Powerful Non-Technical Guide to Affinity Concealment in ML
Introduction Affinity Concealment in ML is the practice of masking or removing user affinity signals from machine learning workflows to protect privacy and reduce bias. In simplest terms, concealment allows organizations to build models that ignore sensitive patterns such as repeated behavior or personal preferences while still delivering useful predictions. By focusing on non-technical strategies,…