The Policy2Code Prototyping Challenge explored utilizing generative AI technology to translate U.S. government policies for public benefits into plain language and code, culminating in a Demo Day where twelve teams showcased their projects for feedback and evaluation.
The team aimed to automate applying rules efficiently by creating computable policies, recognizing the need for AI tools to convert legacy policy content into automated business rules using Decision Model Notation (DMN) for effective processing and monitoring.
This case study describes how Nava is working with the General Services Administration, Fearless, and the U.S. Postal Service to design, build, and deliver a new in-person identity verification service to nearly 20,000 USPS locations
Ad Hoc has found that product operations can help scale impact by putting objective indicators at the center of product decision-making. The team has seen success in supporting product thinking at agencies like the Department of Veterans Affairs (VA), where they made it easier for Veterans to access employment and education assistance and for caregivers to receive needed support.
Less than 10% of applications for VA health care are submitted digitally. This article describes how the U.S. Digital Service partnered with the Health Eligibility Center to change that, making it possible for anyone with an internet connection to apply anytime, anywhere, from any device.
Data provided by the NYC Mayor’s Office for Economic Opportunity regarding benefit, program, and resource information for over 80 health and human services available to NYC residents in all eleven local law languages.
