A training course on using artificial intelligence (AI) tools to de-jargonize government language, with a tutorial on turning a complex piece of government writing into simpler and easier-to-understand language for government employees and residents alike.
This report examines how the U.S. federal government can enhance the efficiency and equity of benefit delivery by simplifying eligibility rules and using a Rules as Code approach for digital systems.
This bill authorizes the U.S. Digital Service to make a grant to a state, Indian tribe, or local government to establish or support a team of relevant experts dedicated to modernizing the delivery of government services to the public through information technology. A state, tribe, or local government may receive up to two such grants.
Handbook by 18F designed for executives, budget specialists, legislators, and other “non-technical” decision-makers who fund or oversee state government technology projects that receive federal funding and implement the necessary technology to support federal programs. It aids in setting projects up for success by asking the right questions, identifying the right outcomes, and equally important, empowering decision-makers with a basic knowledge of the fundamental principles of modern software design.
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.
Monthly SNAP participation data for the United States and every state, from October 1988 through the latest month published by USDA Food and Nutrition Service (generally a 3-month lag).
