Data Centers, Minerais Críticos, Energia e Geopolítica

Artificial Intelligence (AI) has expanded significantly in recent years, permeating various sectors of the economy and daily lives. However, this rapid adoption requires an analysis of the underlying trade-offs associated with its operation, which are often unknown to the public. Based on an analysis of data extracted from academic articles, technical reports, data repositories, and government documents, this article explores the physical, energy, and geopolitical dimensions underpinning AI. Despite often being perceived as immaterial, AI relies on a vast and complex physical infrastructure, supported by data centers that house thousands of pieces of equipment manufactured from a wide range of minerals and metals, many of which are classified as critical. Currently, approximately 12,000 data centers are in operation worldwide, including 992 hyperscale facilities that cover areas of thousands of square meters. The short life cycle of data center equipment, combined with inadequate disposal, removes valuable metals from the supply chain, intensifying mineral extraction and exacerbating socio-environmental impacts. Meanwhile, the competition between the United States and China for control over critical minerals and leadership in AI technologies has heightened geopolitical tensions, with mutual restrictions on the export of advanced technologies and essential minerals. Another key aspect is the high energy consumption of AI applications: in the United States, data centers already account for about 4% of national electricity consumption, with projections reaching 9.1% by 2030. Although major technology companies invest in renewable energy sources, such as solar and wind, to meet this growing demand, these sources also require significant volumes of critical minerals. This set of factors highlights the complex interconnection between Artificial Intelligence, Data Centers, Critical Minerals, Energy, and Geopolitics

Big Data and Business Intelligence · Chemistry · Competitive and Knowledge Intelligence · Environmental Science · Materials Science

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