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.
Hear perspectives on topics including centering beneficiaries and workers in new ways, digital service delivery, digital identity, and automation.This video was recorded at the Digital Benefits Conference (BenCon) on June 14, 2023.
These guidelines from the National Institutes of Standard and Technology provide technical requirements for federal agencies implementing digital identity services.
National Institute of Standards and Technology (NIST)
This article describes the General Services Administration’s efforts to get a limited number of state and local governments to try login.gov with their federally funded programs.
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 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
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. These guidelines focus on the authentication of subjects interacting with government systems over open networks, establishing that a given claimant is a subscriber who has been previously authenticated.
National Institute of Standards and Technology (NIST)
This book explores the current capabilities, future possibilities, and necessary governance for facial recognition technology. The report discusses legal, societal, and ethical implications of the technology, and recommends ways that federal agencies and others developing and deploying the technology can mitigate potential harms and enact more comprehensive safeguards.
National Academies of Sciences, Engineering, and Medicine
Governments around the world are digitizing how they deliver services to citizens. And yet, without a secure and reliable way for people to prove their identity online, digital transformation efforts face a considerable barrier. This panel discussion, hosted by the Information Technology & Innovation Foundation (ITIF), focuses on the potential benefits and concerns surrounding digital ID and identity proofing technology as well as the legal and technical barriers for use.
Information Technology & Innovation Foundation (ITIF)
