This case study highlights how states used data sharing and targeted outreach to boost WIC enrollment among Medicaid and SNAP participants, improving program reach and reducing disparities.
This policy brief explores how federal privacy laws like the Privacy Act of 1974 limit demographic data collection, undermining government efforts to conduct equity assessments and address algorithmic bias.
This guide outlines ethical frameworks and best practices for responsibly collecting and using demographic and other sensitive data to build equitable digital products.
This blog explains that verifiable digital credentials (VDCs) are cryptographically secure digital versions of physical credentials (like driver’s licenses or diplomas) stored in digital wallets that can be presented and verified online or in person.
National Institute of Standards and Technology (NIST)
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 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.
This academic paper examines how federal privacy laws restrict data collection needed for assessing racial disparities, creating a tradeoff between protecting individual privacy and enabling algorithmic fairness in government programs.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This framework is a logical structure for classifying, organizing, and communicating complex activities involved in making decisions about and taking action on enterprise data.
This guide introduces privacy-enhancing technologies (PETs) and provides practical guidance for government agencies on selecting and implementing them to securely use, share, and protect sensitive data.
Digital IDs can improve convenience, but they risk surveillance, data misuse, and exclusion if not designed with privacy, security, and accessibility safeguards.
