Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–4 of 4 results
Advanced filters: Author: Miriam Aczel Clear advanced filters
  • In recent years, there has been a significant increase in the number of people displaced by climate-related damage to the physical and social environment. These migrants are more exposed to climate-related environmental damage than others and more vulnerable to its social and health impacts because they possess fewer resources for mitigation and adaptation. Emerging artificial intelligence (AI) tools and approaches may help improve understanding of climate migration and immobility and support more timely, equitable interventions to reduce avoidable harm before, during, and after displacement. While AI systems have already been applied to climate modeling, disaster forecasting, and public health surveillance, their adaptation to the context of climate-induced displacement remains under-studied and unevenly implemented. Specific AI applications can address the lived realities and systemic vulnerabilities of climate migrants, such as anticipatory relocation, equitable health service provision, and sustainable infrastructure in host regions. However, we must first address certain issues such as the risk of fostering greater inequality through inherent biases in training data; developing public-private-academic collaboratives to collect and integrate high-resolution, localized and open-access datasets tailored to address disparities; prioritizing energy-efficient algorithms and hardware and balancing performance with environmental sustainability; and developing responsible models of AI governance that capture co-design and co-ownership of the design process with climate migration stakeholders including vulnerable and affected communities. We therefore call for empirical research to document the effectiveness of current and proposed initiatives to apply AI in supporting climate migration equity and overcoming methodological and operational limitations and implementation risks. By aligning technological innovation with human-centric values and global justice, AI may contribute to shifting climate mobility policy from crisis response toward resilience-building, if paired with rights-based governance and accountable implementation. While most applications remain pilot-based, context-specific, and unevenly evaluated, this article advances a structured framework to guide future empirical research and governance.

    • Lawrence A. Palinkas
    • Mustafa F. Özbilgin
    • Michalle Mor Barak
    Comments & OpinionOpen Access
    Humanities and Social Sciences Communications
    Volume: 13, P: 1-8