Abstract The increased use of Artificial Intelligence (AI) in safety-critical systems such as Automated Driving Systems (ADS) requires a reevaluation of established Systems and Safety Engineering processes to accommodate AI characteristics. Datasets determine an AI system’s (potentially hazardous) behavior significantly. Hence, ISO/PAS 8800 demands dataset requirements, safety analyses, and validation activities in an AI safety lifecycle. This article investigates commonalities between Safety Engineering Activities specified in ISO 21448 and dataset-related activities specified in ISO/PAS 8800. We introduce a model-based approach to support traceability from knowledge about an Operational Design Domain to required dataset requirements and data labels for training and testing AI systems in the scope of ISO/PAS 8800. The approach is demonstrated in an example safety analysis for an L4 hub-to-hub scenario.
Nolte et al. (Fri,) studied this question.