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Digital Distortions and Interpretive Choices: A Cartographic Perspective on Encoding Regulation
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.
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Moving Because of Unaffordable Housing and Disrupted Social Safety Net Access Among Children
This article shows how moves because of unaffordable housing can disrupt social safety net access for children.
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Shared Values/Conflicting Logics: Working Around E-Government Systems
This paper describes results from fieldwork conducted at a social services site where the workers evaluate citizens' applications for food and medical assistance submitted via an e-government system. These results suggest value tensions that result - not from different stakeholders with different values - but from differences among how stakeholders enact the same shared value in practice.
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Exposing Error in Poverty Management Technology: A Method for Auditing Government Benefits Screening Tools
This paper introduces a method for auditing benefits eligibility screening tools in four steps: 1) generate test households, 2) automatically populate screening questions with household information and retrieve determinations, 3) translate eligibility guidelines into computer code to generate ground truth determinations, and 4) identify conflicting determinations to detect errors.
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Envisioning a Human-AI collaborative system to transform policies into decision models
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.
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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.
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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.
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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.
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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.
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Digital Identity: Emerging Trends, Debates and Controversies
This academic review covers the broad range of arguments, trends, and patterns from the emerging field of digital identity scholarship.
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Digital Identity and Inclusion: Tracing Technological Transitions
This article explores technological transformations underway in the digital identity sector.
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Digital Identities and Verifiable Credentials
This article discusses the challenges of today’s centralized identity management and investigates current developments regarding verifiable credentials and digital wallets.