An Investigative Report
The Meritocracy Myth
AI promised to make hiring objective. Instead, it codifies and amplifies human bias at an industrial scale, creating massive, unseen liabilities. This interactive report explores the risks and provides a framework for responsible governance.
of Fortune 500 companies use AI to sift candidates, creating a new class of automated gatekeepers.
of resumes are rejected by an algorithm before ever being seen by a human recruiter.
of employers believe their own AI systems screen out qualified candidates.
The Anatomy of Algorithmic Bias
Bias in AI is not a bug; it's a feature learned from flawed data. Understanding its forms is the first step to mitigation. Click on each card to learn more.
From Theory to Tangible Risk
The threat of algorithmic discrimination is not hypothetical. It has materialized in high-profile lawsuits and regulatory action, creating significant legal and reputational exposure.
Visualizing Disparate Impact
The "disparate impact" doctrine is a key legal risk. It holds that a neutral hiring practice (like an AI tool) is illegal if it disproportionately harms a protected group, regardless of intent. The chart below simulates how a biased algorithm can create legally indefensible outcomes compared to a fair process.
Case Studies in Failure
A Framework for Responsible Governance
Mitigating algorithmic risk requires a continuous, multi-faceted strategy. This framework outlines the key pillars of a responsible AI governance program.