Artificial intelligence conjures fears of job loss and privacy concerns — not to mention sci-fi dystopias. But machine learning can also help us save energy and make renewables better.
Artificial intelligence (AI) is infiltrating every corner of our lives. Video streaming services use it to learn our tastes and suggest what we might like to watch next. AIs have beaten the world’s best players in complex board games like chess and Go.
Some scientists even believe AI could one day achieve superhuman intelligence resulting in apocalyptic scenarios reminiscent of films like “The Matrix.”
As if to dispel such fears, the UN AI For Good Global Summit in Geneva later this month highlights AI applications to address the pressing problems of our time, including climate change.
Most countries aren’t cutting emissions nearly fast enough. AI could help speed things up. In particular, a field called machine learning can process colossal amounts of data to make energy systems more efficient.
To fulfil the Paris Agreement, we will have to virtually eliminate fossil-fueled energy from all sectors of the economy. This will mean networking decentralized, fluctuating renewable power generation with consumers that automatically adjust to minimize waste and balance the entire system.
Hendrik Zimmermann, a researcher into digitalization and sustainability at environmental NGO Germanwatch, says efficiently managing data on this scale is only possible with AI.
“To be able to design this system, we need digital technologies and a lot of data that have to be quickly collected and analyzed,” Zimmerann told DW. “AI or machine learning algorithms can help us manage this complexity and get to zero emissions.”
Cutting energy consumption
But digitalization comes with a host of problems, too — not least the huge amount of energy all this data processing itself consumes. Sims Witherspoon is a program manager at Deepmind, the British AI firm owned by Google’s parent company Alphabet that developed the Go-playing bot. She told DW that data centers — the huge “server farms” around the world that store users’ data — now consume 3% of global energy.
Which is why Deepmind decided to use its “general purpose learning algorithms” to reduce the energy needed to cool Google data centers by up to 40 percent.
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