This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This paper examines the challenges U.S. state and local digital service teams face in retaining talent and offers strategies to improve retention and team stability.
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.
Recent studies demonstrate that machine learning algorithms can discriminate based on classes like race and gender. This academic study presents an approach to evaluate bias present in automated facial analysis algorithms and datasets.
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 brief outlines the U.S. federal government’s framework to identify, reduce, and address administrative burdens through a series of executive orders, legislative actions, and updated policies focused on improving customer experience and increasing access to government benefits.
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
The Digital Identity Community of Practice kick-off event featured key resources, a new research publication on account creation and identity proofing, and insights from multiple speakers.
This toolkit provides guidance to protect participant confidentiality in human services research and evaluation, including legal frameworks, risk assessment strategies, and best practices.
U.S. Department of Health and Human Services (HHS)
This report analyzes the growing use of generative AI, particularly large language models, in enabling and scaling fraudulent activities, exploring the evolving tactics, risks, and potential countermeasures.
Led by the Digital Benefits Network in partnership with Public Policy Lab, the Digital Doorways research project amplifies the lived experiences of beneficiaries to provides new insights into people’s experiences with digital identity processes and technology in public benefits. This executive summary gives an overview of the project’s findings.
