Invention Grant
- Patent Title: Audit machine learning models against bias
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Application No.: US16125741Application Date: 2018-09-09
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Publication No.: US11263550B2Publication Date: 2022-03-01
- Inventor: Marisa Affonso Vasconcelos , Carlos Henrique Cardonha
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Intelletek Law Group, PLLC
- Agent Gabriel Daniel, Esq.
- Main IPC: G06F21/62
- IPC: G06F21/62 ; G06N99/00 ; G06F16/24 ; G06K9/62 ; G06N20/00 ; G06N5/04

Abstract:
A method and system of mitigating bias in a decision-making system are provided. A presence of bias is identified in one or more machine learning models. For each of the machine learning models, a presence of bias in an output of the model is determined. One or more options to mitigate a system bias during a processing stage, based on the identified presence of bias for each of the one or more models, are determined. One or more options to mitigate the system bias during a post-processing stage, based on the identified presence of bias in each output of the models, are determined. A combination of options is provided, including (i) a processing option for the processing stage, and (ii) a post-processing option for the post-processing stage, wherein the combination of options accommodates a threshold bias limit to the system bias and a total bias mitigation cost threshold.
Public/Granted literature
- US20200082299A1 Audit Machine Learning Models Against Bias Public/Granted day:2020-03-12
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