7 citations · 13 across the 6 of their papers we have counts for
4 papers · 1 filter
Assurance Cases as Foundation Stone for Auditing AI-enabled and Autonomous Systems: Workshop Results and Political Recommendations for Action from the ExamAI Project
Rasmus Adler, Michael Klaes
The European Machinery Directive and related harmonized standards do consider that software is used to generate safety-relevant behavior of the machinery but do not consider all ki…
Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception
Janek Groß, Rasmus Adler, Michael Kläs +3
Data-driven models (DDM) based on machine learning and other AI techniques play an important role in the perception of increasingly autonomous systems. Due to the merely implicit d…
Towards a Roadmap for Trustworthy Dynamic Systems-of-Systems
Rasmus Adler, Frank Elberzhager, Julien Siebert
This paper gives insights into the DynaSoS project, which aims to propose a cross-domain roadmap for systems engineering research into trustworthy dynamic systems-of-systems with a…
Integrating Testing and Operation-related Quantitative Evidences in Assurance Cases to Argue Safety of Data-Driven AI/ML Components
Michael Kläs, Lisa Jöckel, Rasmus Adler +1
In the future, AI will increasingly find its way into systems that can potentially cause physical harm to humans. For such safety-critical systems, it must be demonstrated that the…