Created for use in the Digital Doorways research project, this design stimuli shows the steps of submitting an application, sharing personal information, and verifying identity for New York's online application for Medicaid.
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.
The Benefits Enrollment Field Guide looks at the landscape of America’s safety net benefits experience in 2023 and tracks the differences from our 2019 assessment based on expanded evaluation criteria. It also highlights successful paths to equitable, human-centered experiences. It examines online enrollment for Modified Adjusted Gross Income (MAGI) Medicaid, SNAP, TANF, the Child Care Assistance Program (CCAP), and WIC.
In May 2020, Stanford's HAI hosted a workshop to discuss the performance of facial recognition technologies that included leading computer scientists, legal scholars, and representatives from industry, government, and civil society. The white paper this workshop produced seeks to answer key questions in improving understandings of this rapidly changing space.
This piece highlights promising design patterns for account creation and identity proofing in public benefits applications. The publication also identifies areas where additional evidence, resources, and coordinated federal guidance may help support equitable implementations of authentication and identity proofing, enabling agencies to balance access and security.
The Digital Benefits Network at the Beeck Center for Social Impact + Innovation at Georgetown University and Public Policy Lab co-hosted a webinar presenting breaking research on beneficiary experiences with digital identity processes in public benefits.
This report offers best practices for public agencies implementing digital identity verification, emphasizing privacy, equity, and security in the delivery of government services.
This article advises government agencies to prioritize cybersecurity methods over AI-driven approaches when combating identity fraud in benefits programs, highlighting potential risks that automated systems pose to legitimate applicants.
The Login.gov program roadmap articulates the values of the Login.gov program, outlines strategic priorities, and documents how the program is approaching nuanced identity topics.
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)
