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Power-hungry AI hurts climate goals

2024-09-20
| Policy Research and Advocacy Team, Friends of the Earth (HK)



"Write an article about the impacts of the AI boom on climate progress”—in recent years, artificial intelligence (AI) has become increasingly entrenched in many aspects of our lives. This ranges from everyday use like ChatGPT for writing support or Midjourney for image generation to the more technical applications in medical imaging analysis and weather forecasting. In some of our past articles, we have also covered how AI can provide solutions to environmental issues, such as smoothening traffic flows and optimising grid stability.[1]


AI-generated images can replace the need for stock photos, but getting the ‘right’ image can be costly (Image source: WhatTheyThink)

The AI boom is bringing in convenience and productivity; the demand for faster and greater computation power is however coming at a huge cost to the environment, as running data centres to process all that digital information takes a lot of electricity. What you might consider a simple request on ChatGPT for example uses ten times as much electricity as a web search.[2] Making one AI-generated image could have charged your smartphone half-full.[3] This adds up when you have millions to billions of users making requests every day.

Newer AI models demand more computing power, and consequently more energy (Image source: The Economist)

In Google’s latest environmental report, it points to AI for the 48% growth in greenhouse gas emissions since 2019, and for setting back the tech company’s 2030 net-zero goal.[4]Microsoft also saw emissions rose by 30% from 2020 in its race to be an AI leader.[5] The International Energy Agency predicts by 2026, electricity demand will double for data centres.[6]More specifically, the AI industry alone will use ten times as much electricity compared to now.

Electricity is not the only concern; to keep servers cool and running at peak efficiency, data centres are also very thirsty. In the U.S., data centres rank among the top 10 water-consuming industries.[7]Closer to home, research suggests data centres in China consume 1.3 billion cubic metres of water annually,[8]and doubling by 2030, as AI becomes more commonplace.[9]Paired with climate change, this is driving conflicts with local communities in water-stressed regions.[10]

Data centre operators like arid regions for their abundance of low-carbon energy, but water demands put them in conflict with local communities (Image source: Jim Todd/Reuters)

With its incredible positive potential, AI is here to stay. OpenAI has already announced it is developing a GPT-4 successor.[11]As newer, larger generative models are expected to come with increasingly larger environmental footprints, experts have called on data centre operators to decarbonise operations by investing in low-carbon energy. The use of massive ‘hyperscale’ data centres can also enhance energy efficiency by consolidating small data centres into a centralised facility.[12]Google has applied load shifting techniques to data centre operations, shifting computing load to align with times when low-carbon energy is plentiful.[13]

The use of AI is unlocking new potential, but its hunger for electricity is also making it harder for the world to decarbonise and meet climate goals. As these technologies continue to mature and popularise, developers must make sure their benefits and climate and environmental impacts are balanced.

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