ChimpFace is an image analysis software that uses machine learning to identify photos linked to wildlife trafficking activities. As its name suggests, the project focuses primarily on chimpanzees given the frequency of their live sale as exotic animals on the online black market and their highly recognizable and distinct facial features. Using a combination of public and privately curated imagery datasets, the AI-driven computer vision will be deployed to monitor social media and e-commerce websites. Flagged posts will then be sent to a team of experts for review and further action. The creators of ChimpFace hope to implement textual analysis to down-select posts based on trafficking lingo used in the photo’s description, as well as broaden their imagery datasets to include more species. The ultimate aim of ChimpFace is to be able to transmit photographic evidence to the proper authorities for use in criminal proceedings prosecuting wildlife traffickers. The project was launched in 2017. Currently, image recognition technologies of this sort do exist, but are not autonomous and require time-consuming vetting by humans. As a result, most of the search for these animals on the web is done through manual searches, which is like “searching for a needle in a haystack” according to the creators of ChimpFace. In both the manual and ChimpFace methods, double-counting (or even triple or more) the same chimpanzee due to the detection of multiple pictures of the same chimp on one or more sites could lead to some inaccuracies in count. By creating a modern, internet-facilitated detection tool, conservationists and law enforcement alike will be able to keep up with the growth of the online wildlife trafficking market with high efficiency. 


Russo, A. (2017). ChimpFace. Retrieved from


Artificial Intelligence, Biodiversity, Illegal Resource Extraction, Visual Technologies