This report investigates how D.C. government agencies use automated decision-making (ADM) systems and highlights their risks to privacy, fairness, and accountability in public services.
An in-depth report that examines how states use automated eligibility algorithms for home and community-based services (HCBS) under Medicaid and assesses their implications for access and fairness.
In this piece, the Digital Benefits Network shares several sources—from journalistic pieces, to reports and academic articles—we’ve found useful and interesting in our reading on automation and artificial intelligence.
NYC's My File NYC and New Jersey's unemployment insurance system improvements demonstrate how successful digital innovations can be scaled across various programs, leveraging trust-building, open-source technology, and strategic partnerships.
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.
The team conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
In this interview, Code for America staff members share how client success, data science, and qualitative research teams work together to consider the responsible deployment of artificial intelligence (AI) in responding to clients who seek assistance with three products.
This case study details the development of a document extraction prototype to streamline benefits application processing through automated data capture and classification.
