NAIROBI, Kenya – As the world struggles with the escalating climate crisis, significant investments are being made in technology to drive solutions.
Scientists and technologists worldwide are at the forefront, advocating for breakthroughs in climate adaptation and mitigation.
Recent years have shown promising progress, particularly in weather forecasting and industrial decarbonization, suggesting a hopeful future driven by innovation.
Key Developments and AI’s Role
Despite historical underestimations of technological progress, breakthroughs alone cannot resolve the climate crisis.
The real impact arises when these advancements transition from laboratories to real-world applications.
This necessitates a focus on practical results and the later stages of the innovation cycle, such as product prototyping, localization, and user engagement.
AI, particularly Generative AI (GenAI), has expanded the scope of what is achievable in climate technology.
AI is poised to make a significant difference in three pivotal areas:
First, it will help organize earth data and down-scale models. Earth science faces challenges with complex systems and unstructured data from various observational methods.
AI is essential in organizing this vast data for local applications. Platforms like Google’s Earth Engine integrate satellite imagery and geospatial data with machine learning algorithms, transforming raw data into actionable insights.
AI’s ability to down-scale global models for specific local environments, such as wildfire predictions, is crucial for operationalizing extensive observational data, especially in data-scarce regions.
Secondly, AI will help translate climate models into simple language. Climate models are complex and often difficult for non-specialists to understand.
GenAI, powered by large language models (LLMs), can revolutionize this by providing interfaces that translate intricate models into simple, conversational language.
This approach would allow business leaders, politicians, and citizens to access and comprehend critical climate data, fostering broader engagement and trust in climate projections.
Additionally, AI will help accelerate technology prototyping. AI is transforming R&D across scientific domains, including climate change.
It shortens the deep tech cycle from research to prototype, which is vital as the world nears critical warming thresholds.
In materials science, AI accelerates the discovery and design of essential materials for climate mitigation and adaptation.
By predicting material properties through learned relationships, AI reduces the time and cost associated with traditional methods.
The Need for an Ecosystem Approach
The rapid development of AI technology does not automatically translate to swift application.
The climate crisis demands practical tools and use cases, necessitating a comprehensive ecosystem approach.
This includes multi-stakeholder participation, open data sharing, and pre-competitive collaboration, as seen in successful past initiatives like the development of an open-source operating system and mapping the human genome.
The World Economic Forum’s Tech for Climate Adaptation Initiative exemplifies this approach, bringing together technology companies, startups, academia, government, and other stakeholders.
The initiative’s latest project, the Action Toolkit, offers guidance on leveraging AI and advanced technologies for climate-related activities.
