Evaluating LLMs for providing evidence-based information on conservation actions
This is an idea proposed in 2025 as a good starter project, and is currently being worked on by Radhika Agrawal. It is co-supervised with Alec Christie and Sadiq Jaffer.
We are building a Conservation Co-Pilot to improve worldwide conservation action through evidence-driven insights. Biodiversity loss is one of the biggest threats to our planet and to tackle it, we must improve the effectiveness of conservation action, which currently falls short of its full potential. This is because conservationists typically find it hard to access locally relevant evidence on what works to conserve biodiversity as research knowledge is not translated quickly or accessibly enough into policy and practice. We therefore need to accelerate the transfer of relevant, reliable evidence to decision-makers using more intuitive and interactive interfaces.
This project will use the comprehensive Conservation Evidence database (holding 8600 studies that have quantitatively tested 3600 actions) to evaluate the ability of a Mixture of Agents (MOA) approach, and/or individual LLMs, at providing rigorous evidence-based answers to priority questions from real conservationists.
This will extend our previous work that found that LLMs coupled with a hybrid retrieval strategy can answer multiple choice conservation questions as well as human experts. This will enable us to develop a "Conservation Co-Pilot" that can handle complex and nuanced questions from different users.
ideas