While there are worries about energy use and potential job losses associated with AI in some sectors, the optimists are quite positive, even evangelical about the future. For example, Carl Ennis, Siemens CEO for UK and Ireland, says that ‘the potential for AI to lead the green technological revolution is especially relevant when it comes to enabling a more resilient and responsive energy system. This is essential if UK businesses are to play their part in the transition towards net zero and a greener future’. In effect he says ‘AI turns traditional, reactive grid management into a proactive, intelligent system that can respond faster and more efficiently to the evolving demands of the UK’s low-carbon energy transition.’
And beyond that, he says the ability provided by advanced AI to conduct extended research and development before concepts are taken into the real world could have a transformative impact on the UK’s energy system, and beyond, potentially into ‘multiple areas of business and industry that require intricate test and design processes’. He also says that ‘it will drive the design of low-carbon buildings, simulate entire microgrids and test new technologies in a risk-free, low-cost environment. It opens the doors to rapid prototyping, cutting material waste and dramatically speeding up innovation cycles.’
Overall he notes, efforts to decarbonise operations, infrastructure and supply chains while building greater efficiency and resilience ‘are among the most pressing priorities for UK businesses’, and he says that AI and digitalisation are vital for economic and ecological survival: ‘ultimately, those who adopt digitalisation will gain a strategic advantage in the markets they operate in – not just by reducing environmental impact, but by becoming more agile, cost-effective and resilient in the face of the increasing need to operate sustainably.’
In a UNESCO report, Stefania Giannini is also very keen on AI. Indeed, she sees the digital & green transitions, so often at loggerheads, as in fact able to support each other, with AI-driven simulation tools aligning with the evolving needs of the green energy sector. For example, she says ‘digital technology is instrumental in driving research and innovation to promote green energy solutions. The technology optimizes renewable energy sources like solar and wind, advances climate adaptation strategies, supports sustainable agriculture & enhances waste management, among many other uses’.
She looks to education as providing the key link. ‘Educational & research institutions rightly see the digital revolution as a catalyst to help societies practice sustainability and begin rebalancing our relationship with the natural world. AI and machine learning are already promoting breakthroughs in renewable energy research. As one example, AI-driven predictive models are being used to enhance solar and wind power generation. The models improve the prediction of weather patterns, allowing solar panels and wind turbines to optimize energy generation by anticipating and adjusting to slight variations in sunlight and wind speed’.
By incorporating AI driven developments like this into educational programmes, she says ‘universities and schools are training students and researchers to build the technologies that will underlie a green energy revolution’. She also sees AI as playing ‘an increasingly important role in climate adaptation strategies and helping communities respond to climate change. AI-powered systems can model and anticipate extreme weather events, providing early warning systems that save lives and minimize economic loss,’ with Sustainable agriculture being a key domain where AI and digital technologies are helping to power a green transition.
In all this she says ‘Universities & research institutions serve as incubators and testing grounds for the innovations that are adding momentum to the green energy transition. Numerous universities have established research centres dedicated to green energy & climate solutions. These centres are partnering with governments, businesses and non-governmental organizations to develop technologies that will reduce dependence on fossil fuels for energy & heating. But she says ‘the development and deployment of AI in the context of green energy research and innovation must be guided by ethical considerations and climate justice principles. Just as AI can enhance green energy production, it can also increase production of non-green energy, by introducing efficiencies in fossil fuel extraction and use. Higher education & research institutions have an obligation to help students understand how to develop and use AI responsibly, and this work should be guided by national or international frameworks, such as the 2021 UNESCO recommendations on the Ethics of Artificial Intelligence.’
She adds that ‘A critical outlook on technology and the ability to harness it for sustainable development, human rights, inclusion and justice are essential competencies as we look to the future. Global citizenship education equips learners with the knowledge, skills, attitudes and values needed to address complex global challenges. In the digital age, this includes the ability to critically assess the role of technology in society and use digital tools to move communities and the world towards greater sustainability’. Although she rather ruined it all for me by mentioning nuclear technology as an example of a progressive option! Perhaps she saw that as an answer to the burgeoning energy needs of AI, although some say that can be reduced with better technology.
While Giannini’s approach overall is positive and welcome, and the enthusiasm shown by Carl Ennis for AI is infectious, there do still seem to be some unresolved eco-issues and an urgent need for the careful regulation and assessment of AI, although, if you are like Trump, maybe all that can be ignored. At least until it gets too noticeable and costly- even possibly outweighing any benefits. But for the moment, with AI technology developing fast, we don’t know what the balance will be, and while some think that current projections for AI energy use are overstated, others think that it is vital to look critically at the potential impacts of AI.
*I am current working with OU colleague Terry Cook on a paper looking at the interaction between AI and green energy development. There may still be some conflicts but, as Giannini says, AI can be used to optimize smart energy grids and ‘balance electricity supply and demand dynamically’, and flexible system management to avoid costly curtailment losses is something that is going to become crucial as renewables develop. Watch this space!
But not just yet - I’m taking a summer break for a bit now.
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