This guide outlines ethical frameworks and best practices for responsibly collecting and using demographic and other sensitive data to build equitable digital products.
This report analyzes the rise of digital driver’s licenses (DDLs) and warns that, without strong safeguards, they could threaten privacy, civil liberties, and equitable access to identification.
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 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 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.
This report offers best practices for public agencies implementing digital identity verification, emphasizing privacy, equity, and security in the delivery of government services.
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 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.
