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AI Research, Measurement, and Standards Division
Accelerating and expanding the development and adoption of Artificial Intelligence (AI) by strengthening trust through measurement science, testing and evaluation, guidance, and standards
The AI Research, Measurement, and Standards Division is one of six technical divisions in the Information Technology Laboratory (ITL). The Division leads and coordinates the ITL AI Program.
The Division collaborates closely with stakeholders across the AI ecosystem to accelerate the development and adoption of trustworthy artificial intelligence through guidelines and resources that help advance AI. It provides leadership in the global development of AI standards, working with government and industry stakeholders to identify critical standards development activities, strategies, and gaps.
The Division also researches, tests, and evaluates the use of AI to solve scientific and engineering problems arising in measurement science and related use-inspired AI applications.
Groups
The AI Research, Measurement, and Standards Division’s efforts are carried out by the AI Standards and Guidelines Group and the Applied AI Research Group.
Programs, Resources and Publications
The AI Research, Measurement, and Standards Division strengthens trust in AI, accelerates its adoption, and expands U.S. AI preeminence by advancing the vital measurement science related to AI, testing and evaluation, and standards. The Division’s efforts reflect the most recent developments in AI as well as anticipated technological and commercialization progress.
The Division focuses on four high-impact areas:
#1 Advancing Testing, Evaluation, Verification, and Validation (TEVV) for Trustworthy AI: Transforming the measurement of AI – especially system trustworthiness – via TEVV to help ensure that AI is deployed and used responsibly, reliably, and efficiently. Examples include:
#2 Empowering Informed Decision-Making: Providing resources for managing AI benefits and risks, empowering industry and government to make informed decisions about AI trustworthiness and use. Examples include:
#3 Global Standards Leadership: Positioning the U.S. as preeminent in AI technical and governance standards – ensuring U.S. leads global AI innovation, combats adversaries’ growing influence.
#4 Domain-Specific Advances: Enabling the U.S. to lead in applying AI to high-priority areas – including manufacturing and cybersecurity for critical infrastructure – via innovative approaches to address measurement challenges.