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2021 | OriginalPaper | Buchkapitel

3. Artificial Intelligence and Future of Systems Engineering

verfasst von : Thomas A. McDermott, Mark R. Blackburn, Peter A. Beling

Erschienen in: Systems Engineering and Artificial Intelligence

Verlag: Springer International Publishing

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Abstract

Systems Engineering (SE) is in the midst of a digital transformation driven by advanced modeling tools, data integration, and resulting “digital twins.” Like many other domains, the engineering disciplines will see transformational advances in the use of artificial intelligence (AI) and machine learning (ML) to automate many routine engineering tasks. At the same time, applying AI, ML, and autonomation to complex and critical systems needs holistic, system-oriented approaches. This will encourage new systems engineering methods, processes, and tools. It is imperative that the SE community deeply understand emerging AI and ML technologies and applications, incorporate them into methods and tools, and ensure that appropriate SE approaches are used to make AI systems ethical, reliable, safe, and secure. This chapter presents a road mapping activity undertaken by the Systems Engineering Research Center (SERC). The goal is to broadly identify opportunities and risks that might appear as this evolution proceeds as well as potentially provide information that guides further research in both SE and AI/ML.

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Literatur
Zurück zum Zitat Abdar, M., Pourpanah, F., Hussain, S., Rezazadegan, D., Liu, L., Ghavamzadeh, M., & Nahavandi, S. (2020). A review of uncertainty quantification in deep learning: Techniques, applications and challenges. arXiv:2011.06225. Abdar, M., Pourpanah, F., Hussain, S., Rezazadegan, D., Liu, L., Ghavamzadeh, M., & Nahavandi, S. (2020). A review of uncertainty quantification in deep learning: Techniques, applications and challenges. arXiv:​2011.​06225.
Zurück zum Zitat Cody, T., Adams, S., & Beling, P. (2020). Motivating a systems theory of AI. Insight, 23(1), 37–40.CrossRef Cody, T., Adams, S., & Beling, P. (2020). Motivating a systems theory of AI. Insight, 23(1), 37–40.CrossRef
Zurück zum Zitat Freeman, L. (2020). Test and evaluation for artificial intelligence. Insight, 23(1), 27–30.CrossRef Freeman, L. (2020). Test and evaluation for artificial intelligence. Insight, 23(1), 27–30.CrossRef
Zurück zum Zitat Hagedorn, T., Bone, M., Kruse, B., Grosse, I., & Blackburn, M. (2020). Knowledge representation with ontologies and semantic web technologies to promote augmented and artificial intelligence in systems engineering. Incose Insight, 23(1), 15–20. Hagedorn, T., Bone, M., Kruse, B., Grosse, I., & Blackburn, M. (2020). Knowledge representation with ontologies and semantic web technologies to promote augmented and artificial intelligence in systems engineering. Incose Insight, 23(1), 15–20.
Zurück zum Zitat McDermott, T., DeLaurentis, D., Beling, P., Blackburn, M., & Bone, M. (2020). AI4SE and SE4AI: A research roadmap. Incose Insight, 23(1), 8–14. McDermott, T., DeLaurentis, D., Beling, P., Blackburn, M., & Bone, M. (2020). AI4SE and SE4AI: A research roadmap. Incose Insight, 23(1), 8–14.
Zurück zum Zitat McDermott, T. (2019). A framework to guide AI/ML and autonomy research in systems engineering, in 22nd Annual National Defense Industrial Association (NDIA) Systems and Mission Engineering Conference. Tampa, FL. McDermott, T. (2019). A framework to guide AI/ML and autonomy research in systems engineering, in 22nd Annual National Defense Industrial Association (NDIA) Systems and Mission Engineering Conference. Tampa, FL.
Zurück zum Zitat McDermott, T. (2020). Digital engineering and AI—Transformation of systems engineering. Presentation to the International Council on Systems Engineering (INCOSE) Northstar Chapter. McDermott, T. (2020). Digital engineering and AI—Transformation of systems engineering. Presentation to the International Council on Systems Engineering (INCOSE) Northstar Chapter.
Zurück zum Zitat McDermott, T. (2020). Digital engineering and AI—Transformation of systems engineering, in AI welcomes systems engineering: Towards the science of interdependence for autonomous human-machine teams, Association for the Advancement of Artificial Intelligence (AAAI) 2020 Spring Symposium Series. McDermott, T. (2020). Digital engineering and AI—Transformation of systems engineering, in AI welcomes systems engineering: Towards the science of interdependence for autonomous human-machine teams, Association for the Advancement of Artificial Intelligence (AAAI) 2020 Spring Symposium Series.
Zurück zum Zitat Ren, K., Zheng, T., Qin, Z., & Liu, X. (2020). Adversarial attacks and defenses in deep learning. Engineering, 6(3), 346–360.CrossRef Ren, K., Zheng, T., Qin, Z., & Liu, X. (2020). Adversarial attacks and defenses in deep learning. Engineering, 6(3), 346–360.CrossRef
Zurück zum Zitat Selva, D. (2019). Fostering Human Learning from cognitive assistants for design space exploration, in Technical Report SERC-2019-TR-017, Systems Engineering Research Center. Selva, D. (2019). Fostering Human Learning from cognitive assistants for design space exploration, in Technical Report SERC-2019-TR-017, Systems Engineering Research Center.
Zurück zum Zitat Seshia, S. A., Desai, A., Dreossi, T., Fremont, D. J., Ghosh, S., Kim, E., & Yue, X. (2018). Formal specification for deep neural networks, in International Symposium on Automated Technology for Verification and Analysis (pp. 20–34). Springer, Cham. Seshia, S. A., Desai, A., Dreossi, T., Fremont, D. J., Ghosh, S., Kim, E., & Yue, X. (2018). Formal specification for deep neural networks, in International Symposium on Automated Technology for Verification and Analysis (pp. 20–34). Springer, Cham.
Zurück zum Zitat Viros, A., & Selva, D. (2019). Daphne: A virtual assistant for designing earth observation distributed spacecraft missions. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-stars). Viros, A., & Selva, D. (2019). Daphne: A virtual assistant for designing earth observation distributed spacecraft missions. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-stars).
Zurück zum Zitat Wade, J., Buenfil, J., & Collopy, P. (2020). A systems engineering approach for artificial intelligence: Inspired by the VLSI revolution of mead & conway. Insight, 23(1), 41–47.CrossRef Wade, J., Buenfil, J., & Collopy, P. (2020). A systems engineering approach for artificial intelligence: Inspired by the VLSI revolution of mead & conway. Insight, 23(1), 41–47.CrossRef
Metadaten
Titel
Artificial Intelligence and Future of Systems Engineering
verfasst von
Thomas A. McDermott
Mark R. Blackburn
Peter A. Beling
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-77283-3_3