AI employment decision audit

AI Employment Decision Audit Guide

An AI employment decision audit looks beyond recruiting copy and tests whether automated systems that influence employment outcomes are documented, monitored, and reviewed for protected-group impact.

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Where this fits

A tool ranks candidates before recruiter review and affects who advances.

An assessment score is used to decide interview invitations or promotion eligibility.

The company needs one framework across US and EU hiring operations.

Operating steps

  1. Scope every automated decision influence, including ranking, recommendations, scoring, and knockout rules.
  2. Document the legal basis, business purpose, data inputs, human review process, and escalation owner.
  3. Run outcome testing by group, stage, role, geography, and time period.
  4. Assess documentation, notice, accessibility, human oversight, and change-management controls.
  5. Create a report with findings, limitations, remediation actions, and the next review date.

Common risks

  • Calling a tool advisory when recruiters effectively follow the algorithmic ranking.
  • Leaving promotion or internal mobility tools outside the audit scope.
  • Failing to document human oversight in a way that can be reviewed later.

How HireBias Audit connects

HireBias Audit supports AI employment decision audits by combining scope inventory, adverse impact math, tool-stage risk scoring, and report generation.

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