HI, I'M ANDREW.

Andrew is a data scientist specializing in workforce analysis. He is the Auditor General at Aspen Analytics, a data analytics firm he founded in 2006. The firm has a decorated and documented 18-year history of serving the largest international employers.

He authored Aspen's audits which present compliance and/or risks related to AI, wage parity, and human capital disclosures, guidance, and regulations.

Andrew also executed strategic workforce planning for the US federal government in the coveted position of an Operations Research Senior Analyst. Andrew was granted specialized permission to maintain his authorship and operations of Aspen while serving his country.

Andrew received a Master of Science in Business Analytics from the Stern School of Business at New York University and undergraduate degrees from the Smeal School of Business at The Pennsylvania State University. He contributed to the authoring of ISO standards related to Human Capital metrics, has presented at dozens of international conferences regarding human resource analysis, and is a regular source for workforce and labor market insight to the Wall Street Journal.

He lives happily a few hundred yards from the Atlantic Ocean with his family in southern New Jersey and is an avid golfer and baseball fan.

AI, Lawsuits & Deepfakes: HR’s New Risk Frontier

Tuesday, April 7, 10:15 AM

As AI reshapes the HR function—from sourcing to onboarding—HR leaders face a new frontier of reputational, regulatory, and cybersecurity risks. This session delivers a high-impact, compliance-forward briefing on the legal, ethical, and operational hazards emerging from AI adoption in workforce management. We’ll dissect landmark cases like Mobley v. Workday, explore the implications of evolving state and federal AI regulations, and expose the growing threat of synthetic identities and deepfake profiles in hiring pipelines.

Participants will gain actionable insights into:

AI governance frameworks for HR that align with ISO, EEOC, and emerging state-level mandates (e.g., New York City’s AEDT law, California’s CPRA).

Legal precedents and litigation trends, including the Mobley v. Workday case and its implications for algorithmic bias, vendor liability, and due diligence in HR tech procurement.

Cybersecurity vulnerabilities in talent acquisition, including fake candidate profiles, credential spoofing, and social engineering risks targeting recruiters.

Reputation management strategies for HR leaders navigating public scrutiny, regulatory audits, and media exposure tied to AI missteps.

Audit-ready practices for defensible documentation, human-in-the-loop validation, and risk flagging across AI-assisted hiring workflows.

This session is designed for CHROs, HR compliance officers, and talent leaders seeking to future-proof their organizations against reputational fallout and regulatory penalties. Attendees will leave with risk assessment methods and starting frameworks for integrating AI responsibly into HR operations, ensuring defensibility, transparency, and trust at every stage of the employee lifecycle.

Learning Objectives:

1. Identify key regulatory developments affecting AI use in HR and their compliance implications.

2. Analyze legal risks and reputational exposure from recent litigation involving algorithmic hiring tools.

3. Implement cybersecurity protocols to detect and prevent fraudulent candidate activity.

4. Review audit-ready governance strategies for AI-assisted HR processes.