This nine-minute video, produced after the completion of the TANF Data Collaborative (TDC) Pilot, features staff members from the California, Colorado, Minnesota, and Virginia TANF agencies reflecting on their challenges, accomplishments, and general experiences during the pilot. In particular, they describe their research questions and discuss building data capacity, integrating datasets, networking with other states, increasing collaboration between state and county agencies, learning new technical skills, and the benefits of being able to draw from diverse skillsets, all within the context of the TDC Pilot.
Our existing maze of family tax benefits — including the CTC, Earned Income Tax Credit (EITC), Child and Dependent Care Tax Credit (CDCTC), and head of household (HoH) filing status — has several structural deficiencies that make overhauling the system a prerequisite for any effort to boost support for families with children. The report offers several options for expanding and streamlining family tax benefits to address these issues.
Algorithmic impact assessments (AIAs) are an emergent form of accountability for organizations that build and deploy automated decision-support systems. This academic paper explores how to co-construct impacts that closely reflects harms, and emphasizes the need for input of various types of expertise and affected communities.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This guide touches on everything from Code for America’s core research philosophy, to our approach to ethics and trauma-informed research, to specific research methods. It also includes plenty of practical tips on planning and executing research, as well as how to synthesize your findings into action.
This article discusses Code for America’s research into the user experience of applying or Medicaid, SNAP, TANF, WIC, and LIHEAP in the United States. They found that user experience applying for benefits programs varies greatly by (and often within) each state.
This toolkit offers strategies and tools to help agencies build the culture and infrastructure needed to apply data analysis routinely, effectively, and accurately – referred to in this publication as “sustainable data use.”
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)
This resource contains specific examples that highlight the advantages of designing reusable code components, software tools, or design formats. This guide also illustrates the possibilities for connecting new components to existing system infrastructure.
The Guide to Robotic Process Automation, including the RPA Playbook provides detailed guidance for federal agencies starting a new RPA program or evolving an existing one.
