This analysis examines the surge in U.S. state-level AI legislation in 2023, highlighting enacted laws, proposed bills, and emerging regulatory trends.
This report analyzes lawsuits that have been filed within the past 10 years arising from the use of algorithm-driven systems to assess people’s eligibility for, or the distribution of, public benefits. It identifies key insights from the various cases into what went wrong and analyzes the legal arguments that plaintiffs have used to challenge those systems in court.
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This report examines how governments can effectively build, attract, and retain AI talent to responsibly integrate artificial intelligence into public service delivery.
Louisiana issued an RFI to identify solutions that can provide a technology platform for determining eligibility and managing cases across multiple human services programs.
These principles and best practices for AI developers and employers to center the well-being of workers in the development and deployment of AI in the workplace and to value workers as the essential resources they are.
This guidance document provides a framework for developing an agency-wide data strategy that aligns data governance, management, and analytics with organizational goals and service delivery.
This product validation summary deck explores federal opportunities to automate cross-program enrollment proofs and reduce manual verification burdens.
This blog post shares findings from the February 2025 AI Trust Study on Canada.ca, revealing how Canadians perceive government AI and what builds trust.
The team conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
