IEEE Technology and Society Magazine - June 2020 - 41

OPINION

Sana Khareghani

Capitalizing on AI's
Potential to Help
Tackle the
Climate Crisis

he pace of technological change hits
me at least once a
week . I might be
scrolling through
Twitter or perusing an article, and
something comes along tha t
astounds. As the Head of the U.K.
government's Office for Artificial
Intelligence, I see this most often
through the application of AI technologies, as computers learn to
diagnose cancer [1], beat humans
at highly sophisticated games [2], or
solve one of the longest-standing
predicaments in the scientific community [3]. The pace of these achievements dwarfs anything we as a society are reasonably prepared for, and
fortunately many of these advances
tilt toward innovations that aim to
improve the world.
This is the promise of the Fourth
Industrial Revolution. The scale of
investment in these advances in
the past few years alone has been
immense: worldwide spending on
AI was approximately $35.8 billion in 2019, with a 44% increase
from 2018 [4]; the Big Data market
has almost doubled in size in three
years, with a total global revenue
of $49 billion in 2019 [5]; and in
the U.K., recent research estimates
that the digital sector is contributing

£4700 (U.S. $5800) every second
to the U.K. economy, accounting
for 7.7% of gross value added in
2018 [6].
The uptake of these technologies means the world is accelerating
even faster towards a future where
breakthroughs are commonplace,
and where emerging technology
shapes the world we live in. My son
is a Rubik's Cube fanatic, so you
can imagine my fascination when
researchers at OpenAI in San Francisco revealed an algorithm (through
reinforcement learning - trial and
error) capable of manipulating the
pieces of a Rubik's Cube using a single robotic hand [7]. This is no mean
feat: researchers also created environments like friction, elasticity, and
dynamics to make it as real-world as
they could, beating the dexterity of
children by years.

Digital Object Identifier 10.1109/MTS.2020.2991499
Date of current version: 18 June 2020

JUNE 2020

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IEEE TECHNOLOGY AND SOCIETY MAGAZINE

But there is an impact to these
breakthroughs that often gets
glossed over amid the excitement -
training artificial intelligence is very
energy intensive. The computing power required for the Rubik's
Cube training would have required
more than 1000 desktop computers and a dozen machines running
specialized graphics chips, crunching intensive calculations, for several months. For deep learning to
grasp something as complex as
language, models typically have to
be provided with billions of written
articles in order to understand the
meanings of words and how sentences are constructed.
We see this similarly in emerging technologies. Bitcoin, in creating
ever more complicated algorithms
to mine, currently uses more energy
than Switzerland does in a year, or

IEEE Technology and Society Magazine - June 2020

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