Page 29 - Turning digital technology innovation into climate action

Turning digital technology innovation into climate action

ITU’s effort is especially timely, as all these frontier technologies are to a degree interrelated,
especially in their integration with, or reliance on, the Internet of Things (IoT), Artificial Chapter 2
Intelligence (AI), 5G and Big Data. While the concept of many of today’s emerging technologies
has been around for some time, it is especially due to IoT and the wider adoption of ICTs
that it is now becoming feasible to implement them on larger scales.
Therefore, further researching and guiding the affordable and wide-scale deployment of
these ‘enabler’ and core building-block ICTs will assure further advancement and adoption
of other emerging technologies, which may help to engineer innovative climate solutions
in the areas of monitoring, adaptation and mitigation.

2.3 The Limitations of AI and ML

As mentioned in Box 2, however, limitations do remain with regard to the carbon footprint of AI and
machine learning (ML). AI and ML, like most technology, have the potential to help in the fight
28 29 30
against climate change. They can make systems more efficient (e.g. by preventing electricity loss during
transmission), enable remote sensing and automatic monitoring (e.g. pinpointing deforestation,
gathering data on buildings, and tracking personal energy use), provide fast approximations to time-
intensive simulations (e.g. climate models and energy scheduling models) and also have the potential
to lead to interpretable or causal models (e.g. for understanding weather patterns, informing policy
makers and planning for disasters).

It has been estimated, for instance, that ‘using AI for environmental applications could boost the
global economy by up to $ 5.2 trillion (USD) in 2030, a 4.4 per cent increase on the business-as-usual
scenario, while reducing GHG emissions worldwide by 4 per cent, equivalent to the 2030 annual
emissions of Australia, Canada and Japan combined.’ 31

The efficacy of ML and AI will, however, rely on bringing together several factors, including ensuring
their effective integration with other technologies and – because they require large amounts of
computing power – decarbonisation of the energy system to ensure that AI and ML can fulfil their
sustainability potential. This is imperative, as new studies are showing that typical current ML
processes can ‘emit more than 626 000 pounds of carbon dioxide equivalent (CO e) – nearly five
2
times the lifetime emissions of the average American car (and that includes the manufacture of the
car itself)’. 32
Specifically, these studies have examined ‘the model training process for natural-language processing
(NLP), the subfield of AI that focuses on teaching machines to handle human language. In the last
two years, the NLP community has reached several noteworthy performance milestones in machine

28 Rolnick, David, et al. ‘Tackling Climate Change with Machine Learning.’ ArXiv.org, Cornell University, arxiv .org/ pdf/ 1906
.05433 .pdf.
29 Scott, Mike. ‘AI Will Be A Vital Tool in Making the Global Economy More Sustainable and Efficient - PwC.’ Forbes
Magazine, Forbes Media LLC, 23 Apr. 2019, www .forbes .com/ sites/ mikescott/ 2019/ 04/ 23/ ai -will -be -a -vital -tool -in
-making -the -global -economy -more -sustainable -and -efficient -pwc/ #573e61cb4ce7.
30 Hao, Karen. ‘Training a Single AI Model Can Emit as Much Carbon as Five Cars in Their Lifetimes.’ MIT Technology
Review, 7 Jun. 2019, www .technologyreview .com/ s/ 613630/ training -a -single -ai -model -can -emit -as -much -carbon
-as -five -cars -in -their -lifetimes/ ?utm _campaign = site _visitor .unpaid .engagement & utm _source = hs _email & utm
_medium = email & utm _content = 7 3608463 & _hsenc = p2ANqtz - -j9p83piXI m9fiL7riodfQuQX0XOkswkP4qgMHSe
_NJI3GIxGsHMPZsEsVt2YyzyC0TqVKV7Zh0by -TudcURQa5bnoKw & _hsmi = 73608464.
31 Scott, Mike. ‘AI Will Be A Vital Tool in Making the Global Economy More Sustainable and Efficient - PwC.’ Forbes, Forbes
Magazine, 23 Apr. 2019, www .forbes .com/ sites/ mikescott/ 2019/ 04/ 23/ ai -will -be -a -vital -tool -in -making -the -global
-economy -more -sustainable -and -efficient -pwc/ #573e61cb4ce7.
32 Hao, Karen. ‘Training a Single AI Model Can Emit as Much Carbon as Five Cars in Their Lifetimes.’ MIT Technology
Review, 7 Jun. 2019, www .technologyreview .com/ s/ 613630/ training -a -single -ai -model -can -emit -as -much -carbon
-as -five -cars -in -their -lifetimes/ ?utm _campaign = site _visitor .unpaid .engagement & utm _source = hs _email & utm
_medium = email & utm _content = 7 3608463 & _hsenc = p2ANqtz - -j9p83piXI m9fiL7riodfQuQX0XOkswkP4qgMHSe
_NJI3GIxGsHMPZsEsVt2YyzyC0TqVKV7Zh0by -TudcURQa5bnoKw & _hsmi = 73608464.

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