The Yuan requests your support! Our content will now be available free of charge for all registered subscribers, consistent with our mission to make AI a human commons accessible to all. We are therefore requesting donations from our readers so we may continue bringing you insightful reportage of this awesome technology that is sweeping the world. Donate now
Green AI Needs Free-Range ‘Data Commons’
By Geoff Mulgan  |  Nov 03, 2021
Green AI Needs Free-Range ‘Data Commons’
Image courtesy of and under license from
Climate change and tackling this crisis is an ongoing debate, whether in discussions at the dinner table, as highlighted in the media, or discoursed upon by global leaders. But one thing is clear: habits need to change to tackle the climate emergency. Geoff Mulgan discusses the role of Big Data and artificial intelligence in building a sustainable world for the future and argues that it will need free access to data to realize its potential in this regard.

LONDON – Long before the real-world effects of climate change became so abundantly clear, data already painted a bleak picture of the scale of the problem.

For decades, carefully collected data on weather patterns and sea temperatures were fed into models that analyzed, predicted, and explained the effects of human activities on climate. Now the alarming answer has emerged, and one of the biggest questions of the next few decades will be how data-driven approaches can overcome the climate crisis.

Data and technologies like artificial intelligence (AI) are expected to serve a critical function. Yet that will only happen if major changes occur in data management. A move away from the commercial proprietary models that currently predominate in large, developed economies will have to be made. While the digital world might seem a climate-friendly one - better to Zoom to work than to drive - digital and Internet activity already accounts for around 3.7 percent of total greenhouse-gas (GHG) emissions, which is about the same as air travel. In the United States, data centers devour about 2 percent of total electricity use.

The figures for AI are much worse. Training a machine learning (ML) algorithm emits 284,000 kilograms of carbon dioxide - five times the lifetime fuel use of the average car, and 60 times more than a transatlantic flight, per one estimate. The rapid growth of AI means these emissions are set to skyrocket. Blockchain, the technology behind Bitcoin, is perhaps the worst offender. On its own, Bitcoin mining - the computing process used to verify transactions - leaves a carbon footprint roughly equal to New Zealand’s.

Fortunately, ways that AI use can cut carbon dioxide (CO2) emissions are legion, with the biggest opportunities in buildings, electricity, transport, and farming. The electricity sector, blamed for around one-third of GHG emissions, has ad

The content herein is subject to copyright by Project Syndicate. All rights reserved. The content of the services is owned or licensed to The Yuan. The copying or storing of any content for anything other than personal use is expressly prohibited without prior written permission from The Yuan, or the copyright holder identified in the copyright notice contained in the content.
Continue reading
Sign up now to read this story for free.
- or -
Continue with Linkedin Continue with Google
Share your thoughts.
The Yuan wants to hear your voice. We welcome your on-topic commentary, critique, and expertise. All comments are moderated for civility.