Automated identification of ivory carvings using machine learning: A proof-of-concept approach to detecting the illegal wildlife trade

A research study introduces a proof-of-concept machine learning approach to automate the detection of illegal elephant ivory carvings in online marketplaces. The work addresses severe operational bottlenecks in wildlife law enforcement, where high advert volumes, visual resemblance to legal materials, and the physical constraints of traditional identification techniques impede proactive monitoring and prosecution.

This initiative addresses a foundational enforcement challenge by seeking to automate the visual identification of illicit wildlife products across digital channels. Bridging the operational gap between physical lab-based diagnostics and high-volume digital marketplace screening is critical for scaling enforcement without exponential increases in manual labor. Establishing automated detection capabilities could fundamentally alter how regulatory compliance and cross-border trade controls are operationalised online.

International bans have failed to eliminate illicit trade, with poached elephant ivory continuing to be traded actively across digital marketplaces.

Forward consideration, not a verified fact.