Assuring safety for AI-based'' systems is one of the current challenges in safety engineering. For automated driving systems, in particular, further assurance challenges result from the open context that the systems need to operate in after deployment. The current standardization and regulation landscape for AI-based’’ systems is becoming ever more complex, as standards and regulations are being released at high frequencies. This position paper seeks to provide guidance for making qualified arguments which standards should meaningfully be applied to (AI-based'') automated driving systems. Furthermore, we argue for clearly differentiating sources of risk between AI-specific and general uncertainties related to the open context. In our view, a clear conceptual separation can help to exploit commonalities that can close the gap between system-level and AI-specific safety analyses, while ensuring the required rigor for engineering safe AI-based’’ systems.

生成讲解博客的中文版本

生成AI智能校验的中文版本