Climate Change AI Innovation Grants

Grant funding support for projects that will leverage Artificial Intelligence (AI) or machine learning to address problems in climate change mitigation, climate change adaptation, or climate science.

This grants programme is adminstered by Climate Change AI (CCAI), with the financial support of DeepMind and the Quadrature Climate Foundation and administrative support from Future Earth International. CCAI is a global organisation composed of volunteers from academia and industry who believe that tackling climate change requires concerted societal action, in which machine learning can play an impactful role. The programme will allocate grants to year-long research projects that apply artificial intelligence (AI) to help study, mitigate, or adapt to climate change.

Relevant research includes but is not limited to the following topics:

• Machine learning to aid mitigation approaches in relevant sectors such as agriculture, buildings and cities, heavy industry and manufacturing, power and energy systems, transportation, or forestry and other land use.
• Machine learning applied to societal adaptation to climate change, including disaster prediction, management, and relief in relevant sectors.
• Machine learning for climate and earth science, ecosystems, and natural systems as relevant to mitigation and adaptation.
• Machine learning for R&D of low carbon technologies such as electrofuels and carbon capture and sequestration.
• Machine learning approaches in behavioural and social science related to climate change, including those anchored in climate finance and economics, climate justice, and climate policy.
• Projects addressing AI governance in the context of climate change, or that aim to assess the greenhouse gas emissions impacts of AI or AI-driven applications, may also be eligible for funding.

For context, CCAI advises applicants to review the list of the research projects funded during the 2022 Innovation Grants cycle.

The 2023 competition, features a special track on machine learning in the electric power sector. Applications in this track may optionally request support from a DeepMind Engineer, in addition to the financial award.

Projects are expected to result in scientific publications or other public dissemination, and should either yield deployed systems or include well-considered pathways to deployment.