This UN report warns against the risks of digital welfare systems, emphasizing their potential to undermine human rights through increased surveillance, automation, and privatization of public services.
The White House Office of Science and Technology Policy has identified five principles that should guide the design, use, and deployment of automated systems to protect the American public in the age of artificial intelligence. These principles help provide guidance whenever automated systems can meaningfully impact the public’s rights, opportunities, or access to critical needs.
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.
This report offers a detailed assessment of how AI and emerging technologies could impact the Social Security Administration’s disability benefits determinations, recommending guardrails and principles to protect applicant rights, mitigate bias, and promote fairness.
The AI RMF Playbook offers organizations detailed, voluntary guidance for implementing the NIST AI Risk Management Framework to map, measure, manage, and govern AI risks effectively.
National Institute of Standards and Technology (NIST)
This is a searchable tool that compiles and categorizes over 4,700 policy recommendations submitted in response to the U.S. government's 2025 Request for Information on artificial intelligence policy.
The report examines how AI deployment across state and local public administration such as chatbots, voice transcription, content summarization, and eligibility automation are reshaping government work.
This report analyzes the growing use of generative AI, particularly large language models, in enabling and scaling fraudulent activities, exploring the evolving tactics, risks, and potential countermeasures.
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 recap of a community innovation hackathon in Seattle where technologists and students used AI to prototype solutions that help youth discover and access local programs and services.
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.
