Abstract: Systems and methods can compute a multidimensional score of apparent skin color to capture skin color variation and provide a comprehensive representation of its constitutive complexity. The multidimensional apparent skin color score can be used to reveal biases related to skin color in image datasets and computer vision models. The multidimensional skin color score can focus on the perceptual lightless, L*, as a measure of skin tone ranging from light to dark, and the hue angle h*, as a measure of skin hue ranging from red to yellow. The multidimensional skin color scale offers a more representative assessment to surface socially relevant biases due to skin color effects in computer vision. This could help to (i) enhance the diversity in the data collection process, by encouraging specifications to better represent skin color variability; and (ii) improve the identification of dataset and model biases in fairness benchmarking, by highlighting their limitations.

Abstract: Systems and methods can compute a multidimensional score of apparent skin color to capture skin color variation and provide a comprehensive representation of its constitutive complexity. The multidimensional apparent skin color score can be used to reveal biases related to skin color in image datasets and computer vision models. The multidimensional skin color score can focus on the perceptual lightless, L*, as a measure of skin tone ranging from light to dark, and the hue angle h*, as a measure of skin hue ranging from red to yellow. The multidimensional skin color scale offers a more representative assessment to surface socially relevant biases due to skin color effects in computer vision. This could help to (i) enhance the diversity in the data collection process, by encouraging specifications to better represent skin color variability; and (ii) improve the identification of dataset and model biases in fairness benchmarking, by highlighting their limitations.