An infographic-style brief that maps the roles and responsibilities of key state leaders involved in governing the development, acquisition, use, and oversight of artificial intelligence in public-sector programs.
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 report offers best practices for public agencies implementing digital identity verification, emphasizing privacy, equity, and security in the delivery of government services.
An overview video describing the Digital Identity Risk Management process outlined in NIST's Digital Identity Guidelines, which organizations can use to develop a risk-based approach to identity management.
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.
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.
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 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.
Digital IDs can improve convenience, but they risk surveillance, data misuse, and exclusion if not designed with privacy, security, and accessibility safeguards.
