Climate Change and Policy: Measurements in an AI world
February 20th, 2025 (GMT)
Department of Economics, King's Business School, King's College London
Dr. Canh Thien Dang
Lecturer in King's College London
Dr. Canh Thien Dang is a Lecturer in Economics at the Department of Economics, King's Business School, King's College London. He is also an academic supervisor at the Institute of Finance and Technology, University College of London, and a chief examiner for the University of London International Programme (Econometrics). Before joining King's, he lectured and conducted research at the London School of Economics as an LSE Fellow in Economics, and at the University of Warwick as a postdoctoral fellow (in Economics). He completed my PhD in Economics at the University of Nottingham in 2018.
He uses both theory and data to answer questions at the intersection of economics and public policies. His research interests include Development Economics, Public Economics, and Applied Econometrics. His current research focuses on the economics of nonprofit organisations, financial data, public good provision (housing, security, preferential tax treatment, and public procurement), and innovation.
He has lectured courses in econometrics and macroeconomics at King's, LSE, and Warwick, and led seminars (tutorials) in various courses at Nottingham.
Background:
Climate change remains one of the most pressing global challenges, urging the development of robust policies driven by accurate and comprehensive data. In this context, artificial intelligence (AI) emerges as a transformative tool, enhancing our ability to monitor environmental changes and predict future impacts with unprecedented precision. AI technologies are instrumental in analyzing vast datasets—from satellite imagery to sensor networks monitoring air quality—facilitating real-time insights into climatic phenomena. This capability not only improves our understanding of climate dynamics but also enables the crafting of more effective and adaptive policies. As policymakers and scientists collaborate, the integration of AI into environmental governance holds the promise of more targeted interventions, optimizing resource use and mitigating adverse effects on ecosystems and communities worldwide. This workshop will explore these intersections, focusing on the advancements in AI that can bolster our response to climate change through informed policy-making.
Goal / Rationale:
The central problem this workshop aims to address is the gap between the vast amount of climate-related data available and the effective policies needed to combat climate change. Despite an abundance of raw data, the challenge lies in processing, interpreting, and translating this into actionable, informed policy decisions. Artificial Intelligence (AI) stands out as a crucial player in bridging this gap. Recent advances in AI, such as machine learning algorithms capable of predictive modeling and pattern recognition, enable more accurate forecasts of climate patterns and their impacts. These technologies can also enhance real-time decision-making through the automation of data analysis, providing policymakers with timely insights necessary for swift action.
Furthermore, AI facilitates the integration of diverse data sources, including remote sensing and citizen science platforms, creating a more comprehensive understanding of climate dynamics at both local and global scales. By leveraging these advancements, the workshop will explore methods to refine climate models, improve the accuracy of climate predictions, and develop more dynamic, responsive policy frameworks that can better mitigate the adverse effects of climate change on ecosystems and human societies.
Scope and Information for Participants:
The scope of this research topic encompasses several critical themes aimed at leveraging artificial intelligence to enhance climate change policies:
Contributors are encouraged to present novel research findings, methodologies, or case studies within these themes, fostering a comprehensive discussion on integrating AI into effective climate change policy-making.
Department of Economics, King’s Business School, Bush House, Aldwych Road, London, UK
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