IEEE Technology and Society Magazine - June 2020 - 44

a lack of commercial incentive to
obtain or share data.
The Office for AI has been working with the Open Data Institute to
explore how access to data can be
improved, through Data Trusts [37].
By demonstrating the benefits of
sharing data - including non-personal data - such as our pilot projects in illegal wildlife trade and food
waste, we may be able to start building thriving AI and data technology
ecosystems that can step up to the
challenge of climate change.
Tackling this multifaceted challenge requires drawing on a huge
range of disciplines and skills, which

By demonstrating the benefits
of sharing data, we may be able
to start building thriving AI and
data technology ecosystems that
can step up to the challenge of
climate change.
means both institutional expertise
and human skills. The most successful in this pursuit will need to
understand the promise of emerging
technologies in reaching net zero, but
also in understanding the language
around these technologies. The pool
of individuals is currently too small
and not representative of our diverse
society to develop the correct technology at scale to attack this problem.
In the U.K. this is reflected by
an imbalance of supply to meet the
demand for AI technologies. The
Office for AI has sought to address
this by developing a talent and skills
pipeline to enable as many people
as possible to benefit from the
opportunities presented by AI [38].

gas (GHG) emissions [42], but this
should not discount the system-wide
importance of applying technological solutions to a wide range of sectors with the intent to help mitigate
and adapt.
The U.K. energy system, much
like others around the world, is
transitioning from being centralized and fossil-fuel dominated, to
being increasingly decentralized
and renewables dominated, and
with new demands from transport
and heat. As this happens, there is
an increasing need to optimize and
manage the many complex constituents of the energy system, including
renewables, electric vehicle charging, and battery storage. AI will not
only be a useful tool in optimizing
and managing future electricity
systems, but will also be essential
in managing increased complexity, whether in relation to solar and
wind forecasting, grid management,
battery management, or analyzing
smart meter data.
Perhaps one of the most important roles AI could play in this space
is in optimizing electricity dispatch.
Electricity dispatch is the short-term
allocation of the optimal amount of
generated electricity that is required
to meet the demand of the overall
system, and to do so at the lowest cost. All else being equal, systems that have large amounts of
intelligence - and the capacity to
-
update quickly in light of real-world
conditions - are systems that are a
lot more efficient.
In contrast, the more uncertainty
grid operators have in their forecast
of electricity supply or demand, the
more backup power, typically provided by fossil fuel generation, is
required. AI, alongside improved
data collection, can much more
closely forecast in real time the
right balance of renewables supply
with demand, to optimize the role
of renewables on the system [43].

The U.K. government is also
supporting new U.K. Research and
Innovation Centers for Doctoral
Training in AI [39], which will train
200 new Ph.D. students per year
until 2025 with a multi-disciplinary
approach, and two of these Centers
are focused explicitly on AI and sustainability issues.
On its own, this won't be enough
to draw the best and brightest into
the net zero challenge, but once
these foundations are enabled, the
opportunity to plug into this challenge is what comes next. But we
cannot afford to wait for long. The
Intergovernmental Panel on Climate
Change has warned that our
current trajectory of decarbonization means that the
"safe limit" of 2°C will have
been breached by 2036
[40]. Though there has been
political and technological
progress, the rate of global
decarbonization required is
increasing each year, which
puts in sharp focus the
need to bring every technological solution to bear on
accelerating the decarbonization of the economy.

Transformative Potential of AI
AI technologies provide a host of
applications to mitigate and adapt
to the issue of climate change, and
many qualified individuals, including
Luccionni et al. in this issue, have
opined on this [41]. Some estimates
have put the potential of applying AI
to clean growth as bullish: globally,
AI can help deliver a reduction in
GHG emissions of up to 4% by
2030 with a concurrent uplift of
4.4% to global GDP [42].
In order to illustrate how AI can
be used to transform our sectors,
energy is perhaps the most practical lens through which to focus. AI
applications in energy provide the
largest global impact on greenhouse
IEEE TECHNOLOGY AND SOCIETY MAGAZINE

∕

JUNE 2020

IEEE Technology and Society Magazine - June 2020

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - June 2020