Face recognition is becoming widely used in government and business for a variety of tasks including border control, crowd control, shopper identification, and so on. A significant issue for such models is to deal with the bias of the models often resulting from the bias inherent in the dataset of images provided for the training of the model.
The US National Institute of Standards and Techology (NIST) has considered issues of bias and effectiveness of face recognition models. For example, during the COVID-19 pandemic NIST investigated the impact of masks on identification but automatically masking images of millions of faces and testing the effectiveness.
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