From Machine Learning to Machine Knowing: A Digital Anthropology Approach for the Machine Interpretation of Cultures

The paper explores the potential for combining anthropology, data science, and artificial intelligence to create a transdisciplinary practice capable of modeling and interpreting human culture. It proposes an Ethnographic Semantic Data Modeling (EKSDM) approach to combine ethnographic practices with semantic data modeling techniques for greater context and explainability. An Anthropological Knowledge Graph (AKG) is proposed as a tool for situating data in context through links and semantic metadata. An AKG maturity model provides a roadmap for progressively building a robust and contextually rich knowledge graph. Using EKSDM to create an AKG offers a powerful tool for enhancing other technologies, such as Large Language Models (LLMs), and moving from machine learning to machine knowing for the machine interpretation of cultures.