Determining data representative of bias within a model

Methods, systems, and computer program products for determining data representative of bias within a model are provided herein. A computer-implemented method includes obtaining a first dataset on which a model was trained, wherein the first dataset contains protected attributes, and a second dataset...

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Bibliographic Details
Main Authors Bhide, Manish Anand, Lohia, Pranay Kumar, Saha, Diptikalyan, Mehta, Sameep
Format Patent
LanguageEnglish
Published 25.04.2023
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Online AccessGet full text

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Summary:Methods, systems, and computer program products for determining data representative of bias within a model are provided herein. A computer-implemented method includes obtaining a first dataset on which a model was trained, wherein the first dataset contains protected attributes, and a second dataset on which the model was trained, wherein the protected attributes have been removed from the second dataset; identifying, for each of the one or more protected attributes in the first dataset, one or more attributes in the second dataset correlated therewith; determining bias among at least a portion of the identified correlated attributes; and outputting, to at least one user, identifying information pertaining to the one or more instances of bias.
Bibliography:Application Number: US201916690686