This report highlights 5 key takeaways from the Aspen Institute Financial Security Program's 2022 Benefits Forum, where 55 experts from various sectors discussed solutions for improving public and private benefits to better support workers and their families.
This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
Programs like Medicaid and SNAP are managed at the federal level, administered at the state level, and often executed at the local level. Because there are so many in-betweens, there is significant duplicated effort, demonstrating the need to simplify eligibility rules to facilitate easier implementation.
This brief provides research recommendations to improve programs serving LGBT youth, focusing on homelessness and sexual health education services funded by the U.S. Department of Health and Human Services.
U.S. Department of Health and Human Services (HHS)
Takeaways from a workshop focusing on applying human-centered design to government artificial intelligence (AI) projects, led by Elham Ali, Researcher from the Beeck Center for Social Impact and Innovation.
Companies have been developing and using artificial intelligence (AI) for decades. But we've seen exponential growth since OpenAI released their version of a large language model (LLM), ChatGPT, in 2022. Open-source versions of these tools can help agencies optimize their processes and surpass current levels of data analysis, all in a secure environment that won’t risk exposing sensitive information.
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)
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.
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 Spanish translated fact sheet provides strategies for organizations to support and affirm LGBTQIA2S+ youth and young adults experiencing homelessness.
U.S. Department of Health and Human Services (HHS)
