This report analyzes how administrative burdens in SNAP caused one in eight working-age adults to lose benefits in 2024, with future federal policy changes expected to worsen disruptions
Guidance outlining how Australian government agencies can train staff on artificial intelligence, covering key concepts, responsible use, and alignment with national AI ethics and policy frameworks.
This report highlights key findings from the Rules as Code Community of Practice, including practitioners' challenges with complex policies, their desire to share knowledge and resources, the need for increased training and support, and a collective interest in developing open standards and a shared code library.
In this video, Susan S. Gibson, chair of the Pandemic Response Accountability Committee's (PRAC) Identity Fraud and Redress Working Group, speaks with Jeremy Grant of the Better Identity Coalition, about the challenges of identity fraud for benefits program during the COVID-19 pandemic.
Digitizing public benefits policy will make the biggest impact for administrators and Americans, but only if it happens at the highest level of government.
This guide provides a detailed overview summarizing the many initiatives and activities from Congress, the White House, federal agencies, and coalitions which may impact the digital identity landscape in the United States, including at state, local, Tribal, and territorial levels.
An analysis showing that a proposed plan to shift some cost of SNAP benefits to states could push nearly 900,000 additional people into poverty during a recession.
This framework provides a structured approach for ensuring responsible and transparent use of AI systems across government, emphasizing governance, data integrity, performance evaluation, and continuous monitoring.
A detailed guide outlining how states can minimize coverage losses and administrative burden while implementing new Medicaid work requirements established under the 2025 federal reconciliation law.
A report that defines what effective “human oversight” of AI looks like in public benefits delivery and offers practical guidance for ensuring accountability, equity, and trust in algorithmic systems.
This publication explains the fundamentals of state IEE systems—including the technology, opportunities, risks, and stakeholders involved. It is a resource for state officials, advocates, funders, and tech partners working to implement these systems.
