AI methods have had a great deal of success in automating the arduous task of labelling biological and medical images. Camera trap images require a similar labelling task where many different labels need to be assigned, sometimes to a single image. This project will explore how an interactive system can be developed to assist in the semi-automatic labelling of multiple species. This will involve using state-of-the-art explainable AI (XAI) methods combined with multi-class active learning to assist in choosing labels or highlighting which images need human intervention. It will also use XAI methods to help explain why images were labelled in a particular way so that a better understanding of the strengths and weaknesses of AI methods can be determined.