"New Form of Imperialism": Renowned U.N. Scientist on AI Boom's Huge Water, Carbon & Land Footprint

The rapid expansion of artificial intelligence is revealing a hidden environmental crisis, one that extends beyond carbon emissions to include massive water usage, land degradation, and significant energy demands. A recent report by the United Nations University Institute for Water, Environment and Health highlights the staggering scale of these impacts, warning that by 2030, the water required for AI operations could meet the needs of 1.3 billion people—roughly equivalent to the entire population of Europe. At the same time, the energy consumption of global data centers is projected to surpass that of several nations combined, placing them among the world’s top consumers of electricity. These findings underscore the urgent need to examine the environmental consequences of the AI boom, particularly as the infrastructure supporting it grows exponentially.

According to the report, titled *“Environmental Cost of AI’s Energy Use: Carbon, Water, and Land Footprints,”* the environmental burden of AI is not evenly distributed. Nearly 90% of AI computing capacity is concentrated in the United States and China, while the rest of the world—and even marginalized communities within those two countries—shoulder the majority of the costs. These include the extraction of rare earth minerals, the generation of electronic waste, and the depletion of freshwater resources. The report emphasizes that the physical infrastructure underpinning AI, such as data centers, requires vast amounts of energy and water for operation, maintenance, and cooling. As AI becomes more integrated into daily life, so too does the strain on natural resources.

The report was authored by Kaveh Madani, director of the United Nations University Institute for Water, Environment and Health, who described the current situation as a “new form of imperialism.” He explained that while many view AI as a purely digital phenomenon, its real-world effects are deeply rooted in material realities. From the mining of raw materials in developing countries to the construction of sprawling data centers, the environmental cost is immense. Moreover, the operational phase of these facilities, which includes continuous energy use and water consumption for cooling, adds another layer of complexity to the problem. Madani emphasized that these issues are not just technical challenges but also ethical ones, involving questions of equity and responsibility.

Despite the warnings from the UN report, some major tech companies are attempting to mitigate public concerns by highlighting improvements in resource efficiency. For instance, Amazon recently announced that its data centers are seven times more water-efficient than the industry average, and it claims to be 75% of the way toward its goal of replenishing more water into communities than it consumes by 2030. The company attributes this progress to advancements in cooling technologies, such as free-air cooling, which minimizes reliance on water. However, critics argue that such comparisons to other industries, like agriculture, may not fully address the specific concerns of communities affected by the presence of large-scale data centers.

Meanwhile, the placement of new data centers in drought-prone regions raises further alarm. According to reports, many of the upcoming data center projects in the United States are being planned for areas already suffering from severe water shortages. This trend highlights a growing tension between technological advancement and environmental sustainability, particularly in regions where water scarcity is already a pressing issue. While companies like Amazon and Google continue to invest in more efficient cooling solutions, the sheer scale of AI infrastructure growth remains a challenge that may outpace these innovations.

As the debate over the environmental impact of AI continues, stakeholders across the globe are grappling with the implications of this rapidly evolving landscape. Governments, corporations, and environmental organizations are beginning to recognize the need for comprehensive strategies that balance technological progress with ecological preservation. Whether these efforts will succeed in curbing the environmental toll of the AI boom remains uncertain, but the urgency of addressing these challenges is clear.