Contemporary Global Rare Earth Politics: Persistent Myths, Policy Challenges, and Possible Pathways Forward

This event is co-hosted by the Centre for Grand Strategy and the Environmental Security Research Group, Department of War Studies, King's College London.

Speaker: Dr Julie Michelle Klinger (Department of Geography and Spatial Sciences, University of Delaware)

Discussant: Professor Joe Maiolo (Department of War Studies, KCL)

Rare earth elements are not rare, but they are critical inputs to many kinds of technologies. Based on over a decade of research in different parts of the world, this talk unpacks persistent myths in Anglophone discourse, analyzes long-standing policy challenges in the US, and discusses possible pathways forward for the international community.

Julie Michelle Klinger (she/her) holds a PhD in Geography from the University of California, Berkeley. She is an Assistant Professor in the Department of Geography and Spatial Sciences at the University of Delaware and Associate Director of the Minerals, Materials, and Society Program. Focusing on the dynamics of global resource frontiers and space-based technologies with particular emphases in China, Brazil, and the US, Dr. Klinger has conducted extensive ethnographic, qualitative, and quantitative fieldwork over the past 15 years. She has published numerous articles on rare earth elements, natural resource use, environmental politics, and outer space.

Her 2017 Book Rare Earth Frontiers: From Terrestrial Subsoils to Lunar Landscapes was awarded the Meridian Book Prize for its “unusually important contribution to the art and science of geography.” Dr. Klinger’s current work focuses on characterizing the environmental, social, and climate impacts of rare earth and other critical mineral supply chains, from extraction to disposal, to accelerate a just transition to a low-carbon future. She is the Principle Investigator of the U.S. National Science Foundation-funded project Characterizing the Global Illicit Trade in Energy-Critical Materials using Machine Learning, Remote Sensing, and Qualitative Research.