This article analyses ‘digital distortions’ in Rules as Code, which refer to disconnects between regulation and code that arise from interpretive choices in the encoding process.
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.
The exclusion of agricultural and domestic workers—predominantly African Americans—from the 1935 Social Security Act's unemployment insurance program is analyzed as a result of international policy diffusion rather than solely domestic racial politics.
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 article examines how the decentralization of safety net programs after welfare reform has led to growing inequality in benefit generosity and access across U.S. states.
A recent study challenges the common belief that income support programs like SNAP reduce employment, finding that for individuals with a work history, receiving SNAP benefits can actually increase long-term employment.
This paper concludes that the substantial COVID-19 unemployment insurance expansion had limited disincentive effects on job searches, particularly among lower-income individuals, despite high wage replacement rates.
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.
This article analyzes the translation of law into computer code and the use of automated decision-making systems in government to make legal distinctions. Specifically, how are algorithmic decisions tied to law, and what happens when legal effects are mediated through technologies?
A case study describing how Massachusetts is building long-term public-sector capacity to deliver people-centered digital services by strengthening in-house expertise, shared tools, and agency-embedded support.
This guide is a practical introduction to Digital Service Teams (DSTs) for state and local governments. It is designed to help leaders interested in standing up new government DSTs understand what they are, why they exist, and how they are structured, staffed, funded, and more.
