AI and climate resilience governance
Sara Mehryar, Vahid Yazdanpanah, Jeffrey Tong
Abstract
process, all of which involve subjective, qualitative, and context-specific elements. Additionally, the study points out challenges such as difficulty of simulating complex long-term changes, and evolving policies and human behavior, reliance on data quality and computational resources, and the need for improved interpretability of results as areas requiring further development.
Topics & Concepts
Resilience (materials science)Corporate governanceClimate changeAdaptation (eye)Risk assessmentHazardPerspective (graphical)Risk analysis (engineering)Climate change adaptationManagement scienceEnvironmental resource managementComputer scienceEnvironmental planningBusinessEnvironmental sciencePsychologyArtificial intelligenceEngineeringEcologyComputer securityFinanceBiologyPhysicsNeuroscienceThermodynamicsInfrastructure Resilience and Vulnerability AnalysisFlood Risk Assessment and ManagementRisk Perception and Management