This primer is written for a non-technical audience to increase understanding of the terminology, applications, and difficulties of evaluating facial recognition technologies.
This webinar provides insight on behavioral science concepts and how states can put such ideas into practice to tailor engagement, messaging, and independence planning, as well as promote participation in SNAP E&T programs.
This article describes how Code for America conducted qualitative research within its GetCalFresh application by asking families to tell them about their familial, housing, and financial situations. From client messages, they gathered information regarding how to make changes to their product to keep their work people-centered.
The CARES Act Stimulus Payments Report by New America analyzes the implementation and impact of the Economic Impact Payments (stimulus checks) distributed during the COVID-19 pandemic, highlighting accessibility challenges and policy recommendations for future direct payments.
Policy changes are often dynamic and occur quickly, but they can only create impact once implemented. The Eligibility APIs Initiative at 18F shares an example from their work that shows the potential for rapid, accurate policy implementation as code.
This tool kit brings together emergent best practices, workflows, and tools that communities, educators, mutual aid groups, designers, artists and activists are using for community building, and how design needs to change to best suit people, right now.
New America spoke to to the people at the frontlines of the pandemic—professional caregivers, family caregivers, parents, and essential workers—to understand the policy interventions people need most. This report discusses ideas for policymakers, private sector leaders, and community innovators to use in pursuit of work-family justice and equity across race, gender, and class.
This reporting explores how algorithms used to screen prospective tenants, including those waiting for public housing, can block renters from housing based on faulty information.
This report explores Michigan’s implementation of the Pandemic Electronic Benefit Transfer (P-EBT) program. Drawing on interviews from individuals within the Michigan Department of Health and Human Services and input from SNAP participants via surveys distributed using the Fresh EBT app, this report provides insights into the strategies that enabled Michigan to roll out an entirely new program quickly and effectively.
Little is known about how agencies are currently using AI systems, and little attention has been devoted to how agencies acquire such tools or oversee their use.
