The team examined how AI, specifically LLMs, could streamline the case review process for SNAP applications to alleviate the burden on case workers while potentially improving accuracy.
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.
Learn how to use generative AI to quickly create unemployment insurance translations that are accurate, easy to understand, and tailored to your state.
This framework provides voluntary guidance to help employers use AI hiring technology in ways that are inclusive of people with disabilities, while aligning with federal risk management standards.
This action plan outlines Oregon’s strategic approach to adopting AI in state government, emphasizing ethical use, privacy, transparency, and workforce readiness.
This framework provides practical guidance, detailed reference designs, and example solutions to help organizations securely adopt and operationalize Zero Trust principles across diverse IT environments.
National Institute of Standards and Technology (NIST)
This toolkit provides guidance to protect participant confidentiality in human services research and evaluation, including legal frameworks, risk assessment strategies, and best practices.
U.S. Department of Health and Human Services (HHS)
Guidance from Washington Technology Solutions (WaTech) outlining the state’s framework for responsibly procuring, deploying, and monitoring generative AI technologies across government agencies.
A virtual event showcasing how one city applied technology, including artificial intelligence, to streamline municipal code administration and reduce bureaucratic friction.
The New York State Office of Information Technology established guidelines for the acceptable and responsible use of Artificial Intelligence technologies by state entities.
New York State Office of Information Technology Services
