Machine learning assisted evidence synthesis to support evidence-based policy on climate change

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• Dr Max Callaghan, Mercator Research Institute on Global Commons and Climate Change, Berlin
• Tuesday 23 January 2024, 16:00-17:00
• Drum Building, Madingley Rise Site, West Cambridge and on zoom: https://zoom.us/j/6708259482?pwd=Qk03U3hxZWNJZUZpT2pVZnFtU2RRUT09.

If you have a question about this talk, please contact Annabelle Scott.

Useful information about climate change is hidden in millions of unstructured texts. Using Natural Language Processing (NLP) to identify, classify and analyse these texts, we can derive insights that help us to understand the science and politics of climate change. Machine learning-assisted evidence synthesis can make vital meta-learning from scientific literature more tractable, and aid important assessment processes like the Intergovernmental Panel on Climate Change. In this talk, we will explore some of the ways in which machine learning can be used to scale up evidence synthesis, with applications in climate science, climate impacts, and climate mitigation policy.

This talk is part of the AI4ER Seminar Series series.

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• AI4ER Seminar Series
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• Drum Building, Madingley Rise Site, West Cambridge and on zoom: https://zoom.us/j/6708259482?pwd=Qk03U3hxZWNJZUZpT2pVZnFtU2RRUT09
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