The Decide Methods help you derive insights from the information gathered during the Discovery phase. You’ll validate initial assumptions, develop a deeper understanding of workflows and processes, and develop design hypotheses.
This research brief summarizes the ideas and recommendations from sessions with dozens of cross-sector stakeholders within the technology ecosystem to identify conditions for better, healthier, more secure digital ecosystems that could help guide the next generation of open protocols and platforms.
This brief highlights key takeaways from APHSA’s work on young families, starting with an overview of the young families work and its early years, followed by key takeaways and highlights from its final year, ending with opportunities for future work in the young families space.
American Public Human Services Association (APHSA)
The toolkit provides strategies for state and local WIC agencies to enhance enrollment by utilizing data from Medicaid and SNAP for cross-program data matching and targeted outreach.
This paper introduces a method for auditing benefits eligibility screening tools in four steps: 1) generate test households, 2) automatically populate screening questions with household information and retrieve determinations, 3) translate eligibility guidelines into computer code to generate ground truth determinations, and 4) identify conflicting determinations to detect errors.
This reporting explores how algorithms used to screen prospective tenants, including those waiting for public housing, can block renters from housing based on faulty information.
This book is an in-depth exploration of federal programs and controversial legislation demonstrating that administrative burden has long existed in policy design, preventing citizens from accessing fundamental rights. Further discussion of how policymakers can minimize administrative burden to reduce inequality, boost civic engagement, and build an efficient state.
Digitizing public benefits policy will make the biggest impact for administrators and Americans, but only if it happens at the highest level of government.
This academic paper examines predictive optimization, a category of decision-making algorithms that use machine learning (ML) to predict future outcomes of interest about individuals. Through this examination, the authors explore how predictive optimization can raise concerns that make its use illegitimate and challenge claims about predictive optimization's accuracy, efficiency, and fairness.
Starting November 1, 2023, the Centers for Medicare & Medicaid Service (CMS) began asking three new optional sexual orientation and gender identity (SOGI) questions on the single, streamlined application developed by the Secretary. This guidance gives instructs states on the process for modifying SOGI questions in their applications.
This Blueprint is a whole-of-government effort that aims to provide a resource to assist federal decisionmakers in leveraging social and behavioral science to improve policy and program design and delivery.
