Protecting Employee Data Guide

  • Explains how to prevent the "mosaic effect" where multiple harmless data points are combined to reveal a person’s identity
  • Provides a "Safe vs. Never Use" checklist for common HR data types like salary, health records, and performance scores
  • Offers a step-by-step practical framework for anonymizing, aggregating, and documenting data processing actions
  • Delivers a decision-making "Pause-or-Proceed" flowchart to ensure compliance before processing data with AI
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Downloads 6 downloads Type Guide Publication date January 02, 2026 Topics AI for HRDigital HRPeople Analytics

This guide serves as an essential manual for HR professionals to safeguard employee privacy while utilizing AI tools, detailing how to identify, anonymize, and ethically manage various categories of personnel data. It provides practical frameworks for avoiding the accidental identification of individuals through combined data points, often referred to as the “mosaic effect”.

Included in this resource:

  • Introduction to AI and employee privacy
  • Understanding employee data categories (PII, sensitive, inferred, and aggregated)
  • The Mosaic Effect: Risks of combining data
  • Data usage matrix: Safe vs. restricted ai inputs
  • Practical steps for data protection
  • Pause-or-proceed decision framework
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