Library
Discover the latest innovations, learn about promising practices, and find out what’s coming next with best-in-class resources from trusted sources.
Is there something missing from our library?

Search for the topic or resource you're looking for, or use the filters to narrow down results below.
-
Rules as Code Community of Practice
The DBN’s Rules as Code Community of Practice (RaC CoP) creates a shared learning and exchange space for people working on public benefits eligibility and enrollment systems — and specifically people tackling the issue of how policy becomes software code. The RaC CoP brings together cross-sector experts who share approaches, examples, and challenges. Participants are from state, local, tribal, territorial, and federal government agencies, nonprofit organizations, academia, and private sector companies. We host recurring roundtable conversations and an email group for asynchronous updates, insights, and assistance.
-
Gathering feedback with customer panels
To improve the .gov registrar, 18F and CISA created customer panels to gather feedback, opinions, and suggestions. Using a customer-centric approached enabled 18F and CISA to identify areas for improvement, build a product roadmap, and establish relationships with users.
-
What’s in a name? A survey of strong regulatory definitions of automated decision-making systems
The Electronic Privacy Information Center (EPIC) emphasizes the necessity of adopting broad regulatory definitions for automated decision-making systems (ADS) to ensure comprehensive oversight and protection against potential harms.
-
What is a (Digital) Identity Wallet? A Systematic Literature Review
The report examines how current remote identity proofing methods can create barriers to Medicaid enrollment and suggests improvements to ensure equitable access for all applicants.
-
What Are Generative AI, Large Language Models, and Foundation Models?
What exactly are the differences between generative AI, large language models, and foundation models? This post aims to clarify what each of these three terms mean, how they overlap, and how they differ.
-
The Privacy-Bias Trade-Off
This policy brief explores how federal privacy laws like the Privacy Act of 1974 limit demographic data collection, undermining government efforts to conduct equity assessments and address algorithmic bias.
-
The Ohio Benefits Program is “BOT” In
This award documentation from the National Association of State Chief Information Officers (NASCIO) explains how agencies in Ohio used automation to support administration of public benefits programs.
-
The difference between digital identity, identification, and ID
This style guide from Caribou Digital outlines how to talk about identity in a digital age.
-
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing
This paper explores design considerations and ethical tensions related to auditing of commercial facial processing technology.
-
Looking before we leap: Exploring AI and data science ethics review process
This report explores the role that academic and corporate Research Ethics Committees play in evaluating AI and data science research for ethical issues, and also investigates the kinds of common challenges these bodies face.
-
Large Language Models (LLMs): An Explainer
In this blog post, CSET’s Natural Language Processing (NLP) Engineer, James Dunham, helps explain LLMs in plain English.
-
Disability, Bias, and AI
This report explores key questions that a focus on disability raises for the project of understanding the social implications of AI, and for ensuring that AI technologies don’t reproduce and extend histories of marginalization.