The state of Indiana developed a policy framework for the ethical and efficient use of artificial intelligence (AI) within state agencies. The policy adopts the National Institute of Standards and Technology’s AI Risk Management Framework to manage potential risks effectively. It also details the applicability of the actions undertaken by the Office of the Chief Data Officer (OCDO) to enable the deployment of trustworthy AI systems.
Research identified five key obstacles that researchers, activists, and advocates face in efforts to open critical public conversations about AI’s relationship with inequity and advance needed policies.
An event recap from one of FormFest 2024's breakout sessions featuring speakers from the Canadian Digital Service and the National Head Start Association.
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This paper introduces a framework for algorithmic auditing that supports artificial intelligence system development end-to-end, to be applied throughout the internal organization development lifecycle.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This report explores how despite unresolved concerns, an audit-centered algorithmic accountability approach is being rapidly mainstreamed into voluntary frameworks and regulations.
This framework provides voluntary guidance to help employers use AI hiring technology in ways that are inclusive of people with disabilities, while aligning with federal risk management standards.
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.
