Performance model adverse impact correction
US10438135B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 27, 2016 |
| Grant date | Oct 8, 2019 |
| Priority date | — |
| Expiry date | Feb 5, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Technology for training a predictive model is described. A processing device collects digital interview data including features identified from candidate interviews. A model training tool selects a data set of the digital interview data. The data set includes a predicted performance outcome and an actual performance outcome for each of a plurality of candidates. The model training tool determines an error metric for each of the plurality of candidates. The error metric includes a relationship between the predicted performance outcome and the actual performance outcome for each candidate. The model training tool determines a number of candidates whose digital interview data includes a feature corresponding to a protected class. The model training tool normalizes an effect of each candidate on the error metric based on the corresponding protected class and applies the normalized error metric to reduce bias in the predictive model with respect to the protected class.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.