How Artificial Intelligence Can Power Climate Change Strategy

How Artificial
Climate Change
Intelligence Can Power
Strategy

© 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
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Text
IntroductionIntroduction
Climate change could be much more destructive than the economic and societal
changes we just experienced with COVID-19. Artificial intelligence (AI) can help us
research, test, and discover new ways of reducing carbon emissions, create new
materials, and make operations and systems more efficient to use less energy. Here's
how AI can power a climate change strategy.
How Artificial Intelligence Can Power Climate
Change Strategy

Title
Text
IntroductionIntroduction
Slowing down climate change is an urgent matter. If we fail, our world will face a more
extensive crisis than we experienced because of the global COVID-19 pandemic. When
artificial intelligence (AI) technology helps solve a problem, problem-solving can be
done quicker, and the solution is often one that would have taken longer for humans to
discover. Could artificial intelligence power climate change strategy? Yes, and it’s already
doing so.
How Artificial Intelligence Can Power Climate
Change Strategy

AI Can Accelerate Our Response to Climate Change
There’s no time to waste: atmospheric CO2 levels are the highest ever (even with
significant drops from the stay-at-home orders for COVID-19), average sea levels are
rising (3 inches in the last 25 years alone), and 2019 was the hottest year on record for the
world's oceans. Artificial intelligence isn't a silver bullet, but it can certainly help us reduce
greenhouse gas (GHG) emissions in various ways.
According to Capgemini Research Institute modeling, AI is estimated to assist
organisations in industries from consumer products to retail to automotive and more fulfill
up to 45% of the Paris Agreement targets by 2030. AI will likely reduce GHG emissions by
16%. Here are a few of the most promising ways that artificial intelligence already is or can
impact climate change strategy:

Improve Energy Efficiency
According to the Capgemini Research Institute, artificial intelligence should improve
power efficiency by 15% in the next three to five years. Machine learning supports
efficiencies in power generation and distribution, from autonomous maintenance and leak
monitoring to route optimization and fleet management. Google’s Deepmind AI can
predict wind patterns up to 36 hours in advance to optimize wind farms.
Electricity systems create vast amounts of data. So far, energy companies aren’t leveraging
this data for learning to the extent that’s possible. Machine learning can comb through
this data to understand and forecast energy generation and demand to help suppliers
better use resources and fill in gaps with renewable resources while reducing waste. The
uses of AI for energy efficiency might start at the industry level, but use cases go down to
the household and individual levels.

Optimize Clean Energy Development
In the Amazon basin, developers of hydropower dams have typically developed one at a
time with no long-term strategy. A group led by Cornell University that included computer
scientists, researchers, and ecologists developed an AI computational model to find sites
for dams (hundreds of hydropower dams are currently proposed for the basin) that can
produce the lowest amounts of GHG emissions. The AI model revealed a more
complicated and surprising set of considerations to lower GHG emissions than had ever
been considered before.

Avoid Waste
Companies, governments, and leaders frequently deploy AI solutions to avoid waste.
Whether AI is used to reduce energy waste from buildings (accounts for one-quarter of
CO2 emissions) or understand supply and demand, a huge way AI can power climate
change strategy is to reduce waste in all forms (time, money, material, etc.)

Make Transportation More Efficient
Another quarter of global CO2 emissions is from the transportation sector. AI is already
the technology that powers autonomous vehicles, including shared cars and smart
transportation systems in some cities. Further adoption will help curtail emissions in the
future. Artificial intelligence optimizes routes for fleets, traffic signals, and more. All of
these incremental changes add up to make a significant impact on climate change.

Tools to Help Understand Carbon Footprint
They say “knowledge is power,” and when it comes to climate change mitigation, AI can
help build tools to help individuals and companies understand their carbon footprint and
what actions they can take to reduce it.

Monitor Environment
This year, there were severe weather events that caused massive destruction and loss. AI is
used and will continue to be used to enhance weather prediction and response. Changes
to complex systems such as cloud cover and ice sheet dynamics caused some recent
weather changes. Grasses, trees, and other plant life store carbon, but deforestation and
unsustainable agriculture release carbon into the air. As a result, this is a major contributor
to climate change. Satellite imagery and AI help conservationists monitor where this is
happening to create change.

Create New Low-Carbon Materials
The production of steel and cement accounts for 9% of global GHG emissions. If AI could
develop new materials with similar properties but with a smaller carbon footprint, it could
help slow climate change. Artificial intelligence supports scientists by making the process
of mixing various chemical compounds into combinations never tested before much faster
and easier.

Doesn’t AI Have a Carbon Footprint?
The appeal of AI to mitigate climate change was questioned after a report released by the
University of Massachusetts at Amherst estimated the power required to train a neural
network was approximately five times the average U.S. car's lifetime emissions (including
its manufacturing). Yes, artificial intelligence does have a carbon footprint, and it's quite
severe when the model is developed.
Researchers are making progress in reducing the power required to train AI models. The
adoption of AI server farms powered by renewable resources, development of AI once-
for-all neural networks, and more are ways researchers reduce AI's carbon footprint. In the
meantime, when considering AI's carbon footprint, the tremendous value of AI, and the
real-world outcomes it can have on reducing carbon emissions need to be considered as
well. Some of those downstream offsets can counterbalance the emissions created when
the model is trained.

Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2020 Bernard Marr , Bernard Marr & Co. All rights reserved© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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How Artificial Intelligence Can Power Climate Change Strategy

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