Findem completes independent AI bias audit with Warden AI

How did Findem perform in the Warden AI audit?

The Warden AI audit is designed to reflect how systems behave in the real world. It evaluates observed outcomes rather than stated intent, and focuses on the questions teams today need to answer:

• Are candidates evaluated consistently using the same criteria?
• Do outcomes differ across protected groups in ways that raise concern?
• Can results be documented clearly and reviewed over time?

The audit found that Findem’s applicant-matching practices met Warden AI’s fairness thresholds across key groups. These thresholds assess whether outcomes are distributed equitably across protected groups, without favoring or disadvantageing any particular demographic.

“When AI is part of hiring, it’s important to understand how it’s behaving in real use, not just how it was designed,” said Tina Shah Paikeday, General Manager, Findem. “Independent review helps us do that and gives our customers clearer visibility into the results.”

Why ongoing assurance matters as AI scales hiring decisions

Organizations have moved from AI experimentation to AI integration. According to the World Economic Forum, more than 65% of chief strategy officers expect AI and emerging technologies to shape business strategies over the next 5 years. As adoption grows, so does scrutiny, especially around bias.

Bias is a concern not just for HR, but for legal, compliance, procurement, and executive leadership. It often increases when teams are under pressure, when incomplete information and tight timelines push people toward familiar signals that feel efficient but aren’t reliable predictors of success. Training alone hasn’t solved this problem at scale.

Tina Shah Paikeday addressed this in her piece, “Slow Thinking Fast: How AI Trumped Human Bias.” She argues that most bias problems come from fast, intuitive decisions and unstructured processes, not bad intentions. When AI is designed around structured rubrics, consistent criteria, and comprehensive data, it can do that slow, deliberate “system two” thinking at machine speed, expanding talent pools and improving both diversity and quality. 

Used this way, AI doesn’t replace human judgment; it supports it, acting as a scalable bias interrupter instead of a bias amplifier. Ongoing, independently maintained assurance makes that oversight visible and keeps conversations grounded in evidence rather than assumptions.

How Findem applies responsible AI to applicant matching

Findem’s applicant-matching practices are designed to support, not replace human decision making. Candidate profiles are evaluated against employer-defined job requirements, such as skills and experience. Each profile is assessed individually, using the same criteria, to surface candidates who align with what the role actually requires.

This structure reduces reliance on shallow heuristics early in the process and keeps the focus on job-relevant signals. Hiring decisions remain human-led, with context and judgment applied where they matter most. Because AI behavior can change as data and organizational needs evolve, responsible use also requires ongoing oversight. 

Findem’s work with Warden AI is part of that broader, responsible approach to AI. Our platform is designed to assist human judgment, focus evaluation on objective, job-related criteria, and reduce dependence on signals that often encode bias. 

Explore the AI Assurance Dashboard to view ongoing, independently maintained audit results for Findem’s applicant-matching practices and learn more about our responsible approach to AI.