The Bias
Hiring software auto-rejected every woman 55 or older and every man 60 or older. The rule was programmed in - nobody caught it. The EEOC's first settlement over automated hiring discrimination: $365,000.
25 minutes. A branching story, a proxy-spotting audit lab, and a touchpoint-mapping sprint. A safety score with feedback on every decision.
Before you start
- One real incident, played as decisions - no slides, no lectures.
- About 25 minutes, one sitting - leave early and you start over.
- You make timed choices; your score changes with your decisions.
- You get a safety score with feedback on every decision - never a leaderboard, never your name.
- Your firm sees completion evidence - never your answers. Teammates never see your score.
- Finish and you get a certificate with a unique ID anyone can verify.
Free for everyone. All 18 drills are free - finish and you get a verifiable certificate.
Auto-rejected. Every woman 55 or older. Every man 60 or older.
2020. iTutorGroup programmed its application software to auto-reject women 55 or older and men 60 or older. The EEOC sued in 2022 - its first case over automated hiring discrimination - and settled in 2023 for $365,000 covering 200+ rejected applicants.
It wasn't the first warning: Amazon scrapped an experimental recruiting model that penalized the word "women's" on resumes (Reuters, 2018). It learned patterns from ten years of resumes, most from men - and did what those patterns taught it. And the fight is growing: in Mobley v. Workday, a court preliminarily certified a nationwide age-discrimination collective against a mainstream HR vendor in 2025.
Liability doesn't stay in one place. iTutorGroup shows the employer can't hide behind the vendor. Mobley v. Workday shows the vendor can't hide either - a court let a discrimination suit against Workday itself proceed.
Your first week as HR director.
The vendor demo starts in 10 minutes.
You are Alex. The company is growing fast and the resume pile is unmanageable. An AI screening vendor is about to pitch you their tool.
YOUR SCREEN
The demo looks great: "95% accuracy." The rep says bias is "handled by the algorithm." Legal is copied on the thread, asking if anyone reviewed it.
"Bias is handled by the algorithm."
Six months in, a rejected candidate's lawyer asks for records on how your AI screened her application.
You notice the screener auto-rejects applicants with employment gaps.
Spot the proxy.
Select every model input that can proxy a protected characteristic. Then check your work.
Where can AI touch HR?
SAFETY
101
This certifies that
has completed Module 4 - The Bias: AI in hiring and HR decisions on with a safety score of /100 in of active time.
Safety score - fairness: how your decisions held up, graded 0-100.
Objective: Spot proxy discrimination in AI-assisted decisions and require human review.
Seat time ~10-25 minutes. Verify this certificate at aisafety101.com/verify.
Evidence on record: module completion, seat time, final score, and certificate ID. This certificate ID verifies in your firm's admin report. A team certificate issues when every enrolled employee completes the full curriculum.
Your one rule to keep: AI can assist employment decisions, but the organization remains responsible for the process. Validate the tool, test outcomes for adverse impact, apply appropriate human review, and document the controls.
Next: The Deepfake. This module was about decisions AI makes about people. Next: a person who is not a person at all - your CFO, on video, asking for $25M.