American Journal of Advanced Multidisciplinary Research and Innovation

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Artificial Intelligence Applications in Climate Risk Assessment and Environmental Policy

Author(s) Mykel J. Kochenderfer
Country United States
Abstract Climate change has intensified the need for accurate risk assessment, timely environmental monitoring, and evidence-based policymaking. Conventional approaches to climate risk analysis often face limitations associated with the volume, complexity, and spatial and temporal variability of environmental data. Artificial Intelligence (AI), including machine learning, deep learning, natural language processing, computer vision, and predictive analytics, provides new opportunities for processing large-scale climate and environmental datasets and supporting more responsive policy decisions. This study examines the applications of AI in climate risk assessment and environmental policy, with particular attention to climate prediction, extreme-event forecasting, vulnerability assessment, environmental monitoring, adaptation planning, and policy evaluation. A qualitative and analytical methodology based on secondary literature, scientific studies, policy frameworks, and international environmental reports is employed. The analysis indicates that AI can improve the identification of climate-related hazards, enhance early-warning systems, support ecosystem monitoring, and facilitate evidence-based environmental governance. However, limitations involving data quality, model uncertainty, computational requirements, algorithmic bias, transparency, and institutional capacity remain significant. The study argues that AI should complement rather than replace scientific expertise and public policy judgment. Future climate governance will require transparent, explainable, interdisciplinary, and ethically governed AI systems capable of integrating scientific knowledge with local and community-level information.
Keywords Artificial Intelligence, Climate Risk, Environmental Policy, Machine Learning, Climate Change, Environmental Monitoring, Climate Adaptation, Predictive Analytics
Field Engineering
Published In Volume 4, Issue 2, March-April 2022
Published On 2022-03-21
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