This audit measures how much your hiring decisions depend on AI tools versus your own assessment. It focuses on the moments where you choose to trust an algorithm instead of your instinct about candidates.
Create a sourcing list of candidates who were rejected by AI screening but hired after you interviewed them anyway. Show this list to your hiring managers quarterly. This builds the case for human override.
Never let a job description be written entirely by AI. At minimum, interview your hiring manager for 30 minutes about what the role actually requires, then write it yourself. AI drafts amplify keyword bias and attract candidates who sound right on paper but have no real fit.
If you use LinkedIn Recruiters AI, turn off auto-suggestions for your top 20 percent of hires. Review those profiles manually first. Track whether AI would have surfaced them or filtered them out.
Conduct a bias audit on your screening decisions from the past 6 months. Compare candidates AI rejected with candidates you interviewed anyway. Look for patterns: age, gender, university, employment gaps. If you are overriding AI more often for certain demographics, the tool may be embedding bias at scale.
Schedule a 30-minute conversation with one candidate per week after they are hired. Ask them why they applied, what confused them about the job description, and which part of the process felt most unfair. Use their feedback to adjust either your AI settings or your manual process.