This annotated bibliography compiles key resources on data linkage and integration for research and statistical purposes, focusing on best practices, governance, and technical considerations.
This report explores policy options Utah and other states can adopt to mitigate benefit cliffs, which occur when small income increases lead to sudden loss of public assistance.
This panel discussion from the Academy's 2025 Policy Summit explores the intersection of artificial intelligence (AI) and public benefits, examining how technological advancements are influencing policy decisions and the delivery of social services.
The Digital Benefit Network's Digital Identity Community of Practice held a session to hear considerations from civil rights technologists and human-centered design practitioners on ways to ensure program security while simultaneously promoting equity, enabling accessibility, and minimizing bias.
This tip sheet provides guidance for child welfare and social service agencies on how to effectively and respectfully collect SOGIE (Sexual Orientation, Gender Identity, and Expression) data.
U.S. Department of Health and Human Services (HHS)
The report documents how grantees implemented specialized Transitional Living Programs for LGBTQ youth and young adults aging out of foster care, highlighting approaches, challenges, and lessons learned.
This case study examines how Michigan’s Department of Health and Human Services uses data practices to advance racial equity in child welfare through identity-informed data collection and anonymous decision-making.
U.S. Department of Health and Human Services (HHS)
DSN Spotlights celebrate our members’ stories, lift up actionable takeaways for other practitioners, and put the examples we host in the Digital Government Hub in context. Submit a proposal by May 31, 2025 to be featured in our series as part of our open call for submissions.
This report offers a detailed assessment of how AI and emerging technologies could impact the Social Security Administration’s disability benefits determinations, recommending guardrails and principles to protect applicant rights, mitigate bias, and promote fairness.
