The global rush to artificial intelligence (AI) technology will require almost as much energy by the end of this decade as Japan uses today, with a predicted quadrupling in power consumption by 2030.
The global rush to artificial intelligence (AI) technology will require almost as much energy by the end of this decade as Japan uses today. However, only about half of the demand is likely to be met from renewable sources.
Harnessing the Power of AI for Energy Efficiency
Harnessing AI can make it easier to design electricity grids to take more renewable energy. Most grids were designed for centralised fossil fuel power stations that produce reliable levels of electricity. With ‘AI,’ these grids need to be redesigned to balance demand when more of the supply comes from intermittent and unpredictable sources, such as wind and solar power.
Finding efficiencies within energy systems and in industrial processes could also become easier with AI. Huge opportunities to increase efficiency are missed because it is harder for companies to change their processes than to carry on with wasteful practices. AI could assist with new technologies like driverless vehicles or detecting threats to vital infrastructure, which could offset some of the massive demands that AI will place on energy systems.
The Double-Edged Nature of AI’s Energy Impact
AI has the potential to reverse all the gains made in recent years in advanced economies to reduce their energy use, mainly through efficiencies. However, this rapid increase in AI also means companies will seek the most readily available energy – which could come from gas plants or coal-fired power stations being given a new lease on life.
Artificial intelligence (AI) systems require significant amounts of electricity to operate, contributing to greenhouse gas emissions and energy consumption.
According to a study by the Natural Resources Defense Council, data centers used for AI processing account for up to 1% of global electricity demand.
Additionally, AI algorithms often involve complex computations that consume substantial energy resources.
To mitigate this impact, researchers are exploring more energy-efficient AI architectures and developing techniques for reducing computational requirements.
The Environmental and Social Costs of AI Datacentres
The rapid growth of AI datacentres is expected to result in massive demands on energy systems, with global electricity demand more than doubling by 2030. One datacentre today consumes as much electricity as 100,000 households, but some of those currently under construction will require 20 times more.
AI datacentres are specialized facilities designed to support artificial intelligence and machine learning workloads.
They typically feature high-performance computing equipment, advanced cooling systems, and high-bandwidth networking infrastructure.
According to a report by MarketsandMarkets, the global AI datacentre market is expected to grow from $3.4 billion in 2020 to $13.8 billion by 2025.
This growth is driven by increasing demand for cloud-based services and the need for businesses to process large amounts of data.
Using vast quantities of fresh water for cooling their computers, many AI datacentres are also sucking water from some of the world’s driest areas, an investigation revealed. This raises concerns about the environmental and social costs of the rapid adoption of AI technology.
Artificial Intelligence (AI) relies heavily on complex algorithms and computations, which require significant amounts of energy.
According to a study by the Natural Resources Defense Council, data centres consume approximately 1.3% of global electricity production.
Moreover, water is often used as a cooling agent in these facilities, with some estimates suggesting that data centre water consumption can be as high as 12 gallons per hour.
This raises concerns about the environmental impact and resource efficiency of AI infrastructure.
A Call for Greater Regulation
Claude Turmes, a former Green MEP and energy minister for Luxembourg, accused the IEA of painting too rosy a picture and failing to spell out harsh truths to policymakers. He said that governments needed much more help to avoid the pitfalls of AI and new mega datacentres on the energy system.
While harnessing the power of AI can make it easier to design electricity grids to take more renewable energy, it is crucial for governments to provide greater direction and regulation to mitigate the negative impacts of AI on the environment.
- theguardian.com | Energy demands from AI datacentres to quadruple by 2030, says report
