Pentagon Plans AI Program To Help Estimate Prices And Predicts Critical Mineral Supply
JAKARTA - The United States Department of Defense plans a program to estimate prices and predict supplies of critical minerals such as nickel and cobalt. The program, announced last October, aims to increase global metal market transparency. The US government wants to support domestic production to reduce dependence on China, the current market leader.
DARPA, the Pentagon's defense research division, leads the program by using artificial intelligence to build metal price models. They want to overcome market intransparencies and reduce the risks faced by futures prices and agents to price national security.
The program, called Open Price Exploration for National Security (OPEN), aims to provide price transparency to government agencies and commercial entities and predict the impact of market shocks. The project is not meant to replace futures exchanges such as the London Metal Exchange (LME), but to provide clearer structural price estimates.
DARPA and the US Geological Survey will hire private contractors to develop this artificial intelligence model. The program will be run in three phases over two years.
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The importance of this program is emphasized by cases such as the announcement of Jervois Global to delay cobalt projects in Idaho due to low market prices. This shows how fluctuating commodity prices can affect new mining investments in the US.
The program is also trying to predict the impact of market shocks, such as strikes, to inform purchase decisions for national stocks. However, this program will not predict natural disasters or specific market events.
However, this program can confuse the market structure that has existed for hundreds of years. Institutions like LME have issued a statement stating that their prices are based on real-world transactions by market users around the world.
This program is an important step in US efforts to increase independence in production of critical minerals and mitigate national security risks related to global market price instability.