This case study details the development of a document extraction prototype to streamline benefits application processing through automated data capture and classification.
This resource page provides comprehensive information on the state's initiatives, policies, training, and governance related to the adoption and implementation of generative AI technologies in government operations.
This blog post shares findings from the February 2025 AI Trust Study on Canada.ca, revealing how Canadians perceive government AI and what builds trust.
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)
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.
The Maryland Information Technology Master Plan 2025 lays out the state’s strategy to modernize IT, expand digital services, and strengthen infrastructure to better serve residents and government agencies.
This framework provides a structured approach for ensuring responsible and transparent use of AI systems across government, emphasizing governance, data integrity, performance evaluation, and continuous monitoring.
A report that defines what effective “human oversight” of AI looks like in public benefits delivery and offers practical guidance for ensuring accountability, equity, and trust in algorithmic systems.
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.
The team conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
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.
