Pioneering Data-Driven Environmental Governance Through Artificial Intelligence

Environmental governance in the contemporary era is confronted with complex challenges such as climate change, environmental pollution, and the depletion of natural resources. To overcome these challenges, there is a need for innovative and efficient approaches that can process and analyze vast amounts of environmental data to facilitate evidence-based decision-making. Artificial intelligence (AI) has emerged as a powerful tool in this context, capable of revolutionizing environmental governance through predictive modeling, intelligent monitoring systems, and data-driven decision-making tools. This research investigates the transformative role of AI in environmental governance through data-driven approaches. Employing a mixed-methods approach that includes a systematic literature review, qualitative content analysis, and semi-structured interviews with experts, this study identifies and analyzes the key applications of AI in eight core areas of environmental governance. The findings reveal that AI has significant potential to improve climate change modeling, biodiversity monitoring, air and water quality management, natural resource optimization, waste management, disaster risk reduction, industrial risk assessment, and ecosystem restoration. However, important ethical challenges such as privacy concerns, exacerbating inequalities, and the need for transparency in decision-making have also been identified. This study emphasizes the need to develop robust governance frameworks to ensure the responsible and equitable use of AI in environmental governance.

کلیدواژه ها:

Governance ، Environment ، Artificial Intelligence (AI) ، Data-driven