Based on user interviews with families across the United States who navigated the Medicaid renewal process, this report offers insights and recommendations for improving the experience of renewing Medicaid and other benefits.
This essay explains why the Center on Privacy & Technology has chosen to stop using terms like "artificial intelligence," "AI," and "machine learning," arguing that such language obscures human accountability and overstates the capabilities of these technologies.
Hear perspectives on topics including centering beneficiaries and workers in new ways, digital service delivery, digital identity, and automation.This video was recorded at the Digital Benefits Conference (BenCon) on June 14, 2023.
The article discusses the phenomenon of model multiplicity in machine learning, arguing that developers should be legally obligated to search for less discriminatory algorithms (LDAs) to reduce disparities in algorithmic decision-making.
The paper hopes to stimulate discussions towards an ethical protocol for better practice in BI experiments and provide a useful resource to those working on, or interested in, BI research.
A panel of experts discuss the application of civil rights protections to emerging AI technologies, highlighting potential harms, the need for inclusive teams, and the importance of avoiding technology-centric solutions to social problems.
Propel describes how its mobile app outreach campaign helped millions of Medicaid enrollees navigate renewal during the post-pandemic “unwinding” by driving action through notifications, messaging, and in-app tools.
The RFI summary report consolidates submissions received from the open-source software community and details twelve activities that members of the OS3I plan—or have completed—in 2024-2025.
This resource helps individuals with aligning their work with the needs of the communities they wish to serve, while reducing the likelihood of harms and risks those communities may face due to the development and deployment of AI technologies.
