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 and filters
Search for the topic or resource you're looking for, or use the filters to narrow down results below.
Results
-
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.
-
POVERTY LAWGORITHMS: A Poverty Lawyer’s Guide to Fighting Automated Decision-Making Harms on Low-Income Communities
This guide, directed at poverty lawyers, explains automated decision-making systems so lawyers and advocates can better identify the source of their clients' problems and advocate on their behalf. Relevant for practitioners, this report covers key questions around automated decision-making systems.
-
Automated Decision-Making Systems and Discrimination
This guidebook offers an introduction to the risks of discrimination when using automated decision-making systems. This report also includes helpful definitions related to automation.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
Challenging the Use of Algorithm-driven Decision-making in Benefits Determinations Affecting People with Disabilities
This report analyzes lawsuits that have been filed within the past 10 years arising from the use of algorithm-driven systems to assess people’s eligibility for, or the distribution of, public benefits. It identifies key insights from the various cases into what went wrong and analyzes the legal arguments that plaintiffs have used to challenge those systems in court.