Understanding the Antiquities Market Through an AI-Driven Approach

This paper presents AIKoGAM, an innovative AI-driven Knowledge Graph of the Antiquities Market, developed to decipher the complexities of the global antiquities trade, a realm where legal and illicit activities often intertwine. AIKoGAM is designed to tackle the dual challenges of artifact authenticity and legality in a market marked by legislative inconsistencies across countries. The system is structured into four primary modules: Information Retrieval, Data Mapping and Transformation, Event Extraction, and Knowledge Graph Construction. These modules work in tandem to collect, standardize, process, and visualize data from diverse sources like auction houses and galleries. The resultant Knowledge Graph Database (KGDB) forms an intricate network of nodes and relationships, shedding light on the connections between objects, dealers, collectors, and auction houses. This analysis offers unprecedented insights into the antiquities market’s dynamics, highlighting the potential pathways of illicit activities and providing valuable information for market regulators and cultural heritage professionals. AIKoGAM shows the power of combining AI and network science in cultural heritage studies, paving the way for more informed policy-making and ethical practices in the antiquities trade.