Through our research understanding the government digital service field and what workers in this field need, we want to help strengthen those existing roles and establish more pathways for promotion and career support, as well as help other teams recognize the value of these skills and create new roles.
Through a field scan, this paper identifies emerging best practices as well as methods and tools that are becoming commonplace, and enumerates common barriers to leveraging algorithmic audits as effective accountability mechanisms.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
The report examines how current remote identity proofing methods can create barriers to Medicaid enrollment and suggests improvements to ensure equitable access for all applicants.
Annual Computers, Software, and Applications Conference (COMPSAC)
What exactly are the differences between generative AI, large language models, and foundation models? This post aims to clarify what each of these three terms mean, how they overlap, and how they differ.
Center for Security and Emerging Technology (CSET)
In the article, researchers examines how administrative burdens in waitlist management for subsidized childcare in Massachusetts have led to significant reductions in the number of families awaiting assistance, potentially obscuring the true extent of unmet need.
This academic paper examines how federal privacy laws restrict data collection needed for assessing racial disparities, creating a tradeoff between protecting individual privacy and enabling algorithmic fairness in government programs.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This report presents new national survey data showing how benefits cliffs and asset limits negatively affect the economic mobility of low-wage workers in the U.S.
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 examines how the 2021 expansion of the Child Tax Credit (CTC) influenced housing affordability and living arrangements for low-income families.
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 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.
This study examines the adoption and implementation of AI chatbots in U.S. state governments, identifying key drivers, challenges, and best practices for public sector chatbot deployment.
