This report outlines best practices for developing transparent, accessible, and standardized public sector AI use case inventories across federal, state, and local governments
NYC's My File NYC and New Jersey's unemployment insurance system improvements demonstrate how successful digital innovations can be scaled across various programs, leveraging trust-building, open-source technology, and strategic partnerships.
This article explores how legal documents can be treated like software programs, using methods like software testing and mutation analysis to enhance AI-driven statutory analysis, aiding legal decision-making and error detection.
The OECD AI Principles promote use of AI that is innovative and trustworthy and that respects human rights and democratic values. The principles were adopted in 2019; this webpage provides an overview of the principles and key terms.
Organisation for Economic Co-operation and Development (OECD)
This playbook provides federal agencies with guidance on implementing AI in a way that is ethical, transparent, and aligned with public trust principles.
U.S. Department of Health and Human Services (HHS)
AI resources for public professionals on responsible AI use, including a course showcasing real-world applications of generative AI in public sector organizations.
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 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 analyzes the growing use of generative AI, particularly large language models, in enabling and scaling fraudulent activities, exploring the evolving tactics, risks, and potential countermeasures.
A practical, step-by-step guide for government agencies to design, implement, and evaluate community engagement efforts around the use of artificial intelligence.
An academic research paper introducing SHADES, a multilingual benchmark designed to evaluate how large language models (LLMs) generate and reinforce stereotypes across different languages and cultural contexts.
