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Assuring Safety-Critical Machine Learning Enabled Systems: Challenges and Promise Machine learning is increasingly being used in safety-critical systems, where the public safety requires a rigorous assurance process. We shall outline how assurance processes work for conventional systems and identify the primary difficulty in applying them to machine learning enabled systems. We will then outline a path forward including identifying where considerable basic research remains.
Document ID
20220015661
Acquisition Source
Langley Research Center
Document Type
Presentation
Authors
Alwyn Goodloe
(Langley Research Center Hampton, Virginia, United States)
Date Acquired
October 18, 2022
Subject Category
Computer Programming And Software
Meeting Information
Meeting: First IEEE International Workshop on Workshop on Assured Autonomy, AI and Machine Learning (WAAM2022)
Location: Charlotte, NC
Country: US
Start Date: October 31, 2022
End Date: October 31, 2022
Sponsors: IEEE Computer Society
Funding Number(s)
WBS: 340428.02.60.07.01
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
Single Expert
Keywords
machine learning
autonomy
certification
assurance
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