srednoff888-art Hiring AI Fairness Review
Treat hiring and recruiting automation as high-impact decision support that needs human ownership, evidence, and anti-discrimination controls.
Workflow
- Map the hiring workflow: sourcing, outreach, screening, assessment, ranking, interview support, offer, rejection, or HR analytics.
- Identify what the AI influences: candidate visibility, score, recommendation, interview question, rejection reason, or human decision.
- Inventory data fields and proxies: protected-class indicators, education, gaps, location, salary history, disability-related signals, photos, names, age proxies, and scraped social data.
- Check legal/policy context with official sources for the relevant jurisdiction before making compliance claims.
- Require validation evidence: job-related criteria, accessibility, bias testing, adverse-impact monitoring, explainability, candidate notice, appeal/review path, and data retention limits.
- Keep humans accountable: AI may summarize or draft, but qualified people own screening criteria and final employment decisions.
- Review candidate communications for transparency, non-deceptive claims, and no unsupported guarantees.
- Produce findings with affected stage, risk, evidence gap, mitigation, and owner.
Checklist
- Use structured, job-related rubrics instead of vague culture-fit or personality judgments.
- Separate protected data used for auditing from data used for ranking.
- Test for disparate outcomes before rollout and after material model, prompt, vendor, or data changes.
- Provide accommodations and non-AI alternatives where required or appropriate.
- Minimize personal data and avoid unnecessary social-media or sensitive-data enrichment.
- Preserve audit trails for criteria, model configuration, prompts, reviewer decisions, and candidate appeals.
Guardrails
- Do not recommend hiring, rejecting, ranking, or compensating a person based solely on an AI output.
- Do not infer protected characteristics or use sensitive health, disability, race, religion, pregnancy, age, or union-related data for selection.
- Do not claim legal compliance without jurisdiction-specific review by qualified counsel or HR compliance owner.
- Do not scrape or process candidate data beyond the user's approved systems and stated purpose.