Artificial intelligence investments reduce risks to critical mineral supply

Speaker: Dr Joaquin Vespignani

Abstract: This seminar will present on the first economic theory of critical minerals for energy transition. This theory posits that back-ended critical mineral projects that have unaddressed  technical and nontechnical barriers, exhibit an additional risk for investors which is termed the "back-ended risk premium". The back-ended risk premium increases the cost of capital and therefore, has the potential to reduce investment in the sector, however, the back-ended risk premium may also reduce the gains in productivity expected from artificial intelligence (AI) technologies in the mining sector. Progress in AI may lessen the back-ended risk premium itself through shortening the duration of mining projects and the required rate of investment through reducing the associated risk. The seminar will cover our conclusion that the best way to reduce costs associated with energy transition is for governments to invest heavily in AI mining technologies and research.

Bio:  Dr Joaquin Vespignani is an Associate Professor of Economics and Finance at the University of Tasmania. With a PhD in Economics from the University of New South Wales and over 20 years of experience in macroeconomic forecasting and macro-energy, he specialises in applied macroeconomics and energy transition and the economics of critical mineral. Joaquin has published extensively in high-impact journals and serves on multiple advisory panels, including the Australian Treasury’s Macroeconomic Expert Panel. He is also the Co-Founder and Program Director of the Centre for Applied Macroeconomic Analysis at ANU and a Research Associate at the Federal Reserve Bank of Dallas.