During the call, we heard from two speakers: April Dunlap, Policy Administrator for Arizona’s Department of Economic Security and Professor Michele Gilman, Venable Professor of Law and Associate Dean for Faculty Research and Development at the University of Baltimore School of Law.
This policy brief offers recommendations to policymakers relating to the computational and human sides of facial recognition technologies based on a May 2020 workshop with leading computer scientists, legal scholars, and representatives from industry, government, and civil society
This primer is written for a non-technical audience to increase understanding of the terminology, applications, and difficulties of evaluating facial recognition technologies.
Research from the Department of Labor shows that document management systems reduce barriers for claimants and help states be more efficient. With additional improvements and investment, these systems can be even more effective in serving the public and reducing backlogs in times of crisis.
These guidelines provide technical requirements for federal agencies implementing digital identity services and are not intended to constrain the development or use of standards outside of this purpose. This guideline focuses on the enrollment and verification of an identity for use in digital authentication.
National Institute of Standards and Technology (NIST)
Recent studies demonstrate that machine learning algorithms can discriminate based on classes like race and gender. This academic study presents an approach to evaluate bias present in automated facial analysis algorithms and datasets.
This article discusses the challenges of today’s centralized identity management and investigates current developments regarding verifiable credentials and digital wallets.
