Abstract
Current certification procedures aim at establishing trust in manufacturers of artificial intelligence/machine learning based cyber-physical systems. The certification process usually requires the manufacturer to demonstrate excellence in following safety engineering standards and regulations throughout the holistic system’s engineering process. This paper touches on the need for real-world performance monitoring performed by the certifier to ensure that the operational system does not deviate from the specifications. We propose an interactive cooperative process between the manufacturer and certifier which aims at verifying conformance and consistency between the specifications and the operational model while preserving the manufacturer’s competitive advantage.
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Notes
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An (AI/ML)-based device is a system designed using AI and ML techniques to learn from and act on data [6].
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This work is partly funded by a DARPA AMP grant.
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Lamrani, I., Banerjee, A., Gupta, S.K.S. (2021). Certification Game for the Safety Analysis of AI-Based CPS. In: Habli, I., Sujan, M., Gerasimou, S., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2021 Workshops. SAFECOMP 2021. Lecture Notes in Computer Science(), vol 12853. Springer, Cham. https://doi.org/10.1007/978-3-030-83906-2_25
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