This report offers best practices for public agencies implementing digital identity verification, emphasizing privacy, equity, and security in the delivery of government services.
A panel of experts discuss the application of civil rights protections to emerging AI technologies, highlighting potential harms, the need for inclusive teams, and the importance of avoiding technology-centric solutions to social problems.
This report outlines best practices for developing transparent, accessible, and standardized public sector AI use case inventories across federal, state, and local governments
BenCon 2024 explored state and federal AI governance, highlighting the rapid increase in AI-related legislation and executive orders. Panelists emphasized the importance of experimentation, learning, and collaboration between government levels, teams, agencies, and external partners.
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 resource provides state agencies and their implementation partners with context on how and why to conduct a Digital Identity Risk Management (DIRM) process, as well as a new spreadsheet-based tool to guide agency teams through the process.
This report analyzes lawsuits that have been filed within the past 10 years arising from the use of algorithm-driven systems to assess people’s eligibility for, or the distribution of, public benefits. It identifies key insights from the various cases into what went wrong and analyzes the legal arguments that plaintiffs have used to challenge those systems in court.
The Digital Benefit Network's Digital Identity Community of Practice held a session to hear considerations from civil rights technologists and human-centered design practitioners on ways to ensure program security while simultaneously promoting equity, enabling accessibility, and minimizing bias.
This post argues that for the types of large-scale, organized fraud attacks that many state benefits systems saw during the pandemic, solutions grounded in cybersecurity methods may be far more effective than creating or adopting automated systems.
