Responsible Artificial Intelligence (RAI) in U.S. Federal Government : Principles, Policies, and Practices

Federal AI use requires robust governance mechanisms: The paper emphasizes that AI systems used in government decision-making—particularly those requiring minimal human involvement—must be governed through transparency and accountability measures to ensure responsible deployment, especially given the high stakes of government decisions affecting citizens.

Responsible AI is now an interdisciplinary field: The rapid advancement and proliferation of AI/ML across both private and public sectors has created new challenges for regulators, leading to the emergence of Responsible AI (RAI) as a distinct research area that brings together multiple disciplines to address governance gaps.

Executive Orders and policies are shaping federal AI practices: The paper reviews the current regulatory landscape through analysis of Executive Orders, policies, and frameworks, indicating that the U.S. federal government is actively developing formal guidance to govern how agencies should implement AI responsibly.

Practical implementation is underway in federal agencies: The Census Bureau and other federal agencies are moving beyond principles to concrete projects and practices, demonstrating that responsible AI implementation is not merely theoretical but is being actively tested and refined in real government operations.

Assessment toolkits are being developed for accountability: The paper references a Responsible AI Assessment Toolkit, suggesting that federal agencies are creating practical tools to evaluate and ensure AI systems meet responsible use standards before and during deployment.