NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.

Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.

U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

PUBLICATIONS

Four Principles of Explainable Artificial Intelligence

Published

Author(s)

P. Jonathon Phillips, Carina Hahn, Peter Fontana, Amy Yates, Kristen K. Greene, David A. Broniatowski, Mark A. Przybocki
Citation
NIST Interagency/Internal Report (NISTIR) - 8312
Report Number
8312
NIST Pub Series
NIST Interagency/Internal Report (NISTIR)
Pub Type
NIST Pubs

Download Paper

https://doi.org/10.6028/NIST.IR.8312
Local Download
Artificial intelligence

Citation

Phillips, P. , Hahn, C. , Fontana, P. , Yates, A. , Greene, K. , Broniatowski, D. and Przybocki, M. (2021), Four Principles of Explainable Artificial Intelligence, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.IR.8312, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933399 (Accessed October 6, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created September 29, 2021, Updated November 29, 2022
Was this page helpful?