Topic: Mitigating Harm + Bias
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Access Denied: Faulty Automated Background Checks Freeze Out Renters
This reporting explores how algorithms used to screen prospective tenants, including those waiting for public housing, can block renters from housing based on faulty information.
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The Social Life of Algorithmic Harms
This series of essays seeks to expand our vocabulary of algorithmic harms to help protect against them.
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ITEM 10: How a Small Legal Aid Team Took on Algorithmic Black Boxing at Their State’s Employment Agency (And Won)
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.
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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.
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Unpacking How Long-Standing Civil Rights Protections Apply to Emerging Technologies like AI at BenCon 2024
A panel of experts discuss the application of civil rights protections to emerging AI technologies, highlighting potential harms, the need for inclusive teams, and the importance of avoiding technology-centric solutions to social problems.
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I Am Not a Number
In early 2023, Wired magazine ran four pieces exploring the use of algorithms to identify fraud in public benefits and potential harms, deeply exploring cases from Europe.
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Less Discriminatory Algorithms
The article discusses the phenomenon of model multiplicity in machine learning, arguing that developers should be legally obligated to search for less discriminatory algorithms (LDAs) to reduce disparities in algorithmic decision-making.
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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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AI Technologies Today at BenCon 2024
Sarah Bargal provides an overview of AI, machine learning, and deep learning, illustrating their potential for both positive and negative applications, including authentication, adversarial attacks, deepfakes, generative models, personalization, and ethical concerns.
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How to determine whether AI is an appropriate solution for public sector challenges
This toolkit provides a checklist of items to help determine whether AI-powered tools are appropriate for specific use cases in the public sector.
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Screened & Scored in the District of Columbia
This report by EPIC investigates how automated decision-making (ADM) systems are used across Washington, D.C.’s public services and the resulting impacts on equity, privacy, and access to benefits.
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Surveillance, Discretion and Governance in Automated Welfare
This academic article develops a framework for evaluating whether and how automated decision-making welfare systems introduce new harms and burdens for claimants, focusing on an example case from Germany.