identifying, by a machine learning network, a plurality of data samples comprising a protected attribute;

processing the identified data samples using a first sub-network of the machine learning network, wherein the first sub-network is configured to determine information corresponding to a plurality of contexts of the protected attribute across the identified data samples, wherein each of the plurality of contexts corresponds to a different meaning associated with the protected attribute;

determining respective impacts of the plurality of contexts on a second sub-network of the machine learning network, wherein the second sub-network of the machine learning network is configured to classify a given data sample into one of a plurality of classes; and

adjusting the second sub-network of the machine learning network to account for the impact corresponding to at least one of the plurality of contexts on the second sub-network;

wherein the method is carried out by at least one computing device.