This chapter explores how artificial intelligence (AI) is helping Asia move towards a sustainable and climate-neutral economy. The chapter thoroughly examines AI's potential influence on decarbonization, energy efficiency, and green growth in the area, focusing on achieving the Sustainable Development Goals (SDGs). Presenting case studies highlighting successful implementations, it investigates applications such as renewable energy forecasts, smart grid management, and sustainable agriculture practices. The chapter addresses issues such as ethical considerations and technological constraints, highlighting the need for competent human capital. It highlights the significance of ongoing innovation, policy support, and cooperation to fully use AI's potential in accomplishing the SDGs. Looking ahead, it describes new trends and future paths. The conclusion emphasizes the value of capacity building, ethical concerns, and strategic planning to successfully integrate AI and promote a more sustainable and environmentally friendly future for Asia.
TopIntroduction
Artificial Intelligence (AI) refers to the development of computer systems capable of performing tasks that typically require human intelligence. These tasks encompass learning, reasoning, problem-solving, perception, speech recognition, and language understanding. AI technologies include machine learning, natural language processing, computer vision, and robotics (Russell and Norvig, 2009).
The Impact of AI on the Sustainable Development Goals (SDGs): An Overview of the SDGs
The Sustainable Development Goals (SDGs) are a set of 17 global objectives outlined by the United Nations to address a wide range of social, economic, and environmental challenges. Achieving these goals by 2030 requires innovative approaches and cutting-edge technologies.
The Reasons Why AI is Said to Help Reach SDGs:
Optimization and Efficiency: AI's ability to handle vast amounts of data and optimize complex systems makes it a powerful tool for resource management, energy efficiency, and waste reduction (Rahman et al., 2020). Examples include AI-driven smart grids that optimize energy distribution, reduce energy consumption, and promote sustainability (Wang et al., 2019).
Predictive Analysis for Environmental Action:
AI can analyze environmental data, predict changes, and facilitate informed decision-making for environmental mitigation and adaptation strategies (Kamilaris, Fonts, and Prenafeta-Boldú, 2018). An example is AI models predicting the impact of climate change on crop yields, enabling farmers to adopt adaptive farming practices (Chen et al., 2021).
Natural Resource Management:
AI contributes to sustainable resource utilization by monitoring and managing ecosystems, preserving biodiversity, and preventing illicit activities (Dandois and Ellis, 2010). For instance, AI-enabled satellite imagery analysis monitors deforestation to support conservation efforts (Mascaro et al., 2014).
Healthcare Advancements:
AI applications in healthcare contribute to achieving SDG 3 (Good Health and Well-being) by enhancing diagnostics, drug discovery, and personalized medicine (Topol, 2019). An example is AI algorithms for early disease detection, improving treatment outcomes, and reducing healthcare costs (Obermeyer and Emanuel, 2016).