AI systems destroy the environment — produce devastating greenhouse gases

Artificial intelligence is not limited to entertaining chatbots: increasingly effective programs trained with machine learning have become integral to uses ranging from smartphone GPS navigators to the algorithms that govern social media. But as AI’s popularity keeps rising, more researchers and experts are noting the environmental cost. Training and running an AI system requires a great deal of computing power and electricity, and the resulting carbon dioxide emissions are one way AI affects the climate. But its environmental impact goes well beyond its carbon footprint.

“It is important for us to recognize the CO2 emissions of some of these large AI systems especially,” says Jesse Dodge, a research scientist at the Allen Institute for AI in Seattle. He adds, however, that “the impact of AI systems in general is going to be from the applications they’re built for, not necessarily the cost of training.”

The exact effect that AI will have on the climate crisis is difficult to calculate, even if experts focus only on the amount of greenhouse gases it emits. That’s because different types of AI—such as a machine learning model that spots trends in research data, a vision program that helps self-driving cars avoid obstacles or a large language model (LLM) that enables a chatbot to converse—all require different quantities of computing power to train and run. For example, when OpenAI trained its LLM called GPT-3, that work produced the equivalent of around 500 tons of carbon dioxide. Simpler models, though, produce minimal emissions. Further complicating the matter, there’s a lack of transparency from many AI companies, Dodge says. That makes it even more complicated to understand their models’ impact—when they are examined only through an emissions lens.

This is one reason experts increasingly recommend treating AI’s emissions as only one aspect of its climate footprint. David Rolnick, a computer scientist at McGill University, likens AI to a hammer: “The primary impact of a hammer is what is being hammered,” he says, “not what is in the hammer.” Just as the tool can smash things to bits or pound in nails to build a house, artificial intelligence can hurt or help the environment.

Take the fossil-fuel industry. In 2019 Microsoft announced a new partnership with ExxonMobil and stated that the company would use Microsoft’s cloud-computing platform Azure. The oil giant claimed that by using the technology—which relies on AI for certain tasks such as performance analysis—it could optimize mining operations and, by 2025, increase production by 50,000 oil-equivalent barrels per day. (An oil-equivalent barrel is a term used to compare different fuel sources—it’s a unit roughly equal to the energy produced by burning one barrel of crude oil.) In this case, Microsoft’s AI is directly used to add more fossil fuels, which will release greenhouse gases when burned, to the market.