Atefeh Soroori Sarabi
Abstract
This study examines the intersection of artificial intelligence, global governance, and disaster risk management through a qualitative investigation of 92 Iranian experts across disciplines ...
Read More
This study examines the intersection of artificial intelligence, global governance, and disaster risk management through a qualitative investigation of 92 Iranian experts across disciplines such as geoinformatics, emergency planning, and environmental engineering. While AI offers a significant promise for enhancing early warning systems, damage assessments, and real-time decision-making, its integration into DRM systems remains constrained by fragmented data infrastructures, institutional silos, and geopolitical exclusions. Participants underscored AI’s potential to improve response coordination and risk forecasting, but emphasized the need for robust data governance, algorithmic transparency, and capacity building. The study highlights critical ethical and political concerns—particularly in countries like Iran facing technological marginalization due to sanctions and limited access to global data ecosystems. Drawing on grounded theory and thematic analysis, the research identifies institutional fragmentation, interoperability barriers, and normative governance deficits as primary obstacles to AI-enabled DRM. It argues for a globally coordinated approach grounded in justice, inclusivity, and human-centered design.
