This paper analyzes the unique challenges of conducting participatory design in large-scale public projects, focusing on stakeholder management, fostering engagement, and integrating participatory methods into institutional transformation.
This resource is a research paper examining the role of the public safety net in insuring job losers against income loss, analyzing which government programs provide financial support and how benefits vary based on pre-job loss income levels.
The OECD report explores the concept of "Rules as Code" (RaC), proposing a transformation in government rulemaking by developing machine-consumable regulations alongside human-readable versions.
Organisation for Economic Co-operation and Development (OECD)
This article explores how AI and Rules as Code are turning law into automated systems, including how governance focused on transparency, explainability, and risk management can ensure these digital legal frameworks stay reliable and fair.
Well-designed, user-focused tools that allow for simple application are key to ensuring that families most in need receive the Child Tax Credit. Reaching these households will require a robust effort from the IRS to create user-friendly tools in partnership with organizations with a direct connection to eligible recipients.
Medicaid and SNAP have reduced racial and ethnic disparities in healthcare access and food security, but some administrative and eligibility policies continue to create inequitable barriers.
This study assesses five commercial RIdV solutions for equity across demographic groups and finds that two are equitable, while two have inequitable performance for certain demographics.
This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
This study examines public attitudes toward balancing equity and efficiency in algorithmic resource allocation, using online advertising for SNAP enrollment as a case study.
This paper argues that a human rights framework could help orient the research on artificial intelligence away from machines and the risks of their biases, and towards humans and the risks to their rights, helping to center the conversation around who is harmed, what harms they face, and how those harms may be mitigated.
This study examines how individuals assess administrative burdens and how these views change over time within the context of the Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC).
