Here’s How Artificial Intelligence Is Fueling Climate Change
You can think of artificial intelligence (AI) in the same way you think about cloud computing, if you think about either of them through an environmental lens: an enormous and growing source of carbon emissions, with the very real potential to choke out humans’ ability to breathe clean air long before a sentient and ornery AI goes all Skynet on us.
At the moment, data centers—the enormous rooms full of stacks and stacks of servers that juggle dank memes, fire tweets, your vitally important Google docs and all the other data that is stored somewhere other than on your phone and in your home computer—use about 2% of the world’s electricity.
Of that, servers that run AI—processing all the data and making the decisions and computations that a machine mimicking a human brain must handle in order to achieve “deep learning”—use about 0.1% of the world’s electricity, according to a recent MIT Technology Review article.
The likelihood that figure will grow, it turns out, is quite good.
Until recently, more than a few scholarly dives into AI and the electricity grid focused on how AI could make power usage or other current carbon-emission-generating pastimes smarter. Putting AI in charge of power loads over a “smart” grid would lead to greater efficiency, and maybe less electricity use overall.
Left unaccounted for in such models, however, was how much electricity AI itself would require. If (almost) everything in an “internet of things” world is connected to the internet and also able to machine-learn—your car, your delivery drone, you name it—then everything will require some kind of data storage solution. And that will require electricity.
Put in global perspective, 0.1% of the total power load is less juice than is currently used by the American legal marijuana industry, which by most guesses is using about 1% of the nation’s electricity load.
