INSIGHT by Tim van den Bergh Project Specialist AI & ML Platform, World Economic Forum. This article was originally published by the World Economic Forum and is part of: United Nations Climate Change Conference COP27.
〉Over the next few decades, climate change is poised to be a major business disruptor, with the potential financial impact of climate change being estimated to range in the trillions of dollars for the U.S. economy alone.
〉To adapt to this new reality, more granular climate insights need to be generated to empower stakeholders to take a more data-driven approach to climate adaptation.
〉Due to the scale of this data, as well as the complexity of climate phenomena, AI must be leveraged to enable early-warning systems and predictive modelling that is more accessible and optimises reaction times.
Despite climate mitigation efforts to keep global warming below 1.5°C, many experts expect the world to warm by 3.5°C by the turn of the next century. This ever-warming world has brought floods and wildfires and the loss of life with more disruption expected in the decades to come.
So, it is crucial to focus on climate adaptation at scale, as well as climate mitigation. We must strengthen our ability to adapt to current and expected climate events, using actionable climate insights to inform decisions. The use of artificial intelligence (AI) for its climate modelling capabilities is fundamental to this, yet we see significantly more AI innovation focused on climate mitigation, such as leveraging AI to measure and reduce emissions. This innovation gap needs to be addressed and the development of responsible AI must be accelerated to acquire actionable climate insights.
This means that governments and businesses must radically rethink their approach to climate adaptation. AI is key to this, with a recent survey by BCG posed to over 1,000 public and private sector executives, finding that 87% see AI as an important tool to fight climate change. Here’s how AI can be key to climate adaptation:
| Using AI to build climate resilience
Between 3.3 and 3.6 billion people live in areas at high risk of climate change, areas where we already see or will see a significant increase in natural disasters and this is likely to increase as the climate crisis is exacerbated. This year’s extreme weather events, such as droughts, hurricanes, wildfires and floods, have shown us that adapting our societies to the perils of climate change is a daunting task.
When modelling extreme weather events, a large number of variables must be included and AI is well situated to model for this complexity due to its ability to gather, complete and analyse large datasets. It can be leveraged for early-warning systems and long-term predictive modelling of local climate events, empowering stakeholders to take a more data-driven approach to climate adaptation. Destination Earth, led by the European Space Agency, for example, aims to create an AI-based model of the Earth to monitor and predict the interaction between climate phenomena, such as droughts and human activities. Once in place, decision-makers around the globe would have increased access to climate insights to inform their adaptation efforts.
Leveraging AI for wildfire prediction and prevention is another good example. It enables interactive mapping of high-risk areas and can track the development of fires in near real-time through fire-spread algorithms, informing optimal resource allocation and long-term strategies for sustainable forest management. As the average annual global cost of wildfires is about $50 billion, this should be welcomed as AI can make combatting wildfires more efficient and cost-effective. To support this, the World Economic Forum has started FireAId, which is working towards building real AI models and piloting them in countries such as Turkey.
These recent developments in leveraging AI for climate adaptation have the potential to make climate insights more accessible for all stakeholders. Something that is needed globally, but particularly in the Global South with less technology access and, coincidently, also the most high-risk areas. As such, AI has the potential to reduce the mismatch between adaptation needs and technology access. In support of this, more must be done to strengthen equitable access to and participation in the development of AI for climate adaptation.
| AI for business continuity in the face of climate risks
Climate change is poised to be a major business disruptor, with the potential financial impact of climate change being estimated to range in the trillions for the U.S. economy alone. Businesses will face major supply chain and production disruptions in the decades ahead. Still, only 33% of business leaders account for climate risks in their business strategies.
AI can play a vital role in predicting where these disruptions to a business might occur, detailing operational vulnerabilities because of climate change. By pulling in complex data sources in visual risk maps, business leaders can see how the complex dynamics of climate change negatively impact business assets and better withstand shocks. For instance, Esri, a leader in geographic information system (GIS) software, is utilising digital twins to model climate risks. Digital twins are digital copies of operations or physical assets. Leveraging data and AI, they can assess vulnerabilities, such as flood vulnerability, to critical business assets in near real-time. This allows for weaknesses to be addressed and pre-emptively strengthened and for preventative maintenance to be undertaken.
But, as with AI for climate adaptation for governments, the access to such AI tools for businesses needs to be critically assessed. Organizations that leverage the full potential of AI for climate adaptation are few and far between. More international collaboration is needed for the continuous development of these applications, as well as accessibility to this technology to make actionable climate adaptation insights accessible to all relevant stakeholders.
| The way forward
These are two emerging central themes where AI can be used for climate adaptation. Many other promising applications are appearing and must be accelerated, such as the use of AI to account for climate risks in financial products or the use of AI for pre-emptive humanitarian efforts.
AI for the use of climate adaptation is in its infancy, with many efforts using advanced data analytics. To leverage the true potential of AI for climate adaptation responsibly, such as the use of synthetic data and predictive modelling, critical barriers must be addressed collectively. Currently, the widespread use of AI in climate adaptation is hindered by barriers in data compatibility, access to existing and new AI and machine learning (ML) models, access to computational resources to run these complex models, technical expertise to derive actionable insights and domain and management expertise to make adequate policy decisions.
Luckily, there is an international appetite to collaboratively work on this effort and close the innovation gap to accelerate the responsible use of AI for climate adaptation at scale, reducing the risk of maladaptation. To this end, the AI and ML Platform of the World Economic Forum is exploring what role the World Economic Forum can play in accelerating the use of AI in combatting climate change. This is supported by consensus-based governance frameworks, toolkits and best practice use cases. It will demonstrate data-driven AI roadmaps and approaches to climate modelling for public and private sector institutions to address the social, economic and environmental impact of climate change.
| The views expressed in this article are those of the author alone and not the World Economic Forum.
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