A Study of the Application of AI & ML to Climate Variation, with Particular Attention to Legal & Ethical Concerns

Abstract

INTRODUCTION: This research investigates the utilization of artificial intelligence and machine learning in comprehending various climatic variations, emphasizing the associated use of legal and ethical considerations. This escalating impact of climatic change necessitates innovative approaches and the potential of AI/ML to offer tools for analysis and prediction. OBJECTIVES: The primary objective here, was to assess the effectiveness of AI/ML in the deciphering of varying climatic patterns and projecting the future trends. Concurrently, this study aims for the identification and analysis of legal and ethical challenges that may arise from the integration of these technologies in climatic research and policy. METHODS: Here, the literature review forms the basis for understanding various AI/ML applications related to climate science. This study employs various case analyses to examine the existing models to gauge the accuracy and efficiency of predictions. Legal frameworks and ethical principles need to be scrutinized through the qualitative analysis of relevant policies and guidelines. RESULTS: This extensive research reveals the various significant contributions of AI/ML in the enhancement of climatic modeling precision and the prediction of extreme events. However legal and ethical considerations such as data privacy, accountability, and transparency also emerged as crucial challenges which required careful attention. CONCLUSION: While AI/ML exhibited great potential in the advancement of climate research, a balanced approach is imperative to navigate the associated legal and ethical concerns. Striking this equilibrium will be pivotal for ensuring responsible and effective deployment of these technologies in the pursuit of best understanding and mitigating varying climatic variations.