U.S. Leadership in AI: A Plan for Federal Engagement in Developing Technical Standards and Related Tools
U.S. LEADERSHIP IN AI: A Plan for Federal Engagement in Developing Technical Standards and Related Tools
This plan outlines a federal strategy for engagement in the development of technical standards and related tools for artificial intelligence, supporting reliable, robust, and trustworthy AI systems. Prepared in response to Executive Order 13859, the document emphasizes active U.S. government participation in voluntary consensus standards development, public-private partnerships, and international cooperation. It identifies priority areas for standardization—such as safety, risk management, and trustworthiness—and provides practical steps for federal agencies to guide their involvement.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Federal agency officials, policymakers, researchers, and standards developers seeking guidance on U.S. priorities and engagement strategies for AI technical standards.
What the document contains
The document addresses federal engagement strategies for the development of AI technical standards and related tools. It outlines priority areas for standardisation, definitions of trustworthy AI, mechanisms for public-private collaboration, and guidelines for agency participation ranging from monitoring to leading standards bodies.
The document does not establish legally binding regulations or enforcement mechanisms for private industry adoption, nor does it provide detailed technical specifications for specific commercial algorithms.
- The U.S. federal government must play an active, purpose-driven role in supporting and engaging in AI technical standards development to maintain national economic and security leadership.
- Standards should focus on nine key areas, including concepts and terminology, data, human interactions, metrics, networking, performance testing, safety, risk management, and trustworthiness.
- Technical standards must be complemented by related tools such as standardized datasets, reference use cases, benchmarks, challenge problems, and testing methodologies.
- Federal agencies should prioritize involvement in standards efforts that are consensus-based, inclusive, open, transparent, and globally relevant.
- The plan recommends bolstering interagency coordination, promoting focused research on trustworthiness and risk management, expanding public-private partnerships, and strategically engaging internationally.
· Executive Summary · 1. Standards and Artificial Intelligence · 2. U.S. Government AI Standards Priorities · 3. Recommended Federal Government Standards Actions to Advance U.S. AI Leadership · Appendix I: Definitions · Appendix II: AI standards · Appendix III: AI related tools · Appendix IV: The assignment and approach · Appendix V: Request for information · Appendix VI: Workshop agenda
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Fairness
3/5Non-discrimination and equitable treatment
U.S. government agencies should prioritize involvement in AI standards efforts that are: inclusive and accessible, open and transparent, consensus-based, globally relevant, and non-discriminatory.
Executive Summary
screening score · 2026-10-23
Human Dignity
2/5Respect for the inherent worth of persons
Human-centered to ensure that human interactions and values—including abilities, disabilities, diversity—are considered during AI data collection, model development, testing, and deployment.
Section 2A
screening score · 2026-10-23
Human Oversight
2/5Humans remain in control of consequential decisions
In considering the applications of AI in areas such as criminal justice and health care, organizations should design, build and deploy AI systems that leverage human judgment and responsibility where they are needed.
Section 1D
screening score · 2026-10-23
Privacy
3/5Protection of personal data and private life
Privacy considerations should be included in any standards governing the collection, processing, sharing, storage, and disposal of personal information
Section 1F
screening score · 2026-10-23
Transparency
3/5Openness about how AI systems work and are used
Trustworthiness standards include guidance and requirements for accuracy, explainability, resiliency, safety, reliability, objectivity, and security.
Executive Summary
screening score · 2026-10-23
Impact Assessment
3/5Required assessment of an AI system's risks/impacts before or during use
Ideally, these aspects of AI should be considered early in the design process and tested during the development and use of AI technologies.
Section 1B
screening score · 2026-10-23