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.
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.
A research report examining how privacy and security risks are unevenly experienced across socioeconomic, racial, and ethnic groups, and how digital inequality shapes people’s exposure to harm and access to protective resources.
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)
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 outlines ethical frameworks and best practices for responsibly collecting and using demographic and other sensitive data to build equitable digital products.
This report reviews global AI governance tools, highlighting their importance in ensuring trustworthy AI, while identifying gaps and risks in their effectiveness, and offering recommendations to improve their development, oversight, and integration into policy frameworks.
Digital IDs can improve convenience, but they risk surveillance, data misuse, and exclusion if not designed with privacy, security, and accessibility safeguards.
