Introduction
Artificial Intelligence (AI) have now known to poses both
strategic advantages and risks. The investment on AI hardware and software is
gaining traction and will continue to rise as more and more companies are
undertaking AI-driven projects as means to move forward.
AI could either be a contributor to a company’s carbon
footprint or even could be a tool the to mitigate a company’s carbon emissions.
Business leaders nowadays are becoming more stringent on
their companies’ environmental issues and foresee the adoption of AI will help
to address environmental issues impacting from its operations. However,
information on the impact AI has on the environment, as well as the management
approach by the companies’ Board and Management has not been adequately
discussed.
Carbon Footprint of AI
AI systems and platforms are required to manage and process
substantial deal of data, expanding the server capacities and are dependent on
energy to cool data centres. This will directly cause the increase in energy
consumption by a company.
Based on a research by the University of Massachusetts, it
was found that training AI models to undertake Natural Language Processing
(NLP), may project 500% carbon dioxide equivalent more of an American car
lifetime emission.
Though that the finding is shocking, bear in mind that this
is based on a study for one specific AI type and not that has been commonly
adopted. Definitely, more studies on various AIs are needed for us to gauge the
environmental impact of AI.
From this research, we can see the importance to extend our
understanding on the carbon footprint of all AI categories. This would ensure
we are able to set the responsible guidelines and standards to evaluate the
environmental risks of AI before the investment made by companies to integrate
AI-based system into AI-driven projects as a norm.
The Board and Management of a company need to be aware and
take actions to include AI’s environmental impact to be included in the risk
management processes as if failure to do so may lead to reputational or even
financial impact to the company. The Board and Management should also
eventually consider to AI’s environmental impacts to be part of the operational
decision-making processes.
AI in Helping Companies to Mitigate Environmental Sustainability
Rather than focusing on high-capacity internal projects that
aim to mitigate environmental footprint, companies may opt to engage with a
data centre cloud provider for AI training and processing. A few technology
companies have began taking these initiatives. An example is Google’s public
cloud offering i.e. Google Cloud Platform. Google’s DeepMind division has developed
self-thought AIs to lower energy consumption to cool its data centres. Overall,
Google has managed to lower its data centre energy requirements by 35%. Another
option is Microsoft via Microsoft Azure also runs high-capacity data centres.
It’s also interesting to note that Microsoft has committed to be carbon
negative by 2030.
Many are also aware that AI can elevate sustainability for
various industries from agriculture, transportation, manufacturing, and many
more. Here is a list of how AI plays the net positive contributor to the
environmental sustainability:
- In
agriculture, AI can transform production by better monitoring and managing
environmental conditions and crop yields. AI can help reduce both
fertilizer and water, all while improving crop yields. Companies in this
sector include Blue River
Technology, Harvest CROO Robotics and Trace Genomics.
- In
energy, AI can use deep predictive capabilities and intelligent grid
systems to manage the demand and supply of renewable energy. By more
accurately predicting weather patterns, AI can optimize efficiency,
cutting costs, and unnecessary carbon pollution generation. Companies in
this sector include Stem, ClimaCell and Foghorn Systems.
- In
transportation, AI can help reduce traffic congestion, improve the
transport of cargo (supply chain logistics), and enable more and more
autonomous driving capability. AI will eventually help with the “last
mile” delivery problem and reduce the need for delivery vehicles. AI can
help businesses with demand forecasting, helping to reduce the amount of
transport needed. Companies in this sector include Nutomony, Nauto and Sea Machines Robotics.
- In
water resource management, AI can help reduce or eliminate waste while
lowering costs and lessening environmental impact. AI-driven localized
weather forecasting will help reduce water usage. Companies in this sector
include Innovyze, Kurita Water Industries and Plutoshift.
- In
manufacturing, AI can help reduce waste and energy use in production
facilities. Robotics can enable better precision. AI can design more
efficient systems. Companies in this sector include Drishti, Cognex Corp and Spark Cognition.
- In
facilities management, AI can help recycle heat within buildings and
maximize the efficiency of heating and cooling. AI can help optimize
energy use in buildings by tracking the number of people in a room or
predicting the availability of renewable energy sources. Companies in this
sector include Aegis AI, IC Realtime and IBM’s Tririga.
- In
materials science, AI can help researchers find new materials for solar
panels, for turning heat back into useful electricity and to help find
absorbent materials as components of CO2 scrubbers (taking CO2 out of the
atmosphere). Companies in this sector include Citrine, Matsci AI and Ansys.
Conclusion
Though there are plenty of opportunities and evidences that
AI adoption facilitate companies to improve its environmental sustainability,
it is important for companies to be aware that AI has also the potential to
produce significant carbon emissions, and also has the potential to offset or
reduce those carbon emissions. Companies need to understand how this can affect
the operations and financial performance. As companies are pressed to be more
transparent in managing its sustainability issues, companies would also need to
monitor and disclose on its strategy and performance related to AI and its
impacts, thus questions on its effectiveness to mitigate carbon emissions as
well as threats imposed on the environment, would also likely to be asked by
the stakeholders.
All views and opinions expressed on this site are by the
author and do not represent any particular entity or organisation
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