Frameworks and principles
National Institute of Standards and Technology
Research and analysis item
Trust and artificial intelligence
The artificial intelligence (AI) revolution is upon us, with the promise of advances such as driverless cars, smart buildings, automated…
Research and analysis item
Psychological foundations of explainability and interpretability in artificial intelligence
In this paper, we make the case that interpretability and explainability are distinct requirements for machine learning systems. To make…
Research and analysis item
Four principles of explainable artificial intelligence
We introduce four principles for explainable artiļ¬cial intelligence (AI) that comprise fundamental properties for explainable AI systems. We propose that…
Research and analysis item
A taxonomy and terminology of adversarial machine learning
This NIST Interagency/Internal Report (NISTIR) is intended as a step toward securing applications of Artificial Intelligence (AI), especially against adversarial…
Research and analysis item
Towards a standard for identifying and managing bias in artificial intelligence
As individuals and communities interact in and with an environment that is increasingly virtual they are often vulnerable to the…
Research and analysis item
U.S. leadership in AI: a plan for federal engagement in developing technical standards and related tools
NIST has released a plan for prioritizing federal agency engagement in the development of standards for artificial intelligence (AI). The…
Research and analysis item
AI risk management framework
NIST is developing a framework to better manage risks to individuals, organizations, and society associated with artificial intelligence (AI). The…
