US 12,347,233 B2
Methods and systems for identifying and reducing gender bias amplification
Dorothy Zhao, Princeton, NJ (US); Jerone Andrews, Tokyo (JP); and Alice Xiang, Seattle, WA (US)
Assigned to SONY GROUP CORPORATION, Tokyo (JP)
Filed by Sony Group Corporation, Tokyo (JP); and Sony Corporation of America, New York, NY (US)
Filed on Nov. 11, 2022, as Appl. No. 18/054,636.
Claims priority of provisional application 63/371,831, filed on Aug. 18, 2022.
Claims priority of provisional application 63/263,985, filed on Nov. 12, 2021.
Prior Publication US 2023/0154235 A1, May 18, 2023
Int. Cl. G06V 40/16 (2022.01)
CPC G06V 40/172 (2022.01) [G06V 40/161 (2022.01); G06V 40/168 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method of determining an extent of a bias, in a model, across a plurality of group membership labels, comprising:
providing a training dataset having multiple training dataset attributes in a plurality of training images of the training dataset;
training the model to identify one of the plurality of group membership labels for a training image object in each of the plurality of training images, wherein the training associates the one of the plurality of group membership labels with multiple ones of the multiple training dataset attributes;
operating the trained model on a plurality of test images of a test dataset, each of the plurality of test images including a test image object and multiple test dataset attributes, to identify one of the group membership labels for each test image object based on the multiple test dataset attributes; and
determining a bias amplification in the identification of one of the plurality of group membership labels for each test image object in each of the plurality of test images.