Seminar, three hours. Requisite: course 101. Large language models and image generators seem to be realizing visions and warnings of science fiction. Study asks how these systems’ accuracies, biases, and inner workings be measured enough to interrogate their value academically. Introduction to automated ways of working with difficult data types and tasks in digital humanities, examining history and critical conversations about artificial intelligence, automation, and data. Students compare different automated and manual methods of description, translation, transcription, classification, natural language processing, and image processing. Evaluation of their potential for use in archives, museums, educational environments, art, and other humanities. No experience or background in coding or artificial intelligence technologies required.