Advancing AI for Climate Action: Global Collaboration on Intelligent Decarbonisation

Task Force 4: Refuelling Growth: Clean Energy and Green Transitions 1. The Challenge Artificial Intelligence (AI) has the potential to contribute to the UN Sustainable Development Goals (SDGs). [1] The International Telecommunication Union (ITU) has identified 281 AI projects by 40 different UN entities addressing various urgent issues, including climate action (SDG 13), which is the focus of this brief. [2] Outside the UN context, an increasing number of promising studies also highlight the use of AI in achieving carbon-neutral transformation goals. Specifically, the Cambridge Centre for Advanced Research and Education in Singapore (CARES) analysed projects across sectors, demonstrating that cyber-physical systems in combination with AI offer a substantially higher potential for emissions reduction and lower costs of reducing CO 2 compared to conventional approaches. [3] As detailed in this brief, the main reason for such abatement potential relates to the capability and high efficiency potential of AI-enabled CPS that are capable of integrating, operating, and managing increasingly more complex and fully electrified economic systems. Based on these promising developments, this brief advocates for the mainstreaming of AI-driven CPS, or what will be referred to here as Intelligent Decarbonisation (IDC), as a vital technology for climate change risk mitigation and adaptation efforts. To understand the full potential of IDC, the brief outlines its key components, with a focus on AI-enhanced CPS and their applications across multiple sectors. While recognising IDC’s potential, the limitations of relying solely on climate technology as a remedy for climate change must be acknowledged. An overreliance on technology as the primary solution has demonstrated limited success, as evidenced by repeated warnings from the UN and IPCC. [4] IDC faces its own limitations, such as lack of data, absence of CPS and AI solutions, and unintended reverse effects of optimisations. Furthermore, IDC is still in its early stages, making any exploration of its long-term impacts merely speculative. AI research also scarcely focuses on climate change. However, the issue of technology solutionism is not just about engineering bottlenecks; technology itself can be part of the problem.