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A Report to Congress: Steps to Implement Recommendations 

Regarding “U.S. Leadership in Artificial Intelligence (AI): A Plan for 

Federal Engagement in Developing Technical Standards and Related 

Tools”

This report is in response to two requirements in House Report 116-455 accompanying the

Consolidated Appropriations Act, 2021 (P.L 116-260):

1) “U.S. Leadership in AI. —The Committee commends NIST for the completion of the plan, ‘‘U.S.

Leadership in AI,’’ and encourages NIST to implement its recommendations, as appropriate.

Further, the Committee directs NIST, on behalf of the Department, and in consultation with the

Office of Personnel Management, the Interagency Committee on Standards Policy, other

interagency groups, and Federal agencies, as NIST considers appropriate, to develop a clear

career development and promotion path that recognizes and encourages participation in and

expertise in AI standards development within the Federal workforce. NIST is also directed, in

coordination with appropriate Federal agencies, to understand AI standards strategies and

initiatives of standards organizations, foreign governments and entities, to the extent

practicable. No less than 180 days after the enactment of this Act, the Department shall submit

a report to the Committee on the steps it has taken to implement the recommendations of the

U.S. Leadership in AI plan.”

2) “AI Talent. —The Committee believes the Department should develop a clear career

development and promotion path that encourages participation and expertise in AI standards

and standards development and directs the Department to report to the Committee on these

efforts no later than 180 days after enactment of this Act.”

Background of the AI Standards Plan

On August 9, 2019, the National Institute of Standards and Technology (NIST) issued “U.S. 

Leadership in AI: A Plan for Federal Engagement in Developing Technical Standards and Related 

Tools”1(AI Standards Plan or Plan), which addresses:

• Federal priority needs for standardization of AI systems development and deployment;

• Identification of standards development entities in which federal agencies should seek

membership with the goal of establishing or supporting United States technical

leadership roles; and

• Opportunities for and challenges to United States leadership in standardization related

to AI technologies.

This plan was required by Executive Order 13859, which recognizing the importance of artificial 

intelligence (AI) to the future of the U.S. economy and national security, directed federal 

1 https://www.nist.gov/system/files/documents/2019/08/10/ai_standards_fedengagement_plan_9aug2019.pdf.

March 1, 2022
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agencies to take a variety of steps designed to ensure the nation maintains its leadership 

position in AI research and development and deployment. Among its objectives, the EO aims to 

“Ensure that technical standards minimize vulnerability to attacks from malicious actors and 

reflect federal priorities for innovation, public trust, and public confidence in systems that use 

AI technologies; and develop international standards to promote and protect those priorities.” 

Recommendations in the AI Standards Plan

NIST engaged with stakeholders from the private and public sectors in developing the AI 

Standards Plan. Recommendations in the Plan called for actions by federal agencies to: 

• Bolster AI standards-related knowledge, leadership, and coordination among federal 

agencies to maximize effectiveness and efficiency.

• Promote focused research to advance and accelerate broader exploration and 

understanding of how aspects of trustworthiness can be practically incorporated within 

standards and standards-related tools.

• Support and expand public-private partnerships to develop and use AI standards and 

related tools to advance reliable, robust, and trustworthy AI.

• Strategically engage internationally to advance AI standards for U.S. economic and 

national security needs.

While the Plan was developed by NIST – which has specific leadership and coordination 

responsibilities for AI standards – many federal agencies are instrumental in carrying out the 

Plan’s recommendations and the goals of the EO.

This Report to Congress

This document summarizes progress made in carrying out the recommendations of the 2019 AI 

Standards Plan, fulfilling a provision in the House Report accompanying the Commerce, Justice, 

Science, and Related Agencies Appropriations Bill, 2021.

2 As the Federal Government’s AI 

standards coordinator, NIST continues to work with other government agencies in the United 

States and around the world, the private sector, and other stakeholders to regularly review and 

carry out the AI Standards Plan. 

1. Steps Taken to Implement Recommendations in the Plan

The Plan provided guidance regarding priorities and appropriate levels of engagement in AIstandards-related matters. It also stated that the “Federal Government should commit to 

deeper, consistent, long-term engagement in AI standards development activities to help the 

United States to speed the pace of reliable, robust, and trustworthy AI technology 

development.” The most notable activities to advance the AI Standards Plan are summarized in 

this report to Congress.

2 H. Rept. 116-455 - Commerce, Justice, Science, and Related Agencies Appropriations Bill, 2021 

https://www.congress.gov/congressional-report/116th-congress/house-report/455.
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Recommendation 1: 

Bolster AI standards-related knowledge, leadership, and coordination among federal 

agencies to maximize effectiveness and efficiency.

Actions Taken to Implement Recommendation 1:

• The National Science and Technology Council (NSTC) Machine Learning/Artificial 

Intelligence (ML/AI) Subcommittee established the role of U.S. Government AI 

Standards Coordinator with responsibility to gather and share AI standards-related 

needs, strategies, roadmaps, terminology, use cases, and best practices in support of 

reliable, robust, and trustworthy AI in government operations, including: 

— planned and ongoing standards approaches and engagement activities, including 

a robust feedback loop with Standards Developing Organizations (SDOs);

— specific horizontal or vertical areas for prioritization;

— requirements for input into proposed standards activities; and 

— analyses of whether ongoing standards activities meet Federal Government 

needs and whether additional guidance is appropriate. 

The Subcommittee selected Elham Tabassi, Chief of Staff of the NIST Information 

Technology Laboratory, to fulfill the role of U.S. Government AI Standards Coordinator. 

• As part of the U.S. Government AI Standards Coordinator responsibilities, the AI 

Standards Coordination Working Group (AISCWG) was established in April 2021, to 

facilitate coordination of government agency activities related to development and use 

of AI standards. The group operates under the charter of the Interagency Committee on 

Standards Policy (ICSP)3. Participants include representatives across federal agencies4

with expertise and/or an agency stake in the development and implementation of AI 

standards. AISCWG activities fall within the oversight and scope of the Federal 

Coordinator for AI standards. The AISCWG is responsible for assisting the ICSP in 

promoting effective and consistent federal policies leveraging AI standards cited in the 

AI Standards Plan. 

The AISCWG raises awareness of federal agencies’ standards needs based on their use 

of AI; fosters agency interest and participation in AI standards activities; fosters

coordination of US Government positions regarding draft standards, standards work 

items, and other standards activities based on consensus processes; and establishes

effective means of coordinating AI international standards activities with those of the 

private sector.

• To better understand federal agencies’ AI standards needs and their current 

participation in AI standards activities – and to help in developing federal strategies for 

participation in AI standards – the AI Standards Coordinator developed a questionnaire. 

3 https://www.nist.gov/standardsgov/interagency-committee-standards-policy-icsp.

4 https://www.nist.gov/standardsgov/interagency-committee-standards-policy-icsp-members-0.
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Input was collected from, and results were reviewed with, agencies – including 

members of the Networking and Information Technology Research and Development 

(NITRD) Subcommittee and the ICSP. 

Nearly all agencies cited the relevance of AI to their business operations and/or their 

missions; some noted AI platforms are only now emerging but will play a larger role for 

them in the future. Overall, direct federal agency participation in AI standards activities 

was indicated to be minimal; in some cases, greater involvement was deemed valuable 

but not possible due to limited resources. Multiple respondents pointed to the need for 

improving coordination across agencies and ongoing data standards efforts as the most 

likely areas of focus for potential future activities related to AI standards. Making 

coordination difficult, several agencies indicated that their AI standards needs, and 

activities will be driven by operational needs and requirements as their agencies have 

very diverse AI standards-related needs. However, agencies consistently cited senior

leadership as necessary for robust AI participation.

Multiple respondents singled out areas of cross-agency needs and opportunities 

regarding standards and related tools, including but not limited to: standards policies; 

encouraging early engagement; best practices; formatting/archiving/availability of large 

data sets; conformity assessment; risk management; standing up new AI/ML 

technological capabilities (e.g., AI maturation); and common procurement and 

contracting language including standardized specifications or considerations around AI 

to apply to vendors and AI offerings.

The AISCWG intends to address many of the gaps identified by agencies responding to 

the questionnaire.

• The Office of Personnel Management (OPM), Office of Science and Technology Policy 

(OSTP), National Science Foundation (NSF), Department of Defense (DOD) including the 

National Security Agency (NSA), Department of Energy (DOE), and Department of 

Veterans Affairs (VA), are among the departments and agencies individually and jointly 

reviewing options to better position the Federal Government to gain access to new 

employees and to develop current employees to meet rapidly growing AI-capable 

workforce needs. This includes aiming to develop and provide a clear career 

development and promotion path valuing and encouraging participation in and 

expertise in AI standards and standards development. NIST is facilitating many of these 

reviews and interactions, in part based on elements of the National Initiative for 

Cybersecurity Education (NICE) Workforce Framework for Cybersecurity which could be 

a model for AI-related workforce approaches. NIST is working with OPM to develop an 

AI occupational series, consistent with House Report 116-455 accompanying the 

Consolidated Appropriations Act, P.L. 116-260, to develop a clear career development 
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and promotion path that recognizes and encourages participation in and expertise in AI 

standards development within the Federal workforce.

• In addition to federal agencies working on standards directly, there are opportunities to 

educate federally-funded AI researchers – including those supported by NSF, the 

Defense Advanced Research Projects Agency (DARPA), DOE, and others – on standards 

processes and engagement. There are many examples where government-supported 

academic researchers participated actively in standards-setting processes with positive 

results. Increasingly, agencies recognize that engaging the AI academic researchers in 

these opportunities would be a useful inter-agency coordinated effort.

• The National Artificial Intelligence Advisory Committee, established by the William 

“Mac” Thornberry National Defense Authorization Act for Fiscal Year 2021 (NDAA)5, 

advises the President and the National AI Initiative Office on AI-related matters. Among 

qualifications for the Advisory Committee’s members set forth in the NDAA is standards 

expertise. The committee is to consider whether ethical, legal, safety, security, and 

other appropriate societal issues are adequately addressed by the AI Initiative called for 

by section 5104 of the NDAA. It also is to advise on “opportunities for international 

cooperation with strategic allies on artificial intelligence research activities, standards 

development, and the compatibility of international regulations.”

• The NDAA explicitly directed NIST6to carry out a wide range of AI standards-related 

functions. These include:

(1) advance collaborative frameworks, standards, guidelines, and associated methods 

and techniques for artificial intelligence;

(2) support the development of a risk-mitigation framework for deploying artificial 

intelligence systems;

(3) support the development of technical standards and guidelines that promote 

trustworthy artificial intelligence systems; and

(4) support the development of technical standards and guidelines by which to test for 

bias in artificial intelligence training data and applications.

Furthermore, this statute directed NIST to develop, in collaboration with other public 

and private sector organizations – including NSF and DOE – a voluntary risk 

management framework for trustworthy AI systems. Among other things, the 

framework shall 

‘‘(1) identify and provide standards, guidelines, best practices, methodologies, 

procedures, and processes for 

 (A) developing trustworthy artificial intelligence systems; 

 (B) assessing the trustworthiness of artificial intelligence systems; and 

5 Pub. L. No. 116-283, https://www.congress.gov/116/bills/hr6395/BILLS-116hr6395enr.pdf.

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See Sec. 5301 of the NDAA, which amends NIST’s authorizing statute. 

https://www.congress.gov/116/bills/hr6395/BILLS-116hr6395enr.pdf.
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 (C) mitigating risks from artificial intelligence systems.” 

The NDAA also specifies that the framework shall:

‘‘(2) establish common definitions and characterizations for aspects of trustworthiness, 

including explainability, transparency, safety, privacy, security, robustness, fairness, 

bias, ethics, validation, verification, interpretability, and other properties related to 

artificial intelligence systems that are common across all sectors.”

Recommendation 2: 

Promote focused research to advance and accelerate broader exploration and understanding 

of how aspects of trustworthiness can be practically incorporated within standards and 

standards-related tools. 

Actions Taken to Implement Recommendation 2:

Delivering the needed measurements, standards, and other tools is a primary focus for NIST’s AI 

efforts, and much of its work focuses on aspects of trustworthiness. Over the past two years, 

NIST has expanded and made noteworthy progress7in carrying out research specifically 

addressing standards-oriented research recommendations in the AI Standards Plan. It has 

selected priority topics and activities based on its statutory mandates and the needs expressed 

by U.S. industry, other federal agencies, and the global AI research community. Among other 

things, NIST recently:

• Initiated research efforts in explainable and interpretable AI, bias in AI, secure AI, user 

trust in AI, and evaluation of AI.

• Developed a series of reports on aspects of AI trustworthiness, including: A Method for 

Evaluating User Trust in AI Systems; A Taxonomy and Terminology of Adversarial 

Machine Learning; Psychological Foundations of Explainability and Interpretability in AI; 

and A Proposal for Identifying and Managing Bias in AI.

• Organized a series of ongoing workshops to build communities and advance scientific 

discussions, beginning with a series kickoff and consisting of one-, two-day, and multiweek sessions involving working sessions aiming to forge agreement on key terms and 

aspects of trustworthiness that can be incorporated into the development of standards.

(Also see actions taken to implement Recommendation 3.)

• Organized a joint workshop with the Food and Drug Administration (FDA) and DARPA on 

AI for Drug Development in August 2021.

The NDAA authorized NSF to establish collaborative AI Research Institutes – codifying the 

program NSF launched in October 2019.8 The AI Institutes program supports foundational and 

use-inspired research involving university, government, and private-sector partners, and will 

include research contributing to improved AI standards, including aspects of trustworthiness.

For example, a 2020 AI Institute award specifically emphasizes trustworthy AI systems in the 

7 AI Fact Sheet | June 2021

8 See Sec. 5201 of the William M. (Mac) Thornberry National Defense Authorization Act for Fiscal Year 2021, Pub. 

L. No. 116-283, https://www.congress.gov/116/bills/hr6395/BILLS-116hr6395enr.pdf.
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context of climate science. The 2021 solicitation for the AI Research Institutes specifically calls 

for NIST involvement in a collaborative institute focusing on trustworthy AI.

The NDAA states explicitly agencies may use funds for: “(A) managing and making available to 

researchers accessible, curated, standardized, secure, and privacy protected data sets from the 

public and private sectors for the purposes of training and testing artificial intelligence systems 

and for research using artificial intelligence systems” and “(B) developing and managing 

testbeds for artificial intelligence systems, including sector specific test beds, designed to 

enable users to evaluate artificial intelligence systems prior to deployment.”9

Recommendation 3: 

Support and expand public-private partnerships to develop and use AI standards and related 

tools to advance reliable, robust, and trustworthy AI.

Actions Taken to Implement Recommendation 3:

• The National AI Research Institutes program, led by NSF, includes a growing number of 

partnerships with federal agencies and private companies. The program made its first 

awards in August 2020 and a second round of awards in July 2021 and launched a third 

competition for new Institutes in October 2021 10 with awards expected to be made in 

2022. Partners to date include the US Department of Agriculture’s National Institute of 

Food and Agriculture (NIFDA), Department of Homeland Security’s Science and 

Technology Directorate, Department of Transportation, National Institute of Standards

and Technology, Accenture, Amazon, Google, and Intel. The program establishes a set of 

multi-disciplinary and multi-organizational institutes on designated themes for 

foundational and use-inspired AI research. While all institutes are encouraged to 

develop and share tools for reliable, robust, and trustworthy AI, the theme of 

trustworthy AI is also the core focus of one proposed institute. 

• NSF supports several grant programs related to AI trustworthiness. They include:

Fairness, Ethics, Accountability, and Transparency— NSF invited researchers to 

submit proposals to a set of longstanding programs that contribute to discovery 

in research and practice related to fairness, ethics, accountability and 

transparency in computer and information science and engineering, including AI.

AI and Society, supported jointly with the Partnership on AI — NSF's directorates 

for Computer and Information Science and Engineering and Social, Behavioral 

and Economic Sciences, together with the Partnership on AI, have jointly 

supported Early-concept Grants for Exploratory Research to understand the 

social challenges arising from AI technology and enable scientific contributions to 

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.

9 See Sec. 5201 of the William M. (Mac) Thornberry National Defense Authorization Act for Fiscal Year 2021, 

Pub. L. No. 116-283, https://www.congress.gov/116/bills/hr6395/BILLS-116hr6395enr.pdf.

10 See NSF-led AI Research Institutes program, https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505686
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overcome them. With increases in the scale and diversity of deployments of AI 

systems comes the need to better understand AI in the open world, including 

unforeseen circumstances and social impacts, and to craft approaches to AI that 

consider these from the start.

NSF Program on Fairness in Artificial Intelligence in Collaboration with Amazon

— NSF and Amazon are partnering to jointly support research focused on 

fairness in AI, with the goal of contributing to trustworthy AI systems that are 

readily accepted and deployed to tackle grand challenges facing society. Specific 

topics of interest include, but are not limited to, transparency, explainability, 

accountability, potential adverse biases and effects, mitigation strategies, 

validation of fairness, and consideration of inclusivity.

NSF has funded a study by the National Academies of Sciences, Engineering, and 

Medicine (NASEM) on “Responsible Computing Research: Ethics and Governance 

of Computing Research and its Applications.” When completed, this study is 

expected to identify ethical principles and practices that research funders, 

research-performing institutions, and individual researchers can use to

formulate, conduct, and responsibly evaluate research and associated activities.

• The National Institutes of Health (NIH) recognizes there is a tremendous opportunity for 

data-driven discovery across its mission, including from AI/ML technologies. This 

requires findable, accessible, interoperable, and reusable (FAIR) and AI/ML-ready data. 

Making data FAIR and AI/ML-ready depends upon interdisciplinary skills not typically 

held by biomedical and behavioral researchers. 

Particularly for biomedical data, AI/ML-readiness should be guided by a concern for 

human and clinical impact. This requires attention to ethical, legal, and social 

implications of AI/ML, such as: biases in datasets, algorithms, and applications; concerns 

related to privacy and confidentiality; impacts on disadvantaged or marginalized groups 

and health disparities; and unintended, adverse social consequences of research and 

development. To assist in ensuring that human and clinical impact is taken into account 

in employing AI/ML technologies, NIH grants will support research in social and 

technical solutions for embedding ethics across the lifecycle of AI applications – and for 

enhancing NIH data so that it is FAIR and AI-ready.

• The General Services Administration (GSA) Information Technology Modernization 

Centers of Excellence (CoE) have designed the CoE AI Capability Maturity Model (AI 

CMM) as a planning tool for organizations building an AI investment strategy and 

technology roadmap. The plans generated from AI CMM activities will enable decisionmakers to identify investment areas that simultaneously meet near-term goals in the 

acceleration of AI adoption and broader enterprise business goals. In addition to 

leveraging the CMM AI system as an industry standard for understanding organizational 
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maturity, the CoE designed a complementary perspective on observing organizational 

maturity that is user-centric.

• NIST is working at its National Cybersecurity Center of Excellence (NCCoE) with industry 

partners to address a basic AI need: developing an acceptable and widely used 

taxonomy and terminology of adversarial machine learning (AML). This work can inform 

future standards and best practices for assessing and managing machine learning 

security by establishing a common language and understanding of the rapidly 

developing AML landscape.

• The NIST NCCoE is conducting research on the feasibility of pursuing projects related to 

the security of AI used in Semi-Autonomous Vehicles and AI Enabled Health Care. The 

results of this research are intended to identify the maturity of industry, standards, and 

technologies applicable to these two areas. Ultimately this will lead to collaborative 

efforts with industry, through research and development agreements. Academia and 

government partners are collaborating at the NCCoE to develop reference architectures 

and example solutions.

• Multiple NIST workshops on AI topics have attracted broad participation from public and 

private sector stakeholders, across the United States and internationally, and including 

AI designers, developers, providers, and users. These sessions have been designed to be 

highly interactive, even in the virtual environment. Views and information shared with 

NIST at these workshops have contributed significantly to the agency’s publications and 

plans related to aspects of AI trustworthiness that are informing standards-related 

efforts. The workshops have helped to build a community of interest for NIST's multifaceted work in this arena, which includes fundamental and applied 

research, benchmarks, and evaluation, standards, and policy engagement. Workshops 

have included:

AI trustworthiness: An August 6, 2020, workshop kicked off a NIST initiative 

involving private and public sector organizations and individuals in discussions 

about building blocks for trustworthy AI systems – and the associated 

measurements, methods, standards, and tools to implement those building 

blocks when developing, using, and testing AI systems. 

Bias in AI: An August 18, 2020, workshop contributed to the development of a 

shared understanding of one characteristic of trustworthiness – bias in AI, what 

it is, and how to measure it. Bias in AI is a key but insufficiently defined 

building block of trustworthiness. Insights shared by speakers and other 

participants moved the AI community closer to agreement on defining bias in AI. 

Explainable AI: As part of NIST’s efforts to provide foundational tools, guidance, 

and best practices for AI-related research, NIST released a draft white paper,

Four Principles of Explainable Artificial Intelligence, for public comment. Inspired 
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by comments received, this January 26-28, 2021, workshop delved further into 

developing an understanding of explainable AI.

Assessing and Improving AI Trustworthiness: Current Contexts, Potential Paths: 

This March 3-4, 2021, workshop hosted by the National Academies of Science, 

Engineering and Medicine (NASEM) and sponsored by NIST was designed to help 

think through this interrelated set of challenges. The workshop produced ideas

for activities and collaborations by academia, industry, and the public sector to 

improve the assessment of trustworthiness of AI systems, and recommendations 

for NIST and similar public bodies.

Co-hosted a workshop on Secure Data Sharing with the National Science 

Foundation (NSF) in an effort to bring federal data stewards (e.g., Chief Data 

Officers) together with technologists (e.g., NSF- and NIST-funded 

researchers pursuing security- and privacy-enhancing techniques), and users 

(e.g., AI researchers). The May 21, 2021, workshop specifically sought to identify 

novel approaches to unlock federal data sets in secure and privacy-preserving 

ways to advance AI research and innovation.

AI Measurement and Evaluation: The June 15-17, 2021, workshop brought 

together stakeholders and experts to identify the most pressing needs for AI 

measurement and evaluation and to advance the state of the art and practice. 

The gathering helped NIST to: 1) identify the needs for and intended uses of AI 

measurement and evaluation along with the gaps in knowledge/practice 

preventing current AI measurement and evaluation activities from effectively 

meeting these needs/uses, 2) solicit guidance on which specific areas that NIST 

should focus its efforts, 3) Identify specific users and applications in need of 

measurement and evaluation, and 4) collate best practices for AI measurement 

and evaluation.

Recommendation 4: 

Strategically engage with international partners to advance AI standards for U.S. economic 

and national security needs.

Actions Taken to Implement Recommendation 4

The US Government increasingly has been undertaking international engagements bilaterally 

and multilaterally as well as in international organizations to advance AI research and standards 

for US economic and national security needs. Special attention has been given to like-minded 

countries with shared values with the goal of exchanging information and cooperating in the 

pre-standardization research and development that underpin trustworthy AI systems. 

In March 2021, NIST supported the US Department of State in developing the Congressional 

report, “A Plan to Establish Exchanges and Partnerships between the United States and Its Allies 
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to Create Standards for Artificial Intelligence Technologies.” Other recent international 

engagements include: 

• The United States championed development of the first international principles for the 

responsible use of AI at the Organisation for Economic Co-operation and Development

(OECD). The OECD is an organization of like-minded democracies committed to open 

markets, and as such has been a focal point for U.S. multilateral work on AI. The OECD 

Principles on AI take a holistic approach, with a strong emphasis on international, multistakeholder collaboration, and flexible, light-touch policy and regulatory environments 

to promote innovative and trustworthy applications of AI in line with human rights and 

democratic values. The United States currently chairs the OECD Network of Experts on 

AI, a multi-stakeholder group that is developing more detailed implementation guidance 

for governments and other stakeholders to move from principle to practice.11

• To help implement a high-level U.S-United Kingdom declaration of cooperation on AI 

R&D signed in September 2020, a new dialogue with the UK was initiated to coordinate 

efforts and promote joint AI research and development. More broadly, NIST utilizes

international Science and Technology Cooperation Agreements negotiated by the State 

Department and participates in the associated bilateral dialogues to strengthen 

international cooperation on standards and measurement-related activities, including 

those for AI technologies.

• The United States became a founding member of the Global Partnership on AI (GPAI)

along with Australia, Canada, France, Germany, India, Italy, Japan, Mexico, New Zealand, 

South Korea, Singapore, Slovenia, the United Kingdom, and the European Union. GPAI is 

a voluntary multi-stakeholder initiative that brings together leading experts from 

science, industry, civil society, international organizations, and government that share 

values of human rights, inclusion, diversity, innovation, and economic growth. It aims to 

bridge the gap between theory and practice on AI by supporting cutting-edge research 

and applied activities on AI-related priorities. There are 25 GPAI members, including all 

G7 and important emerging economies such as Brazil and India. Through GPAI, the 

United States seeks to complement the more policy-oriented work of the OECD by 

increasing coordination on research and development and scaling up practical projects 

for implementing trustworthy AI. 

• To gain a greater understanding of the global landscape of AI standards-related 

activities, NIST will soon begin a year-long data collection and analysis project. While its 

scope will look at technologies beyond AI, the study will examine the role of the 

People’s Republic of China (PRC) in international standards setting organizations over 

the previous 10 years, including leadership roles in standards drafting technical 

committees, and the quality or value of that participation. The study also will consider: 

11 A Plan to Establish Exchanges and Partnerships between the United States and Its Allies to Create Standards for 

Artificial Intelligence Technologies, Required by Section 7019(e) of the Department of State, Foreign Operations, 

and Related Programs Appropriations Act, 2021 and House Report 116-444.
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the effect of the PRC’s ‘‘Chinese Standard 2035’’ strategy on international bodies 

engaged in developing and setting standards; whether international standards for select 

emerging technologies are being designed to promote PRC interests to the exclusion of 

other participants; how previous PRC practices used while participating in international 

standards setting organizations may foretell how China is likely to engage in 

international standardization activities of critical technologies like artificial intelligence 

and quantum information science, and potential consequences; and recommendations 

on how the United States can take steps to mitigate the PRC’s influence and bolster US

public and private sector participation in international standards-setting bodies.

• The NDAA’s AI-related provisions include authorizing NIST to ‘‘(...support and 

strategically engage in the development of voluntary consensus standards, including 

international standards, through open, transparent, and consensus-based processes.”

This reinforces a traditional and ongoing role of NIST.

2. Next Steps and the Way Forward

As noted earlier, as the Federal Government’s AI standards coordinator, NIST continues to work 

with other government agencies in the United States and around the world, the private sector, 

and other stakeholders to regularly review and carry out the AI Standards Plan. Federal 

agencies and private sector organizations alike are expected to deepen their involvement in 

standards activities; it is clear to a growing number of those in the AI community that key 

decisions will be made in standards setting which will determine the pace and type of

innovations we can expect in AI products and technologies, especially when it comes to aspects 

of trustworthiness. NIST will track, coordinate, and seek to catalyze those activities undertaken 

by federal departments and agencies. 

The Biden Administration has made supporting the industry-led technology standardization 

ecosystem a priority, including international collaboration with key partners and allies. This 

includes committing to a Framework for collaboration on digital technical standards through 

the G712 and an emerging technology working group with Quad countries: the United States, 

Japan, Australia, and India.

13 While this work goes beyond AI standards, such collaborations are 

expected to provide a key venue to further the AI Standards Plan. 

Appendices:

• Text from Commerce, Justice, Science, and Related Agencies Appropriations Bill, 2021

• “Recommended Federal Government Standards Actions to Advance U.S. AI Leadership” 

from the August 2019 report, pp. 22-24 

• NDAA, Sec. 5201

• NDAA, Sec. 5301 and 5302 

12 https://www.gov.uk/government/publications/g7-digital-and-technology-ministerial-declaration.

13 https://www.whitehouse.gov/briefing-room/statements-releases/2021/03/12/quad-leaders-joint-statement-thespirit-of-the-quad/.