Designing a Privileged AI Governance Program for Employment: Bias Audits, Controls and Ongoing Oversight

Employers are increasingly deploying artificial intelligence (AI) across the talent life cycle, from candidate sourcing and ranking to pre-hire assessments, to onboarding, performance reviews, development, promotions, and retention. 

While these tools promise efficiency and consistency, they also introduce heightened legal risk if they produce biased outcomes. 

Many states, localities, and international jurisdictions require proactive AI auditing, transparency, and governance to ensure that AI-enabled employment decisions are fair, compliant, and defensible.

Quick Hits

• Jurisdictions such as California, New York City, Colorado, Illinois, and the European Union (EU) variously require (or plan to require) and encourage bias testing, notices, transparency, and, in some cases, public summaries. 
• AI involvement can create substantial legal risk, even when humans make the final decisions; AI-influenced scores, rankings, or screens can still be treated by regulatory authorities as decision-making, triggering validation, bias-testing, notice, and transparency duties.
• Legally privileged bias audits can anchor AI governance efforts by channeling audits through legal counsel, maintaining an inventory and classification of tools, setting clear policies and vendor obligations, and conducting ongoing monitoring and remediation.

Login and download this resource which includes:

• Tips Related to the Scope and Focus of Auditing
• Best Practice Considerations
• A Practical 90-day Roadmap for Building an AI Governance Program

Authors: Lauren B. Hicks and T. Scott Kelly