A new review of face recognition software found that, when identifying gender, the software is most accurate for men with light skin and least accurate for women with dark skin. Joy Buolamwini, an MIT Media Lab researcher and computer scientist, tested three commercial gender classifiers offered as part of face recognition services. As she found, the software misidentified the gender of dark-skinned females 35 percent of the time. By contrast, the error rate rate for light-skinned males was less than one percent.