While much has been written on digital government as a general trend, this working paper instead examines how civic tech is changing American government, focusing on an influential constellation of actors who shape the understanding and implementation of technological opportunities.
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?
This study explores the causal impacts of income on a rich array of employment outcomes, leveraging an experiment in which 1,000 low-income individuals were randomized into receiving $1,000 per month unconditionally for three years, with a control group of 2,000 participants receiving $50/month.
This study describes the potential of human-centered design principles to identify burdens, reducing the effects of what we label as administrative checkpoints.
This article examines the matrix of vulnerabilities that low-income populations face from the widespread collection of big data and predictive analytics.
This research article explores how framing income eligibility guidelines in either dollar amounts or as a percentage of the Federal Poverty Line (FPL) affects public attitudes toward program access and administrative burdens in Medicaid and SNAP.
This discussion paper advocates for states to use the implementation of OBBBA (One Big Beautiful Bill Act) as a catalyst to build integrated, cross-agency data systems.
This foundational article develops the concept of administrative burden, defining it as the learning, psychological, and compliance costs individuals face when interacting with government, and argues that these burdens are often shaped by political choices.
Journal of Public Administration Research and Theory
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 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.