AI for registration and publication of museum collections With the project Automatic recognition as a tool for museum collections, Naturalis set out to investigate how Artificial Intelligence (AI), and specifically automatic image recognition, can contribute to the registration and publication of museum collections. This was done by working closely with various project partners and stakeholders to develop a number of image recognition models for various types of specimens and artifacts. These recognition models were made accessible to man and machine through a web-based interface and an API: https://museum.identify.biodiversityanalysis.nl/. Disappearing identification expertise Objects (specimens) in natural history collections are traditionally identified by taxonomists. Being able to name and interpret species is a crucial prerequisite for biodiversity research and capacity building. Knowledge of popular species groups is often widespread, but for other species groups specialists and knowledge are scarce resources. Virtually all natural history museums have to deal with extensive and ever-growing collections on the one hand, and a decreasing number of available species specialists on the other hand. As a result, often large numbers of objects (specimens) in these types of collections have not yet been identified. Automatic image recognition could contribute to the naming of (a part of) these specimens, thus allowing for more efficient use of the specialist knowledge of taxonomists. Their expertise could be better put to use in cases where automated identification on the basis of a photograph alone cannot provide a conclusive answer (e.g. because microscopic features are relevant) or when the specimen is in fact an undescribed species. What did we learn from the pilots? In this project we investigated which type of objects or collections are well suited for automatic image recognition, how image recognition can be deployed in the process of collection registration and publication, and how AI can answer ...