An in-depth report that examines how states use automated eligibility algorithms for home and community-based services (HCBS) under Medicaid and assesses their implications for access and fairness.
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)
A policy brief outlining concrete actions states can take to regulate tenant screening practices and reduce harm from inaccurate reports, automated scoring, and discriminatory impacts in the rental housing market.
Guidance outlining how Australian government agencies can train staff on artificial intelligence, covering key concepts, responsible use, and alignment with national AI ethics and policy frameworks.
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.
This post introduces EPIC's exploration of actionable recommendations and points of agreement from leading A.I. frameworks, beginning with the National Institute of Standards and Technology's AI Risk Management Framework.
This report provides an overview of the task force’s work in assessing, guiding, and recommending policies for the safe, ethical, and effective use of generative AI across Alabama’s executive-branch agencies.
State of Alabama Generative Artificial Intelligence (GenAI) Task Force
This framework outlines USDA’s principles and approach to support States, localities, Tribes, and territories in responsibly using AI in the implementation and administration of USDA’s nutrition benefits and services. This framework is in response to Section 7.2(b)(ii) of Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.
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 publicly-available suite of policy templates and knowledge-sharing tools offered by the GovAI Coalition (via the City of San José) to help public agencies launch or refine responsible AI governance programs.
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.
