Defending AI-Assisted Layoffs: The Algorithm Is Now the Evidence

This session equips employment and labor counsel with an overview of reductions in force and the use and abuse of AI-assisted technologies to facilitate the process. Drawing on recent litigation confronting AI uses in employment, as well as an active state regulatory patchwork, attendees will learn the do’s and don’ts of privileged bias audits, OWBPA and WARN Act compliance, and multi-state notice obligations. Attorneys completing this session will be able to identify the benefits and potential pitfalls of relying on AI-assistance to administer their RIFs, structure attorney-directed bias testing to preserve privilege, and document the RIF in a manner that anticipates and protects businesses in discovery.

This session examines the litigation defense of lawsuits involving the use of AI in the employment decisionmaking processes. The presentation will examine some of the first major cases to reach the courts — including Does 1–26 v. Meta Platforms and Mobley v. Workday — to map the actual battlefield of motions practice, discovery disputes, and preliminary injunction responses. Attorneys will learn how courts are reacting to TRO and injunction requests; how AI bias-testing data, manager AI prompts, and algorithmic performance dashboards are relevant in discovery; and what the emerging state regulatory patchwork means for defense exposure. Attendees leave equipped with an understanding of pre-litigation strategies to incorporate AI into the employment decision-making process; AI employment litigation framework; discovery considerations relative to AI; and the human-in-the-loop documentation required to mount a credible defense.