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Engineering Future Critical CPSs with Trustworthy GenAI Across the Lifecycle
Mälardalen University, Västerås, Sweden.ORCID iD: 0000-0002-8027-0611
Mälardalen University, Västerås, Sweden.ORCID iD: 0000-0003-0416-1787
Mälardalen University, Västerås, Sweden.ORCID iD: 0000-0001-9881-400X
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Sustainable Digitalisation Research Centre (SDRC).ORCID iD: 0000-0003-0326-0556
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2026 (English)In: Proceedings - 2026 IEEE/ACM 48th International Conference on Software Engineering: Software Engineering in Society, ICSE-SEIS 2026, Association for Computing Machinery, Inc , 2026, p. 142-147Conference paper, Published paper (Refereed)
Abstract [en]

One of the most transformative developments today is the integration of generative artificial intelligence into the development of critical software-intensive cyber-physical systems. From autonomous vehicles to industrial robotics, these systems are entering a new era shaped by artificial intelligence-driven development and automation. In this paper, we consider software engineering, artificial intelligence, artificial intelligence ethics, and social aspects, to explore how such technologies can be harnessed safely, transparently, and with human values at the center. Our contributions include a vision for software engineering, guiding the engineering of future trustworthy safety-critical cyber-physical systems under the influence of generative artificial intelligence. We critically analyze how three established certification principles can be leveraged to cope with the societal and technical tensions introduced by generative artificial intelligence adoption, and propose a research and practice agenda to ensure that future cyber-physical systems development and operations cycle remain trustworthy, both from a system (hardware and software) and from a societal perspective.

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc , 2026. p. 142-147
Keywords [en]
Generative Artificial Intelligence, Software Engineering, Trustworthy
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mau:diva-87381DOI: 10.1145/3786581.3786936Scopus ID: 2-s2.0-105045099303ISBN: 9798400724244 (electronic)OAI: oai:DiVA.org:mau-87381DiVA, id: diva2:2089636
Conference
48th International Conference on Software Engineering: Software Engineering in Society, ICSE-SEIS 2026, 12-18 Apr 2026, Rio de Janeiro, Brazil
Available from: 2026-08-04 Created: 2026-08-04 Last updated: 2026-08-24Bibliographically approved

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Bucaioni, AlessioCicchetti, AntonioCrnkovic, Gordana DodigSpalazzese, RominaSöderberg, EmmaVarró, Dániel
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