AI's rapid growth threatens Big Tech's clean energy efforts

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Intelligent, responsive, and resilient computing systems are essential to meeting global climate goals, as they can help optimize energy production and use. As the world continues to use more and more energy, it is likely that we will reach net zero by mid-century. Sounds more like a pipe dream. The US Energy Information Administration (EIA) predicts that global energy consumption will continue to grow faster than efficiency gains and renewable energy installation capacities through 2050, the mid-century climate goals. It will be difficult – if not impossible – to reach without significant changes in consumer behavior and policy initiatives.

The IEA's International Energy Outlook 2023 found that “global population growth, increased regional manufacturing, and higher living standards drive growth in energy consumption outpacing growth in energy efficiency.” South, where birth rates are high and economies are growing rapidly. Currently, developing countries use much less electricity per capita than rich countries, but according to the World Economic Forum, about 85 percent of all new energy demand in the near future is expected to come from outside the developed world.

It is expected that developed countries will need to support the clean energy transition of poor countries that will have to 'leapfrog' from the usual fossil fuel-driven development paths and directly to expensive large-scale renewable energy. will have to go on building the infrastructure. Developed nations, already booming in terms of population growth and related infrastructure build-out, can then support these countries in terms of climate financing and clean energy exports.

But for the first time in a long time, developed countries' energy consumption is growing at a significant rate even as renewable energy deployment is slowing. While there is no single market trend or industry sector in the developed world that is shifting the energy consumption curve, a recent Forbes report states that it can be essentially boiled down to four key factors. is: 1) “Accelerating demand for AI power,” 2. ) “The Energy Transition and the Rush to Metals as an Asset Class,” 3) “Inelastic Retiree Demand,” and 4) “The Restructuring of Housing Supply in North America.”

Of these four main factors, the massive increase in energy demand for artificial intelligence, not to mention the staggering energy consumption of data centers as a whole, is the biggest. “Currently, the entire IT industry is responsible for about 2 percent of global CO2 emissions,” Science Alert reported last year. And it is growing at an alarming rate. Technology research and consulting firm Gartner projects that in a business-as-usual scenario, the AI ​​sector will be solely responsible for 3.5 percent of global electricity consumption by 2030. – In other words, it already uses as much energy as entire countries.

The energy demand of an increasingly AI-driven world is a runaway train of sorts. The full scope of AI's growth trajectory — as well as machine learning's potential to help pave the way for better and more efficient energy use and production — is still poorly understood. Pandora's box has just been opened. It's true that AI can be a net positive for the world's carbon footprint if we can use and regulate it properly.

Meeting global climate goals will require massive and unprecedented system change. This imperative would be impossible without intelligent, responsive, and flexible computing systems capable of rapidly recognizing, responding to, and predicting complex patterns of production and consumption. Already, AI is integral to renewable energy forecasting, smart grids, coordinating energy demand and distribution, optimizing power generation efficiency, and researching and developing new materials.

“Fundamentally, if you want to save the planet with AI, you also have to consider the environmental impact,” Sascha Lucioni, an ethics researcher at the open-source machine learning platform Hugging Face, told the Guardian last year. “It doesn't make sense to burn forests and then use AI to track deforestation.”

The growing energy needs of mining and metals exploration in the First World are also linked to decarbonization in complex and often ironic ways. Building an electric grid capable of handling the boom in utility-scale solar and wind farms, electric vehicles, and both would require large-scale manufacturing, requiring large quantities of metals and other rare earth elements. which are not yet sufficiently established. supply chain. As such, developed countries that normally don't waste their time and money on basic materials markets are looking to get into the mining game to boost their stores of key ingredients like lithium and copper. . And all these will contribute to a lot of emissions in the atmosphere in the name of reducing them. Mining currently uses between 5% and 10% of global energy.

The last two factors identified by Forbes – the static energy consumption of baby boomers and the urgent need for more housing in the United States and Canada – are increasing the rate of energy consumption and greenhouse gas emissions in developing countries. There are also major contributing factors. This is a major problem for the global stage, as the paths towards net zero were based on the assumption that energy demand in the developed world would remain relatively stable. This is also a problem for global inflation rates, which are likely to remain high. The only option for global policymakers is to immediately get serious about increasing support for new and larger clean energy projects.

By Haley Zaremba for

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