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IBM Data and AI Ideas Portal for Customers


This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (https://ideas.ibm.com).


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Welcome to the IBM Ideas Portal (https://www.ibm.com/ideas) - Use this site to find out additional information and details about the IBM Ideas process and statuses.

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IBM Employees should enter Ideas at https://ideas.ibm.com


Status Not under consideration
Workspace Openscale
Created by Guest
Created on Mar 8, 2020

Composite protected feature indirect bias detection

Currently indirect bias detection works for independent features. For ex: race may have a high correlation with zip code, income etc.

But need to do the same for composite features like black female, or young black female. Sometimes these protected features by themselves may not have a significant effect but does when taken together

For a customer who is interested to identify which all features have a high correlation leading to indirect bias, it needs to be done automatically, since manual approach may not capture everything

Also, how would bias be detected for a composite feature like black male or older white male, where some feature are monitored group and some are protected groups