Developing a stringent safety-argumentation for AI-based perception functions requires a complete methodology to systematically organize the complex interplay between specifications, data and training of AI-functions, safety measures and metrics, risk analysis, safety goals and safety requirements. The project KI Absicherung has successfully conducted a "Proof of Project Concept" (PoPC) in order to define and exemplify the detailed technical workflow for developing a stringent safety-argumentation for AI-based perception functions in a minimalistic example.
The goal of the "Proof of Project Concept" is to give a minimalistic, but complete example of all required steps in a workflow leading to a stringent safety argumentation for AI-based functions, using concise and agreed notions defining and explaining the relationships and dependencies between the workflow steps. The major results are an exemplary mini-safety argumentation (represented in GSN - Goal Structuring Notation) and the methodology itself, explaining how to begin with safety requirement as starting point and going through an analysis of DNN insufficiencies and DNN specific safety concerns, mitigating them by DNN safety measures, and measuring the success by metrics which lead to providing evidences. In addition, the "Proof of Project Concept" has been implemented at the operational level, thus serving as a blueprint for cooperation and interaction between all sub-projects of KI Absicherung.
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