This panel discussion from the Academy's 2025 Policy Summit explores the intersection of artificial intelligence (AI) and public benefits, examining how technological advancements are influencing policy decisions and the delivery of social services.
This introductory guide explains the core concepts of digital identity and how they apply to public benefits programs. This guide is the first part of a suite of voluntary resources from the BalanceID Project: Enabling Secure Access and Managing Risk in SNAP and Medicaid.
Digital IDs can improve convenience, but they risk surveillance, data misuse, and exclusion if not designed with privacy, security, and accessibility safeguards.
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.
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 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 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.
The Center for Democracy and Technology's brief clarifies misconceptions about artificial intelligence (AI) in government services, emphasizing the need for precise definitions, awareness of AI's limitations, recognition of inherent biases, and acknowledgment of the significant resources required for effective implementation.
This analysis explores the dual nature of mobile state IDs, highlighting their potential to enhance digital identity verification while raising significant privacy and equity concerns.
This article advises government agencies to prioritize cybersecurity methods over AI-driven approaches when combating identity fraud in benefits programs, highlighting potential risks that automated systems pose to legitimate applicants.
