Historically, technological revolutions have brought higher carbon dioxide emissions — with the first Industrial Revolution being powered by coal and the second heavily by oil. Will artificial intelligence (AI) — the general-purpose technology of our time — do the same? The early signs are concerning. Microsoft’s carbon emissions has jumped about 30 percent since 2020 as the company invested in AI infrastructure, and Google’s are up almost 50 percent over the past five years.
However, there are two countervailing forces to consider: demand and efficiency. While demand has grown, efficiency has improved. Chips from companies like Nvidia are getting better, and the next generation is expected to be five times faster than the current one. Equally, OpenAI and other industry leaders are making their models more efficient to train and run.
Still, given the surging demand for AI, energy consumption worldwide could still grow, even as models become more efficient. What really matters is emissions, and to project those, we need to know how the electricity to power AI data centers would be generated, and how AI would impact carbon-intensive industries.
According to the International Energy Agency, data centers accounted for roughly 1 to 1.5 percent of electricity use worldwide last year, and this share is sure to grow in the short term. Microsoft, Google and Meta nearly doubled their cumulative electricity consumption from 2020 to 2022, and that was before the arrival of ChatGPT. Since then, they have only strengthened their commitments to expanding this infrastructure.
While data centers represented roughly 1 percent of energy-related carbon emissions last year, the electricity systems that power them are rapidly decarbonizing. In the US, 41 percent of electricity was produced from zero-carbon sources last year — marking a one-quarter increase over the past decade — and in Europe, the proportion is closer to 60 percent. In the US, Europe, the UK and China, renewables are the fastest-growing means of producing electricity.
At the same time, Goldman Sachs expects data center energy demand to grow 15 percent per year until 2030, with AI accounting for one-fifth of that growth. Even if two-fifths of US data centers’ energy needs are met by renewable energy, AI infrastructure would emit about 26 million tonnes of additional carbon emissions annually.
But while that is a huge amount in absolute terms, it needs to be put in context. The additional emissions from AI would represent 0.4 percent of current emissions, and less than the “scope 1” (direct) emissions of any of the three biggest US airlines. Notwithstanding the breathless headlines about AI’s carbon footprint, the US’ energy system is so large that the direct impact of AI represents more of a perturbation than a systematic change.
Moreover, there is compelling evidence that AI can reduce emissions across a variety of hard-to-decarbonize sectors. Since aircraft contrails alone are responsible for about 35 percent of aviation emissions, Google and American Airlines are exploring how machine learning can be used to minimize contrail formation. The early results show that about one-sixth of aviation emissions worldwide could be avoided (more than all the current output from AI data centers in the US combined).
Similarly, food waste (which accounts for 6 percent of global emissions) can be reduced by using AI to forecast demand, manage production levels and optimize schedules across the supply chain. AI is already being used to reduce emissions from industrial processes (currently 30 percent of the global total), such as by aiding in the development of biologically inspired materials that are less reliant on fossil fuels (but still meet industries’ mechanical standards), and by reducing the cost and increasing the efficiency of material recycling. AI would also aid climate adaptation by improving weather forecasting and early-warning systems. Timely preparation has the potential to save lives and reduce economic losses.
Thus, while AI will most likely increase global energy consumption in the short term, its potential to drive down emissions across a wide range of industries is immense. We must remember that technological progress can decouple economic growth from emissions. The UK, for example, has boosted per capita GDP by almost 50 percent since 1990 while slashing domestic emissions by half. AI could be the key to accelerating this trend globally.
However, realizing AI’s full potential as a tool for decarbonization will require stronger climate policies. Putting a price on carbon and doubling down on support for clean energy would create powerful incentives for businesses to invest in AI solutions that minimize emissions and hasten the transition to a sustainable future. If we play our cards right, AI might well prove to be our ace in the hole in the fight against climate change.
Azeem Azhar, founder of Exponential View, is an executive fellow at Harvard Business School and a technology investor. Carl Benedikt Frey, associate professor of AI & Work at the Oxford Internet Institute and director of the Future of Work Program at the Oxford Martin School, is the author of The Technology Trap: Capital, Labor, and Power in the Age of Automation.
Copyright: Project Syndicate
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