Government agencies at all levels collect administrative data in the course of their day-to-day operations. While such information has been used to determine effectiveness through program evaluations for many years, program administrators view it increasingly as a valuable resource that can also be used to improve program performance. For example, administrative data from employment and public benefits programs such as Temporary Assistance for Needy Families (TANF) can offer insights into families’ unmet needs and ways to improve services.
Technology enables governments to engage in “pilot” projects to see where they are headed and course-correct along the way, as opposed to evaluating the results over the course of multiple years. Delivery-driven government utilizes technology and “pilot” projects to see institutions and processes through the eyes of users, allowing for more effective service delivery.
Part of the $1.9 trillion recovery package that Biden signed into law includes a $1 billion grant to the Technology Modernization Fund. The fund’s purpose is to help federal agencies upgrade their cybersecurity and modernize their technology. The TMF is a chance for federal agencies to move toward a responsive model of government, where people quickly and easily access the resources they need.
mRelief recently completed a research study to investigate whether there are specific parts of the Supplemental Nutrition Assistance Program (SNAP; also known as food stamps) benefits application process that make it difficult to complete. We conducted interviews with mRelief users and SNAP outreach workers (individuals whose job responsibilities include providing SNAP application assistance in person or over the phone) in Illinois. We also conducted group interviews with SNAP outreach workers to collaborate with them to uncover findings and develop recommendations.
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
This report explores technologies that have the potential to significantly affect employment and job quality in the public sector, the factors that drive choices about which technologies are adopted and how they are implemented, how technology will change the experience of public sector work, and what kinds of interventions can protect against potential downsides of technology use in the public sector. The report categories technologies into five overlapping categories including manual task automation, process automation, automated decision-making systems, integrated data systems, and electronic monitoring.
The guidelines for bias-free language contain both general guidelines for writing about people without bias across a range of topics and specific guidelines that address the individual characteristics of age, disability, gender, participation in research, racial and ethnic identity, sexual orientation, socioeconomic status, and intersectionality.
NIST has created a voluntary AI risk management framework, in partnership with public and private sectors, to promote trustworthy AI development and usage.
National Institute of Standards and Technology (NIST)
This book explores the current capabilities, future possibilities, and necessary governance for facial recognition technology. The report discusses legal, societal, and ethical implications of the technology, and recommends ways that federal agencies and others developing and deploying the technology can mitigate potential harms and enact more comprehensive safeguards.
National Academies of Sciences, Engineering, and Medicine
