This internal glossary defines key terms and concepts related to automating enrollment proofs for public benefits programs to support shared understanding among product and policy teams.
The report examines how AI deployment across state and local public administration such as chatbots, voice transcription, content summarization, and eligibility automation are reshaping government work.
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.
A unified taxonomy and tooling suite that consolidates AI risks across frameworks and links them to datasets, benchmarks, and mitigation strategies to support practical AI governance.
This strategy document establishes a governance framework and roadmap to ensure responsible, trustworthy, and effective AI use across Canadian federal institutions.
A profile on FormFest spearker’s Barry Roeder, Barabara Deffenderfer, Glenn Brown, and Izzie Hirschy-Reyes highlighting how the Bay Area Housing Finance Authority and its partners use AI and human-centered design to streamline paper housing applications.
This FormFest profile highlights Riverside County’s pilot of AI-powered interviews that streamline benefit applications, reducing bureaucratic burden on families in crisis while freeing caseworkers to focus on human connection.
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.
An interactive chatbot that helps SNAP participants and the public ask questions and receive guidance about SNAP work and community engagement requirements in conversational form.
A case study explaining how a predictive, data-driven machine-learning model was developed to detect unauthorized cash benefit withdrawals more quickly and accurately in California.
