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Artificial intelligence

NIST contributes to the research, standards and data required to realize the full promise of artificial intelligence (AI) as an enabler of American innovation across industry and economic sectors.

Illustration that shows an outline of a face and then icons to represent different areas of AI including heart (health), lock (cyber), windmills (energy), steering wheel (cars) and manufacturing arm
Credit: N. Hanacek/NIST

August 6, 2020 | AI Kickoff Webinar 
This webinar kicks 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 overseeing AI systems. NIST’s effort will be informed by a series of workshops that will follow this initial session.
 
August 18, 2020 | Bias in AI Workshop
This workshop focuses on collectively facilitating the development of a shared understanding of bias in AI, what it is, and how to measure it. This online event will consist of collaborative panels and breakout sessions and will bring together experts from the public and private sectors to engage in important discussions about bias in AI.

Why is Artificial Intelligence (AI) important?

Artificial Intelligence (AI) is rapidly transforming our world. Remarkable surges in AI capabilities have led to a number of innovations including autonomous vehicles and connected Internet of Things devices in our homes. AI is even contributing to the development of a brain-controlled robotic arm that can help a paralyzed person feel again through complex direct human-brain interfaces. These new AI-enabled systems are revolutionizing everything from commerce and healthcare to transportation and cybersecurity.

AI has the potential to impact nearly all aspects of our society, including our economy, but the development and use of the new technologies it brings are not without technical challenges and risks. AI must be developed in a trustworthy manner to ensure reliability, safety and accuracy.

Cultivating Trust in AI Technologies

NIST has a long-standing reputation for cultivating trust in technology by participating in the development of standards and metrics that strengthen measurement science and make technology more secure, usable, interoperable and reliable. This work is critical in the AI space to ensure public trust of rapidly evolving technologies, so that we can benefit from all that this field has to promise. 

AI systems typically make decisions based on data-driven models created by machine learning, or the system’s ability to detect and derive patterns. As the technology advances, we will need to develop rigorous scientific testing that ensures secure, trustworthy and safe AI. We also need to develop a broad spectrum of standards for AI data, performance, interoperability, usability, security and privacy.

NIST's Role

Interagency Engagement

NIST participates in interagency efforts to further innovation in AI. NIST Director and Undersecretary of Commerce for Standards and Technology Walter Copan serves on the White House Select Committee on Artificial Intelligence. Charles Romine, Director of NIST’s Information Technology Laboratory, serves on the Machine Learning and AI Subcommittee. 

A February 11, 2019, Executive Order on Maintaining American Leadership in Artificial Intelligence tasks NIST with developing “a plan for Federal engagement in the development of technical standards and related tools in support of reliable, robust, and trustworthy systems that use AI technologies.” For more information, see: https://www.nist.gov/topics/artificial-intelligence/ai-standards.

Research

NIST research in AI is focused on how to measure and enhance the security and trustworthiness of AI systems. This includes participation in the development of international standards that ensure innovation, public trust and confidence in systems that use AI technologies. In addition, NIST is applying AI to measurement problems to gain deeper insight into the research itself as well as to better understand AI’s capabilities and limitations. 

The NIST AI program has two major goals: 

  1. Advancing application of AI to NIST metrology problems by bolstering AI expertise at NIST and enabling NIST scientists to draw routinely on machine learning and AI tools to gain deeper insight into their research; and 
  2. Fundamental research to measure and enhance the security and explainability of AI systems. 

The recently launched AI Visiting Fellow program brings nationally recognized leaders in AI and machine learning to NIST to share their knowledge and experience and to provide technical support.

News and Updates

Stem Cells and AI: Better Together

One day in the future when you need medical care, someone will examine you, diagnose the problem, remove some of your body’s healthy cells, and then use them to

Events

Bias in AI Workshop

Tue, Aug 18 2020, 9:00am - 5:00pm EDT
The workshop was originally scheduled to be held at NIST Gaithersburg, MD. While we strive to accommodate global

Projects and Programs

JARVIS-ML

JARVIS-ML is a repository of machine learning (ML) model parameters, descriptors, and ML related input and target data. JARVIS-ML is a part of the NIST-JARVIS

Temporal Computing

The human brain does some types of information processing, like speech recognition, image recognition, or video processing, much more efficiently than can be

Spintronics for Neuromorphic Computing

One of the most promising new approaches to next generation information processing is spintronics, where information is carried with electronic spin rather than

Publications

NIST 2020 CTS Speaker Recognition Challenge Evaluation Plan

Author(s)
Seyed Omid Sadjadi, Craig S. Greenberg, Elliot Singer, Douglas A. Reynolds, Lisa Mason
Following the success of the 2019 Conversational Telephone Speech (CTS) Speaker Recognition Challenge, which received 1347 submissions from 67 academic and

Software

Nestor

The Nestor Graphical User Interface (GUI) is a free toolkit that helps maintainers annotate their Maintenance Work Order (MWO) data through a process called

Awards