Quality Management for Machine Learning Systems

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Published Sep 4, 2023
Yutaka Oiwa

Abstract

We have been developing a methodology for process-based quality management of machine learning-based AI systems. Our fruit is compiled as a guideline document named “Machine Learning Quality Management Guideline”, published as our technical report. We will describe our background motivation, surrounding situation and our proposal for quality management.

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Keywords

Machine Learning, Quality Management, Artificial Intelligence

References
AIST: National Institute of Advanced Industrial Science and Technology (2023). Machine Learning Quality Management Guideline, 3rd English Edition. Technical Report Digiarc-TR-2023-01, Digital Architecture Research Center. Tokyo, Japan. https://www.digiarc.aist.go.jp/publication/aiqm/guidelin e-rev3.html .

AIST: National Institute of Advanced Industrial Science and Technology (2021). Machine Learning Quality Management Guideline, 1st English Edition. Technical Report CPSEC-TR-202002, Cyber Physical Security Research Center, Tokyo, Japan. https://www.cpsec.aist.go.jp/achievements/aiqm/AIQM -Guideline-1.0.1-en.pdf .O

OECD: Organisation for Economic Co-operation and Development (2019), OECD Recommendation of the Council on Artificial Intelligence. OECD/LEGAL/0449, May 2019. https://legalinstruments.oecd.org/en/instruments/OECD -LEGAL-0449.

European Parliament (2023),. Artificial Intelligence Act. P9TA(2023)0236. https://www.europarl.europa.eu/doceo/document/TA-92023-0236_EN.pdf .
Section
Special Session Papers