Assistant Curator of Pollinating Insects Field Museum Chicago, Illinois
Museum insect collections are incredibly data-rich, but processing specimens 1-by-1 is time and labor-intensive. We are working to speed up the digitizing process by combining automated whole-drawer imaging with a suite of computer vision-based AI models. From large, high-resolution photographs containing 100s of specimens, we can train AI to automatically find, crop, and extract phenotypic data (qualitative and quantitative) from each individual. We can then use these data to test hypotheses about the macroevolutionary drivers of certain traits, e.g. color patterns, for entire families of insects. These data may even be useful to train future species-ID models, which could help sort backlogs of "unidentified" specimens.