defining a plurality of sensitive categories associated with a plurality of training images;

defining a plurality of protected attributes associated with the plurality of training images;

determining, for a particular sensitive category, a distribution of at least one protected attribute within the plurality of training images;

based on the distribution, calculating for each image in the plurality of training images a corresponding image debiasing weight value associated with the at least one protected attribute;

generating annotated training data comprising the plurality of training images and further comprising, for each image in the plurality of training images, (1) the corresponding image debiasing weight value associated with the at least one protected attribute and (2) a corresponding descriptive text caption; and

performing a training process using the annotated training data to train a generative image model resulting in a trained model, wherein a contribution of each image in the plurality of training images to an optimization loss of the training process is weighted during the training process using the corresponding image debiasing weight value.