  Various mobility applications like advanced driver assistance systems
increasingly utilize artificial intelligence (AI) based functionalities.
Typically, deep neural networks (DNNs) are used as these provide the best
performance on the challenging perception, prediction or planning tasks that
occur in real driving environments. However, current regulations like UNECE R
155 or ISO 26262 do not consider AI-related aspects and are only applied to
traditional algorithm-based systems. The non-existence of AI-specific standards
or norms prevents the practical application and can harm the trust level of
users. Hence, it is important to extend existing standardization for security
and safety to consider AI-specific challenges and requirements. To take a step
towards a suitable regulation we propose 50 technical requirements or best
practices that extend existing regulations and address the concrete needs for
DNN-based systems. We show the applicability, usefulness and meaningfulness of
the proposed requirements by performing an exemplary audit of a DNN-based
traffic sign recognition system using three of the proposed requirements.

Machine Learning;Artificial Intelligence;Cryptography and Security;Computer Vision and Pattern Recognition