This article explores how anticipatory logics—drawing from foresight, futures thinking, and design—are shaping the future of government by creating space for innovative policy approaches, public participation, and proactive governance.
This article discusses the challenges of today’s centralized identity management and investigates current developments regarding verifiable credentials and digital wallets.
This introductory guide explains the core concepts of digital identity and how they apply to public benefits programs. This guide is the first part of a suite of voluntary resources from the BalanceID Project: Enabling Secure Access and Managing Risk in SNAP and Medicaid.
A unified taxonomy and tooling suite that consolidates AI risks across frameworks and links them to datasets, benchmarks, and mitigation strategies to support practical AI governance.
A national survey of low-wage workers showing that administrative burdens in SNAP and Medicaid are common and strongly linked to food hardship, healthcare hardship, and chronic illness.
An academic research paper introducing SHADES, a multilingual benchmark designed to evaluate how large language models (LLMs) generate and reinforce stereotypes across different languages and cultural contexts.
An article examining how automation and AI are being used in welfare systems, arguing that digital benefits administration often reproduces longstanding patterns of surveillance, exclusion, and inequality.
This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
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.
Center for Security and Emerging Technology (CSET)
This resource is a research paper examining the role of the public safety net in insuring job losers against income loss, analyzing which government programs provide financial support and how benefits vary based on pre-job loss income levels.
This article analyses ‘digital distortions’ in Rules as Code, which refer to disconnects between regulation and code that arise from interpretive choices in the encoding process.
