We say the AI is auditable — deliberately not "unbiased." No vendor can honestly promise unbiased screening; what we can promise is the evidence to check for yourself: every AI call logged and an exportable history of AI-assisted decisions.
"Unbiased" is an outcome claim nobody can prove. "Auditable" is a process claim we can back up:
If a bias question ever comes up, you're not asking us to vouch for the AI — you're pulling the records.
Each row is one AI decision:
| Column | What it contains |
|---|---|
| Decision ID and type | Screening or interview analysis |
| Date | When the decision was made |
| Candidate | Initials only — the export is privacy-safe by design (no emails, phones, or profile links) |
| AI score and outcome | What the AI concluded |
| Must-know flags | Any must-know checks that fired — flags for recruiter review, never automatic rejections |
| Human decision recorded / date | Screening: whether and when a recruiter reviewed the response. Interview analysis: whether a recruiter logged an outcome; the date is the interview's last update, so treat it as approximate |
| Role | The role the decision related to |
The export is a decision log, not a bias analysis. PlacementFlow does not collect demographic or other protected-characteristic data about candidates, so it does not compute selection rates across groups and does not apply the four-fifths (80%) rule for you. If your agency runs that kind of analysis, you would combine this log with demographic data you hold lawfully yourself. The "Selection-rate (four-fifths rule) monitoring" row on Settings → Compliance says "Not provided" for this reason.
One bias guardrail does run underneath:
Note: candidate matching itself is keyword- and tag-based with recruiter judgment — PlacementFlow deliberately does not rank candidates by machine-learned similarity to past hires, precisely because that pattern is a well-documented proxy-discrimination risk.
Vendors that promise "unbiased AI" are making a claim they can't defend — and one that regulators and courts increasingly test. Our position: the AI does the operational work, a human approves high-stakes actions, and everything is logged so you can verify rather than trust. When a client's procurement team asks "how do you monitor your AI for bias?", the honest answer is the decision log plus what we deliberately do not collect, not an adjective.