Guide

Bias audit checklist for AI hiring assessments

If AI helps score or rank candidates, outcome monitoring is part of the product. This checklist helps talent, I/O, and legal partners run a repeatable bias-audit loop for verified behavioral assessments-without pretending a single fairness metric solves hiring risk.

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01

Freeze what you will audit

You cannot explain outcomes if questions, rubrics, and models drifted mid-wave. Freeze assessment versions, log model versions, and record who approved the competency model.

02

Export the right outcome data

Track who started, completed, advanced, and was rejected-by role family and assessment version. Include reviewer overrides and integrity-driven retests so audits reflect real decisions, not only raw model scores.

  • Completion and advance rates
  • Override rates and reasons
  • Accommodation and retest counts
  • Integrity flag rates (for process health, not as a protected-class proxy)

03

Compute selection rates and impact ratios carefully

Adverse-impact analyses depend on available demographic data and counsel’s methodology. Do not invent categories. Do document limitations. Pair quantitative reviews with qualitative rubric reviews when disagreement spikes.

Workflow

Keep this loop in mind

Guides go deeper—but the product motion stays the same.

Assessment loop
Select
Role · Customer Success Manager
Customer empathy
30%
Ownership
25%
Communication
20%
Adaptability
15%
Conflict resolution
10%

Integrity gate

Threats get intercepted. Genuine candidates pass through.

A four-scene integrity loop: live session, anomaly detection, layered interception, and verified pass—built for AI-era cheating.

  • Device & session
  • Behavior & language
  • AI assistance
Honrly integrity
Session live
Candidate sessionLive

“When a renewal was at risk, I called the customer the same day and owned the save through Q3…”

Response · 00:14:22
Integrity watch
  • Identity checkok
  • Device postureok
  • Response cadenceok

Comparison

Traditional vs Honrly

Side by side
Primary signal
Traditional

Self-report / black-box score

Honrly

Demonstrated evidence + integrity

04

Inspect the measurement, not only the math

A “fair” score on an undefendable trait is still a bad assessment. Confirm competencies are job-related, anchors are behavioral, and high-risk modalities (faces, accents, appearance) are excluded.

05

Remediate with product changes

If impact ratios look problematic, change the assessment-not only the slide deck. Adjust competencies, anchors, cut scores, or human-review thresholds. Re-freeze and re-measure.

06

Publish and retain documentation

Keep versioned reports, notices, and decision records. Where laws require public summaries (e.g., NYC AEDT rules), treat publication as an operating step.

FAQ

Frequently asked questions

No. Use it as an internal operating checklist and confirm requirements with counsel.

Next step

Ready to run verified assessments with integrity?