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ISSN 2753-7757 (Online)

AI can’t solve global warming, but it can accelerate sustainability


4 min read

Head and shoulders picture of Ethan Faghani, CEO and founding partner, Cetasol Photo: Cetasol
Ethan Faghani, CEO and founding partner, Cetasol

Photo: Cetasol

As the window of time left to prevent global warming exceeding 1.5℃ is narrowing every day, we need to look at every solution at our disposal. Ethan Faghani, CEO and founding partner of Cetasol, discusses AI’s role in the energy transition and how it is reducing emissions in the commercial marine sector.

Artificial intelligence (AI) is not the solution to global warming. However, it is one of the most powerful tools that humans have ever developed, and it is progressing rapidly. If we disregard the interesting technology aspects of AI, in economic terms it simply means ‘affordable brain power’.


But what does that mean for businesses? Basically, everything that is mass produced or has the potential for high profitability per unit and shows optimum predictability will benefit from AI-powered, game changing solutions. Solutions that, though the ideas might have existed for a long time, have not been possible to implement from an economic point of view.


This will gradually change in future and AI will become more and more generic so the solutions can be applied even to those problems with less volume, less profitability and less predictability.


How we will (hopefully) resolve global warming 
To understand the role of AI in relation to global warming, we need to have a good picture of how we are solving the issue at the macro level.


I think our efforts will be directed in a few directions:

• Replace the source of energy from finite to sustainable. This basically means changing from fossil fuels to renewable sources. Although this seems to be the main factor in achieving net zero, due to slow progress in transitioning to renewable energies and high inefficiencies from the source of energy to the consumer, other factors mentioned below will be almost as important as renewable sources.
• Move all small energy conversion units into one power plant. For example, every car in the world is a mini energy conversion system and energy conversion in an uncontrolled environment has a much bigger risk of energy waste. With electrification, we are converting the mini energy conversion units to energy consumption units. Giant conversion units at power generation sites will have more potential for energy efficiency since we can afford to use complex solutions to increase the whole system’s efficiency.
• More energy efficient units. Part of our efforts should be focused on controlling energy demand. This will be as important as moving towards renewable sources of energy in the short term. It will also minimise the total expected investment over the long term. Controlling the demand of energy means creating efficient units, systems and processes with help from intelligent support systems – human-machine layers made using AI.


The future of sustainability in transport
The role of AI in sustainability will be an important ‘accelerator’ for the energy transition. Since global warming is a time sensitive issue, accelerators can arguably be almost as important as the final solution(s) in the short term.


Data science can support operational owners in having a better understanding of their sources of emissions, magnitudes and variabilities, and by extension, their areas of improvement. This basically means that AI can provide automated ‘actionable insights’ in the form of decision support for humans.


AI and Cetasol in the marine sector
AI and data science in the form of an intelligent layer between user and machines is inevitable in future. These types of systems started as data visualisation tools but are already moving towards assisting with decision-making. This basically means that human-machine interactions will become more and more important and will be very different to the user experience (UX) interactions that we know today.


The main challenge in the commercial marine sector is a reluctance to embrace new technologies, slow decision-making and a lack of standards. The market remains largely untapped due to the delayed advancement in new technologies. Nevertheless, AI can have significant benefits for this sector.


For instance, Cetasol is using AI to develop decision support systems in the marine sector with iHelm (Intelligent Helm). The current platform processes large amounts of data from different sources, such as driving patterns from experienced captains, weather data, GPS positioning and ocean currents. This is used to provide real time guidance for ship captains (including navigation for minimising fuel consumption) and to highlight automated key performance indexes related to sustainability for the business owners.


Cetasol’s system is also being used to evaluate the potential for the electrification of operations. Not all operations have similar potentials for moving toward electrification and this is important for authorities supporting the sustainability journey as well as operators.


Global warming is the biggest issue that humanity has ever faced and the solution will be a complex combination of several well time-managed sub-solutions, including the use of AI. However, for it to succeed depends heavily on our ability to collaborate at a scale never seen before. The only path to sustainability is through collaborative innovation.


The views and opinions expressed in this article are strictly those of the author only and are not necessarily given or endorsed by or on behalf of the Energy Institute.