Actionable AI for Climate and Environment

AI has emerged as a powerful tool with great potential to revolutionize climate and environmental research and decision-making processes. Its applications range from climate modeling and prediction to biodiversity conservation and natural disaster management. However, despite notable achievements, much of the AI research remains disconnected from real-world action and implementation. The chapter explores the reasons behind the limited actionable impact of AI research, including the gap between AI experts and domain-specific stakeholders, lack of interpretability and transparency, and the absence of robust validation and integration frameworks. To bridge this gap, scientists should prioritize interdisciplinary collaboration and engage actively with policymakers, practitioners, and affected communities. By involving stakeholders throughout the research process, AI models can be developed to address specific needs, generate actionable insights, and inform evidence-based decision-making. This chapter envisions a future where AI plays a crucial role in tackling climate and environmental challenges. It emphasizes the need for AI systems that are ethically grounded, interpretable, and adaptable to diverse contexts. Additionally, the chapter highlights the importance of integrating AI with traditional knowledge systems and empowering communities to leverage AI technologies for localized decision-making. By harnessing the power of AI in conjunction with human expertise and collective action, we can strive toward a more sustainable and resilient future for our planet.