Racial Bias in Automated Face Classification Models: Effects of Dataset Diversity and Racial Ambiguity

We investigated the degree to which racial bias in AI-based automated face classification models depends on the diversity of training data. Face classification models trained on predominantly-White face datasets poorly classified non-White faces and exhibited hypodescent-like classifications of racially-ambiguous faces. Models trained on racially-diverse faces did not produce these biases.