Summary:
As government agencies, housing providers, healthcare systems, and employers increasingly rely on automated decision-making, errors can have life-altering consequences for the people affected. This presentation examines real-world housing, disability, and civil rights cases where automated processes, data inaccuracies, and administrative failures resulted in significant harm.
Participants will learn how to identify automation-driven failures, evaluate the evidence behind institutional decisions, document procedural breakdowns, and develop effective advocacy strategies. The session will also introduce emerging concepts in AI accountability, validation, and transparency that can help legal professionals better assess decisions made by automated systems.
Featuring Teresa Villa, Founder of JusticeTree.ai.
Learning Objectives:
• Identify common risks associated with automated decision-making systems.
• Recognize how data errors can cascade across multiple agencies and
institutions.
• Analyze housing, disability, and civil rights cases involving
administrative automation.
• Apply evidence-based methods for investigating and challenging
questionable decisions.
• Understand emerging approaches to AI accountability and validation.
GOOGLE MEET LINK WILL BE SENT THE DAY BEFORE.
