US 2020/0090055 A1 · DATA RETRIEVAL WITH BIAS REDUCTION

Abstract

Digital data systems and methods support data retrieval with bias reduction. In some embodiments, these minimize the effect of bias in artificial intelligence-based business intelligence engines by preventing reporting of models that are based on “bias-sensitive” predictor variables such as race, sex and political affiliation, and so forth. In other embodiments, e.g., where the AI engine returns measures (or degrees) of correlation, such censure can be with respect to models where those measures are above a designated quantitative or qualitative high water mark values. Alternatively, or in addition, the systems and methods hereof can minimize the effect of data bias by reducing such a measure of correlation so that the corresponding model appears inferior to ones that are not based on bias-sensitive predictor variables.

Claims20

Dependent claims

A method of data retrieval, comprising

accepting a user request,
applying the user request to an artificial intelligence engine to generate a predictive model from a data store that comprises a set of data records, each representing an individual and comprising values for a plurality of fields pertaining to a characteristic of that individual, the predictive model identifying one or more of the fields as predictor variables that are correlated with a field that is a target variable,
determining whether one or more of the fields identified as a predictor variable is bias-sensitive.

Dependencies are inferred from the claim text.

Data retrieval with bias reduction

Life of this patent

Data retrieval with bias reduction

Life of this patent

Abstract

Claims20