Mitigating demographic bias in facial presentation attack detection

Bias in AI-powered biometric algorithms can lead to unfair treatment of individuals in certain demographic groups based on their gender, age, and race.

As with matching algorithms, bias in liveness detection can also lead to higher error rates and less accessibility for mobile banking services for individuals based on their appearance.

This white paper by ID R&D introduces methodologies to address bias in support of Responsible AI principles.

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Article Topics

AI  |  banking  |  biometric bias  |  biometric liveness detection  |  biometrics  |  ethics  |  ID R&D  |  mobile banking  |  mobile biometrics  |  responsible AI  |  white paper