By Concerned Researchers

Over the past few months, there has been increased public concern over the accuracy and use of new face recognition systems. A recent study conducted by Inioluwa Deborah Raji and Joy Buolamwini, published at the AAAI/ACM conference on Artificial Intelligence, Ethics, and Society, found that the version of Amazon’s Rekognition tool which was available on August 2018, has much higher error rates while classifying the gender of darker skinned women than lighter skinned men (31% vs. 0%). In response, two Amazon officials, Matthew Wood and Michael Punke, wrote a series of blog posts attempting to refute the results of the study [1, 2]. In this piece we highlight several important facts reinforcing the importance of the study and discussing the manner in which Wood and Punke’s blog posts misrepresented the technical details for the work and the state-of-the-art in facial analysis and face recognition.