updated_date 2026/07/28

Abstract

The impacts of mass migration, such as crisis induced by climate change, extend beyond environmental concerns and can greatly affect social infrastructure and public services, such as education, healthcare, and security. These crises exacerbate certain elements like cultural barriers, and discrimination by amplifying the challenges faced by these affected communities. This paper proposes an innovative approach to address migration crises in the context of crisis management through a combination of modeling and imbalance assessment tools. By employing deep learning for forecasting and integrating causal reasoning via Bayesian networks, this methodology enables the evaluation of imbalances and risks in the socio-technological landscape, providing crucial insights for informed decision-making. Through this framework, critical systems can be analyzed to understand how fluctuations in migration levels may impact them, facilitating effective crisis governance strategies.

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