AI Research

NIST’s AI portfolio includes building the scientific underpinning for  measurements, evaluations, benchmarks, technical standards, and guidelines, for responsible use of AI across different contexts and sectors of the economy.  

Trustworthy AI systems are demonstrated to be valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with harmful bias managed.

Reflecting private sector interest and a congressional mandate, NIST developed the voluntary AI Risk Management Framework through collaborations with stakeholders across the public and private sectors. The AI RMF is a key piece of NIST’s AI efforts and helps to drive NIST’s priorities in AI.

Among many other things, NIST develops:  

• Taxonomy and terminology necessary to build a shared understanding of AI benefits and risks, 
• Testbeds and benchmarks for measuring AI capabilities and limitations,  and
• Test methods and standards needed to evaluate AI  models and systems. 

NIST’s AI Trustworthy and Responsible Resource Center hosts documents, software, standards, and related tools that contribute to better understanding, identifying, measuring, and managing various risks associated with AI systems.

Hardware for AI: 

• NIST is helping to develop devices, circuits, systems, measurements, and theory to support the evolution of AI hardware technology from laboratory research to commercial applications. NIST is focusing on scalability, energy efficiency, hardware optimization, and architecture development. The new hardware leverages the physics of devices to perform computations, while the architectures and algorithms have entirely new intelligent functionality. This calls for a new system of measurement techniques and protocols.