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PUBLICATIONS

Proxy Validation and Verification for Critical AI Systems

Published

Author(s)

Phillip Laplante, Joanna DeFranco, D. Richard Kuhn, Jeff Voas

Abstract

This white paper offers a suggestion that prior testing artifacts from similar AI systems can be reused for new AI software. Testing AI and Machine learning software is difficult, and if prior testing results from similar systems could be applied as a proxy, this would be a significant research advance.
Citation
NIST Cybersecurity White Papers (CSWP) - 31
Report Number
31
Pub Type
NIST Pubs

Download Paper

https://doi.org/10.6028/NIST.CSWP.31
Local Download

Keywords

artificial intelligence, assurance, testing, verification
Information technology

Citation

Laplante, P. , DeFranco, J. , Kuhn, D. and Voas, J. (2024), Proxy Validation and Verification for Critical AI Systems, NIST Cybersecurity White Papers (CSWP), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.CSWP.31, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956743 (Accessed November 20, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created September 26, 2024