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The Hidden Environmental Cost of AI: Data Centres' Surging Energy and Water Consumption

 In recent years, artificial intelligence (AI) has become an integral part of our daily lives, powering everything from smart assistants to complex data analysis. However, as AI technologies continue to advance and proliferate, a concerning trend has emerged: the rapidly increasing energy and water consumption of data centres that support these systems.

The Power Hunger of AI

According to the International Energy Agency (IEA), global data centre electricity demand is projected to more than double between 2022 and 2026, largely due to the growth of AI. In 2022, data centres consumed approximately 460 terawatt-hours (TWh) globally, and this figure is expected to exceed 1,000 TWh by 2026. To put this into perspective, that's equivalent to the entire electricity consumption of Japan.

The energy intensity of AI-related queries is particularly striking. While a typical Google search uses about 0.3 watt-hours (Wh), a query using ChatGPT requires around 2.9 Wh - nearly ten times more energy. This difference highlights the substantial energy demands of AI systems compared to traditional computing tasks.

In the United States, the impact is even more pronounced. The Electric Power Research Institute (EPRI) estimates that data centres could consume between 4.6% and 9.1% of US electricity by 2030, up from the current 4%. This significant increase raises concerns about the strain on power grids and the potential need for expanded infrastructure.

Thirsty Data Centres

Energy isn't the only resource being consumed at an alarming rate. Data centres also require substantial amounts of water for cooling systems. In Goodyear, Arizona, for example, Microsoft's data centres are projected to consume over 50 million gallons of drinking water annually. This heavy water usage is particularly concerning in regions already facing water scarcity issues.

Environmental and Social Consequences

The surge in data centre resource consumption has far-reaching implications:

  1. Climate Goals: Despite pledges to run on carbon-free energy, tech giants like Google and Microsoft have seen increased greenhouse gas emissions due to their AI pursuits. This trend poses challenges for companies striving to meet their climate commitments.
  2. Local Impact: Communities are beginning to push back against data centre expansion. In Dublin, Ireland, there is a de facto moratorium on new data centres due to their significant energy consumption.
  3. Infrastructure Strain: The growing demand for data centre capacity is putting pressure on local power grids and water supplies, potentially affecting access for other users.
  4. Economic Implications: The need for increased power infrastructure will lead to financial burdens on taxpayers for future power lines and grid upgrades. Of course there is no guarantee that the increased productivity, should it accrue, from the AI deployments will be reflected in wage growth, on the contrary it is far more likely to increase inequalities.  
Further reading:
https://www.tandfonline.com/doi/abs/10.1080/00213624.2024.2344434
https://www.aeaweb.org/conference/2024/program/paper/5NaKAYsd
https://www.nber.org/system/files/chapters/c14030/c14030.pdf
https://www.sciencedirect.com/topics/economics-econometrics-and-finance/heterodox-economics
https://www.chathamhouse.org/2018/06/artificial-intelligence-and-international-affairs/4-economic-implications-artificial
https://jacobin.com/2024/06/ai-data-center-energy-usage-environment
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