Natural Language Generation for Nature Conservation: Automating Feedback to Help Volunteers Identify Bumblebee Species

This paper explores the use of Natural Language Generation (NLG) for facilitating the provision of feedback to citizen scientists in the context of a nature conservation programme, BEEWATCH. BEEWATCH aims to capture the distribution of bumblebees, an ecologically and economically important species group in decline, across the UK and beyond. The NLG module described here uses comparisons of visual features of bumblebee species as well as contextual information to improve the citizen scientists’ identification skills and to keep them motivated. We report studies that show a positive effect of NLG feedback on accuracy of bumblebee identification and on volunteer retention, along with a positive appraisal of the generated feedback.