Proxy Verification and Validation For Critical Autonomous and AI Systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

A challenging problem for software and systems engineers is to provide assurance of operations for a system that is critical but must operate in situations that cannot be easily created in the testing lab. For example, a space system cannot be fully tested in all operational modes until it is launched and nuclear power plants cannot be tested under real critical temperature overload conditions. This situation is particularly challenging when seeking to provide assurance in critical AI systems (CAIS) where the underlying algorithms may be very difficult to verify under any conditions. In these cases using systems that have a similar underlying application, operational profiles, user characteristics, and underlying AI algorithms may be suitable as testing proxies. For example, a robot vacuum may have significant operational and implementation similarities to act as a testing proxy for some aspects of an autonomous vehicle.In this work we discuss the challenges in assured autonomy for CAIS and suggest a way forward using proxy systems. We describe a methodology for characterizing CAIS and matching them to their non-critical proxy equivalent.

Original languageEnglish (US)
Title of host publicationProceedings - 2022 IEEE 29th Annual Software Technology Conference, STC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages37-40
Number of pages4
ISBN (Electronic)9781665488648
DOIs
StatePublished - 2022
Event29th IEEE Annual Software Technology Conference, STC 2022 - Virtual, Online, United States
Duration: Oct 3 2022Oct 6 2022

Publication series

NameProceedings - 2022 IEEE 29th Annual Software Technology Conference, STC 2022

Conference

Conference29th IEEE Annual Software Technology Conference, STC 2022
Country/TerritoryUnited States
CityVirtual, Online
Period10/3/2210/6/22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Safety, Risk, Reliability and Quality

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