DEI

AI Interview-Notes Bias Scrubber

Design and pilot an AI-assisted process that strips bias-coded language out of interview notes before hiring managers see them, using a two-stage pilot to validate accuracy.

Inspired by Yvette Torres Hansen·Director, Talent Acquisition & DEIB/Belonging·Baylor Scott & White Health

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What this skill does

Designs and pilots an AI-assisted process that strips bias-coded language out of interview notes before hiring managers see them, validated through a two-stage pilot.

What's included

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Customization intake

A short set of questions about your process and data access.

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Step-by-step implementation process

The exact steps to build this from your own data.

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Definition of done

How to know the output is producing a usable, defensible signal.

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Common pitfalls

Where teams usually get this wrong, and how to avoid it.

The process

Step 1 — Step 1 — Define what "clean" notes mean for your organization.

Step 2 — Step 2 — Choose or configure the tool against your actual vendor situation.

Step 3 — Step 3 — Treat the ruleset as trained, not static, with a weekly review loop.

Step 4 — Step 4 — Run Pilot 1 with manual side-by-side verification.

Step 5 — Step 5 — Refine rules and run Pilot 2, handing off to hiring managers.

Step 6 — Step 6 — Decide the rollout gate and who owns it.

The download also includes the full definition of done and common pitfalls.

Where this came from

Inspired by Yvette Torres Hansen, Director, Talent Acquisition & DEIB/Belonging at Baylor Scott & White Health

Heard on The Hiring Scope (National Association for Healthcare Recruitment / NAHCR)

Listen to episode ↗Guest's LinkedIn ↗

This skill was built by the Skills for People team based on Yvette Torres Hansen's public remarks — not written or reviewed by them.