The National Institute of Standards and Technology (NIST) aims to cultivate trust in the design, development, use, and 

governance of Artificial Intelligence (AI) technologies and systems in ways that enhance economic security and improve quality 

of life. NIST focuses on improving measurement science, technology, standards, and related tools – including evaluation and 

data. 

With AI and Machine Learning (ML) already changing how society addresses challenges and opportunities, these technologies 

must be trustworthy and embedded in responsible practices. Trustworthy AI systems are those demonstrated to be valid and 

reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with 

harmful bias managed. Trustworthiness is critical for successful deployment of new technologies for genomics, image and video 

processing, materials, natural language processing, robotics, wireless spectrum monitoring, and more. NIST helps to deliver 

the needed measurements, standards, tools, and expertise. The agency’s AI goals and activities are driven by its statutory 

mandates, Presidential Executive Orders, and the needs expressed by U.S. industry, other federal agencies, and the global AI 

research community.

NIST’s AI goals include:

1. Conduct fundamental research to advance trustworthy AI technologies

2. Apply AI research and innovation across the NIST Laboratory Programs

3. Establish benchmarks, data, and metrics to evaluate AI technologies

4. Lead and participate in development of technical AI standards 

5. Contribute technical expertise to discussions and development of AI policies

FUNDAMENTAL AI RESEARCH

NIST’s AI portfolio includes fundamental research, 

development, and standards vital for trust in AI technologies. 

This work includes efforts on software, hardware, 

architectures, human-interaction and teaming, and all relevant 

intersections and interfaces.

Establishing and Promoting Technical Requirements for 

Trustworthy and Responsible AI

• NIST identifies and quantifies trustworthy and responsible 

AI in technical terms and develops tools and guidance so 

that designers, developers, and evaluators can act. This 

includes developing taxonomy, terminology, and testbeds 

for measuring AI risks, as well as standards for key 

technical characteristics of AI trustworthiness. 

• Aided by workshops and other engagements, NIST 

develops documents, software, standards, and related 

tools that help AI actors better understand, identify, 

measure, and manage risks associated with AI systems.

• As mandated by Congress, NIST has developed a 

voluntary AI Risk Management Framework. The framework 

was worked on collaboratively with public and private 

stakeholders, many of whom are now implementing it and 

using its companion Playbook. 

• NIST has established a Trustworthy and Responsible 

AI Resource Center, a “one stop shop” for foundational 

content, technical documents, and toolkits to enable 

responsible use of AI.

• Per an October 30, 2023 Presidential Executive Order, 

NIST is launching a variety of new initiatives to advance 

critical guidelines, benchmarks, and tools to evaluate AI 

trustworthiness.

• NIST has launched the U.S. AI Safety Institute and a 

related consortium to empower a new measurement 

science. These institutions will help identify proven, 

scalable, and interoperable techniques and metrics to 

promote responsible development and use of safe and 

trustworthy AI.

Hardware for AI: Creating New Measurements and 

Technical Approaches for New AI Chips

• As AI becomes more prevalent in our everyday lives, 

demand for faster, more energy-efficient information 

processing is growing exponentially. Conventional 

hardware cannot keep up with this demand. That is 

why researchers, taking inspiration from the brain, are 

considering alternatives—e.g., where massively connected 

networks of artificial neurons and synapses process 

AI Fact Sheet | November 2023 1
information with high speed, energy efficiency, scalability, 

and adaptive learning. NIST is helping develop devices, 

circuits, systems, measurements, and theory to support 

the evolution of new AI hardware from laboratory research 

to commercial applications. NIST is focusing on scalability, 

energy efficiency, hardware optimization, and architecture 

development. The new physical computation mechanisms 

and intelligent functionality call for new measurement 

techniques and protocols. 

APPLIED AI RESEARCH

NIST’s multidisciplinary laboratories offer an ideal environment 

to develop and apply AI. AI approaches are increasingly an 

essential component in new project conception and execution. 

NIST scientists and engineers are drawing on a variety of ML 

and AI tools to gain a deeper understanding of and insight 

into their research. At the same time, NIST laboratories’ 

experiences with AI are assisting in better understanding AI’s 

capabilities and limitations.

Exploring Research Frontiers by Incorporating AI and ML 

• NIST researchers are developing partnerships across 

the Institute and with academia, other government 

laboratories, and industrial entities. They are integrating 

AI into the design, planning, and optimization of NIST’s 

research efforts – including computer vision, engineering 

biology and biomanufacturing, image and video 

understanding, medical imaging, materials science, 

manufacturing, disaster resilience, energy efficiency, 

natural language processing, quantum science, robotics, 

and advanced communications technologies. Key focus 

areas include innovative measurements using AI/ML 

techniques, predictive systems using AI/ML models, 

and enabling and reducing the barriers to autonomous 

measurement platforms.

Producing Training Data, Algorithms, and Other Tools 

• NIST’s technical staff are working on key practices 

for documentating and characterizing datasets, and 

developing datasets that the broader community can use 

to test or train AI systems. The agency is expanding the 

availability of algorithms, test or training data, and other 

tools for domain-specific applications including advanced 

materials, computer vision, design, industrial robotics, 

natural language processing, spectrum management, and 

video processing. 

With a long history of devising and revising metrics, 

measurement tools, standards, and testbeds, NIST 

increasingly is focusing on measurement and evaluation of 

technical characteristics of trustworthy AI.

NIST’s actions under the President’s Executive Order on 

Safe, Secure, and Trustworthy Artificial Intelligence and its 

new U.S. AI Safety Institute are major initiatives designed to 

dramatically advance the ability to measure and evaluate the 

trustworthiness of rapidly advancing AI technologies. 

While NIST’s activities have typically addressed measures 

of accuracy and robustness, other types of AI-related 

measurements and evaluations under investigation include 

safety, bias, interpretability, and transparency. Working with 

others, NIST aims to augment such efforts by:

• Advancing measurement science for AI: Defining, 

characterizing, and theoretically and empirically 

developing and analyzing quantitative and qualitative 

metrics and measurement methods for various 

characteristics of AI technologies.

• Conducting rigorous evaluations of AI: Designing and 

conducting evaluations of AI technologies – including 

developing tasks, challenge problems, testbeds, software 

tools, and helping to curate and characterize meaningful 

data sets – and identifying technical gaps and limitations 

in AI technologies and related measurements.

• Developing best practices and technical guidance: Sharing 

results and guidance to inform academic, industrial, and 

government programs.

• Contributing to voluntary consensus-based standards 

for measuring and evaluating AI: Leading or participating 

in standardization efforts to support the development, 

deployment, and evaluation of AI technologies.

TECHNICAL AI STANDARDS

NIST leads and participates in the development of technical 

standards, including international standards, that promote 

innovation and public trust in systems that use AI.

Ensuring Awareness and Federal Coordination in AI 

Standards Efforts

• In its role as federal AI standards coordinator, NIST 

works across the government and with industry to identify 

critical standards development activities, strategies, 

and gaps. Based on priorities outlined in the NISTdeveloped Plan for Federal Engagement in AI Standards 

and Related Tools, the agency is tracking AI standards 

development opportunities, periodically collecting and 

analyzing information about agencies’ AI standards-related 

priority activities, and making recommendations through 

interagency processes to optimize engagement.

AI FACT SHEET | NOVEMBER 2023 2

MEASUREMENT & EVALUATION 
• NIST is coordinating federal agencies in the development 

and use of AI standards in part through the Interagency 

Committee on Standards Policy (ICSP), which it chairs. 

ICSP’s AI Standards Coordination Working Group 

promotes effective and consistent federal policies to 

leverage and further development of AI standards, raise 

awareness, and foster agencies’ use of AI. The group 

helps to coordinate government and private sector 

positions on AI international standards activities, a priority 

spelled out in the October 2023 Executive Order.

Participating in High-Priority AI Standards Activities

• NIST supports its staff’s participation and leadership 

in standards development activities aligned with NIST 

technical expertise. Participation is based on national 

needs and an assessment of priority topics and gaps.

• NIST efforts include work through two prominent 

international standards developing organizations: ISO and 

IEEE.

AI POLICY CONTRIBUTIONS

NIST expertise in AI is helping national and global AI policy 

bodies shape the development and use of innovative, 

trustworthy AI. In the international arena, standards are a 

critical element of government’s AI policies and industry 

pracices. NIST plays a key role as a neutral convenor of 

organizations and individuals with disparate views about AI 

matters. The NIST AI Risk Management Framework highlights 

how NIST’s reputation for technical excellence and interacting 

impartially with the private and public sectors is influencing 

international approaches to AI. 

Contributing to Federal Engagements that Explore or 

Determine AI-Related Policies

• NIST leads or participates in several federal AI 

policymaking efforts and engages with many other 

federal offices and interagency groups. This includes 

administering the National Artificial Intelligence Advisory 

Committee, co-chairing the National Science and 

Technology Council’s Machine Learning and Artificial 

Intelligence Subcommittee, co-chairing the Networking 

and Information Technology Research and Development’s 

AI Working group, and founding and co-chairing the 

AI Standards Coordination Working Group under the 

Interagency Committee Standards Policy. NIST’s AI lead 

also serves as Federal AI Standards Coordinator and was 

a member of the National AI Research Resource Task 

Force.

Participating in Major AI Forums

• NIST engages with private, public, and non-profit 

organizations – directly and via international forums and 

other dialogues – about AI-related policies that align 

with NIST’s mission and technical contributions. NIST 

also convenes national and international stakeholders 

to ensure two-way communication on select AI-related 

issues.

• NIST supports U.S. and internatoinal AI policy efforts such 

as the U.S.-EU Trade and Technology Council, OECD, 

Global Partnership on AI, and a host of bilateral initiatives 

in Asia, Europe, and North America.

WORKING WITH NIST ON AI

NIST relies on and encourages robust interactions with companies, 

universities, nonprofits, and other government agencies in driving 

and carrying out its AI agenda. There are multiple ways to engage 

with NIST, including:

NIST Draft Reports: NIST counts on public and private sector review 

of draft reports on a variety of AI issues. Drafts typically are prepared 

based on inputs from private and public sector individuals and 

organizations and then offered for public review on NIST’s AI website 

and via email alerts. Public comments help to improve them. Sign up 

for AI-related emails here.

Workshops: NIST convenes experts for single day, multi-day, and 

multi-week sessions to tackle key characteristics of AI trustworthiness 

and other AI-related topics. All workshops are virtual for now and 

readily accessible.

AI Visiting Fellows: Accomplished Visiting Fellows bring thought 

leadership to fundamental research for trustworthy and responsible 

AI, use-inspired AI research, and AI hardware research, as well as AI 

related standards and evaluations conducted in NIST laboratories.

AI Visiting Researchers: To advance their careers and assist NIST in 

the process, Visiting Researchers conduct their work based on NIST 

laboratory priorities with guidance and recommendations from NIST 

mentors and AI Visiting Fellows.

Student Programs: NIST offers a range of opportunities for 

students to engage with NIST on AI-related work. That includes 

the Professional Research Experience Program (PREP), which 

provides valuable laboratory experience and financial assistance to 

undergraduate, graduate, and post-graduate students.

Grants: NIST offers some financial assistance to support collaborative 

research, including AI projects.

AI FACT SHEET | NOVEMBER 2023 3

Sign up for AI email alerts here. If you have questions or 

ideas about how to engage with us on AI topics, send us 

an email: ai-inquiries@nist.gov.