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Case Study: HR & Talent

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Fixing AI Bias in Hiring Before It Costs Millions

An HR team implemented AI-driven hiring tools to speed up candidate screening. Instead of improving efficiency, the AI amplified hiring bias, disproportionately filtering out diverse candidates and putting the company at risk of discrimination lawsuits.

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The Problem

- Audited AI-driven hiring decisions to identify and eliminate biased screening criteria.
- Established governance frameworks to ensure AI compliance with fair hiring laws.
- Implemented transparency measures, so HR teams could see why candidates were rejected.

What We Did

✔ Reduced AI-driven hiring bias by 40%, ensuring compliance with fair hiring practices.
✔ Increased candidate diversity without sacrificing quality or efficiency.
✔ Built HR and executive trust—AI decisions were now explainable and legally defensible.

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Results

AI in hiring is a lawsuit waiting to happen if left unchecked. If your AI can’t explain why it rejects candidates, HR and legal teams will have to answer for it. We ensured this company’s hiring AI was fair, transparent, and legally sound—before regulators or lawsuits forced the issue.

The Takeaway

Danny Katz Consulting

We help companies fix knowledge chaos, streamline AI governance, and build systems that actually work. Whether it’s unsearchable knowledge silos, AI making bad decisions due to bad data, or compliance teams struggling with operational execution—we solve the problems that stall productivity, increase risk, and waste time.