The report “Environmental Cost of AI's Energy Use: Carbon, Water and Land Footprints” was released by the United Nations University Institute for Water, Environment and Health (UNU-INWEH) on its 30th anniversary.
- UNU-INWEH is one of 13 institutes comprising the United Nations University (UNU), the academic arm of UN and is headquareted in Ontario, Canada.
Environmental Cost of AI
- Electricity: By 2030, global data centers powering AI are projected to consume 945 Terawatt-hours (TWh) of electricity.
- Carbon Emissions: Producing that much electricity would have a carbon footprint of 399 million tonnes CO2e, requiring 6.7 billion trees grown over 10 years to offset.
- Resource Depletion: Associated water footprint will equal the basic annual domestic water needs of all 1.3 billion people in Sub-Saharan Africa and land footprint will exceed 14,500 square kilometers.
- E-Waste Crisis: AI infrastructure could generate 2.5 million tonnes of e-waste annually by 2030, disproportionately affecting the Global South.
- The Rebound Effect (Jevons Paradox): Technological efficiency gains make AI cheaper, driving massive volume growth wiping out overall energy savings.
- Global Digital Divide: 90% of AI computing capacity is concentrated in just two countries (USA and China), shifting the environmental extraction burdens to developing nations.
Way Forward
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