A case study documenting how a modular API layer was built to support a state-level paid family and medical leave program, improving interoperability, scalability, and user experience.
This reporting explores how algorithms used to screen prospective tenants, including those waiting for public housing, can block renters from housing based on faulty information.
Well-designed, user-focused tools that allow for simple application are key to ensuring that families most in need receive the Child Tax Credit. Reaching these households will require a robust effort from the IRS to create user-friendly tools in partnership with organizations with a direct connection to eligible recipients.
The team introduced "Policy Pulse," a tool to help policy analysts understand laws and regulations better by comparing current policies with their original goals to identify implementation issues.
To assist states in closing digital skill gaps and preparing for digital equity planning, this brief offers key questions and resources for state leaders to consider.
This field guide is written for digital services and technology leaders working in government agencies at the federal, state, or local level. It’s meant to highlight the power of product thinking to government digital services. With this guide, agencies can start moving from a project management mindset to a product-based approach to delivering services.
This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
The team examined how AI, specifically LLMs, could streamline the case review process for SNAP applications to alleviate the burden on case workers while potentially improving accuracy.
This study assesses five commercial RIdV solutions for equity across demographic groups and finds that two are equitable, while two have inequitable performance for certain demographics.
