Operational Fairness for Facial Authentication Systems
Résumé
How to design a facial authentication system taking into account both performance and fairness? We consider the choices that a developer makes when coding such a system, such as the training parameters, the architecture of the neural network or the authentication threshold. We evaluate their impact on the global fairness of the system showing that fairness is not only affected by the training data but also by the multiple choices that are made when coding the model.
Domaines
Intelligence artificielle [cs.AI]| Origine | Fichiers éditeurs autorisés sur une archive ouverte |
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