AI Safety: Performance Metrics And Failure Modes

dc.contributor.authorRanieri, C.
dc.contributor.authorLecis, P. O.
dc.contributor.authorCastaldi, L.
dc.date.accessioned2026-08-14T09:30:18Z
dc.date.issued2025
dc.description.abstractAim of this work is to update the safety assessment in order to extend the actual safety rigor to Artificial Intelligence (AI) systems. The results are based on the European Union Aviation Safety Agency (EASA) publications, part of the EASA AI Roadmap (Ref. 1), and the starting point of the entire discussion is the Concept Paper: First usable guidance for level 1&2 application (Ref. 2). In the guideline, the Anticipated-MOC-SA-01-7 asks to specify a link between AI performance metrics and safety assessment: this work shows a direct connection between the performance metrics of an AI binary classification algorithm and its Failure Mode, allowing to provide the link required but also to set safety requirements on the performance metrics that will guide the AI development.
dc.identifier.citation51st European Rotorcraft Forum (ERF 2025), September 9-12, 2025, Venice, Italy : proceeedings. ISBN 9798331335472.
dc.identifier.urihttps://hdl.handle.net/20.500.11881/4779
dc.language.isoen
dc.titleAI Safety: Performance Metrics And Failure Modes

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