Bias persists in face detection systems from Amazon, Microsoft, and Google

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Commercial face-analyzing systems have been critiqued by scholars and activists alike over the past decade, if not longer. A paper last fall by University of Colorado, Boulder researchers showed that facial recognition software from Amazon, Clarifai, Microsoft, and others was 95% accurate for cisgender men but often misidentified trans people. Furthermore, independent benchmarks of vendors' systems by the Gender Shades project and others have revealed that facial recognition technologies are susceptible to a range of racial, ethnic, and gender biases. Companies say they're working to fix the biases in their facial analysis systems, and some have claimed early success.