The IRS Direct File Pilot Program After Action Report evaluates the 2024 pilot of a free, government-run tax filing system, assessing taxpayer participation, user experience, and potential for future expansion.
The OECD AI Principles promote use of AI that is innovative and trustworthy and that respects human rights and democratic values. The principles were adopted in 2019; this webpage provides an overview of the principles and key terms.
Organisation for Economic Co-operation and Development (OECD)
This report shares the results of our comprehensive content audit and heuristic evaluation of eligibility pre-screeners, including ratings on security, mobile-friendly design, accessibility, and more.
As a part of Benefit Data Trust (BDT)’s Medicaid Churn Learning Collaborative, BDT has created a memo describing policy options and state examples for Medicaid administrators to reduce churn for non-MAGI Medicaid enrollees when the federal public health emergency ends.
Medicaid and SNAP have reduced racial and ethnic disparities in healthcare access and food security, but some administrative and eligibility policies continue to create inequitable barriers.
The U.S. Department of Labor provides a playbook to help state workforce agencies enhance communication with unemployment claimants by offering clear, proactive updates on claim statuses, thereby improving claimant satisfaction and reducing call center inquiries.
This study evaluates the use of RPA technology by three states to automate SNAP administration, focusing on repetitive tasks previously performed manually.
This essay explains why the Center on Privacy & Technology has chosen to stop using terms like "artificial intelligence," "AI," and "machine learning," arguing that such language obscures human accountability and overstates the capabilities of these technologies.
This case study describes Nava's work with the state of Montana’s Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) agency to build an API prototype, which is part of Nava's larger work inform a national API standard.
This report summarizes findings and observations on the implementation of Phase 1 of the U.S. Department of Labor’s Open UI Initiative, highlighting effective strategies, challenges, opportunities, and recommendations for supporting states’ UI modernization efforts.
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.
