Artificial intelligence is rapidly transforming human resources operations. From AI-powered recruiting platforms that screen résumés and rank candidates, to onboarding tools that personalize new-hire experiences, performance management systems that predict attrition, identity verification solutions using biometrics, and platforms administering ERISA-governed benefit plans, employers are increasingly relying on third-party vendors whose products are built on or

Senate Bill (SB) 1130, legislation that would establish criminal penalties for certain uses of wearable recording devices, continues to move through the California legislature. I’ve had the honor of discussing this measure with staff of the bill’s sponsor, California State Senator Eloise Gómez Reyes, and anticipate there will be more efforts to enact laws

For much of the past two years, discussions regarding generative artificial intelligence (AI) in professional services seems to have focused on lawyers, and perhaps for good reason. Courts have sanctioned attorneys who submitted briefs containing fabricated case citations. In response to these and other mishaps, several state bars issued ethics opinions often applying existing professional

Artificial intelligence has quickly become part of the modern lawyer’s toolkit. Attorneys are using generative AI platforms to assist with legal research, drafting, editing, and document review. While these technologies can improve efficiency, a growing number of court filings across the country demonstrate a significant risk: AI-generated hallucinations, including fabricated case citations, nonexistent authorities, and

Employers are increasingly using artificial intelligence and other algorithmic tools to support workplace decisions, including recruiting, screening, interviewing, promotion, workforce planning, and performance management. These tools can improve efficiency and consistency, but they also introduce important compliance, reputational, and employee-relations considerations. Two concepts that often arise in AI governance are bias audits and validation testing.