Service Delivery Area: Benefits
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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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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.
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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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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.
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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.
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Democratizing AI: Principles for Meaningful Public Participation
In this policy brief and video, Michele Gilman summarizes evidence-based recommendations for better structuring public participation processes for AI, and underscores the urgency of enacting them.
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Controlling Large Language Models: A Primer
Concerns over risks from generative artificial intelligence systems have increased significantly over the past year, driven in large part by the advent of increasingly capable large language models. But, how do AI developers attempt to control the outputs of these models? This primer outlines four commonly used techniques and explains why this objective is so challenging.
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Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing
This paper introduces a framework for algorithmic auditing that supports artificial intelligence system development end-to-end, to be applied throughout the internal organization development lifecycle.
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Better Together? An Evaluation of AI-Supported Code Translation
This research explores how software engineers are able to work with generative machine learning models. The results explore the benefits of generative code models and the challenges software engineers face when working with their outputs. The authors also argue for the need for intelligent user interfaces that help software engineers effectively work with generative code models.
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Better Identity at Five Years: An Updated Policy Blueprint and Report Card
In 2018 the Better Identity Coalition released a Policy Blueprint outlining five key initiatives that to solve the majority of America’s challenges in the digital identity space. This report from 2024 grades progress on each of the original Blueprint’s five key initiatives – as well as the 19 items that were contained in the “action plan” to support those initiatives.