Biodiversity ambition analysis with Large Language Models

TheKunming-Montreal Global Biodiversity Framework (GBF) has 23 action-oriented global targets for urgent action over the decade to 2030.Parties committing themselves to the targets set by the GBF are required to share their national targets and biodiversity plans.In a case study on the GBF target to reduce pollution risks, we analyze the commitments of 110 different Parties, in 6 different languages.Obtaining satisfactory results for this target, we argue that using Generative AI can be very helpful under certain conditions, and it is a relatively small step to scale up such an analysis for other GBF targets.