Insides to Trustworthy AI-based Embedded Systems

In an era characterized by the rapid proliferation and advancement of AI-based technologies across various domains, the spotlight is placed on the integration of these technologies into trustworthy autonomous systems. The integration into embedded systems necessitates a heightened focus on dependability. This paper combines the findings from the TEACHING project, which delves into the foundations of humanistic AI concepts, with insights derived from an expert workshop in the field of dependability engineering. We establish the body of knowledge and key findings deliberated upon during an expert workshop held at an international conference focused on computer safety, reliability and security. The dialogue makes it evident that despite advancements, the assurance of dependability in AI-driven systems remains an unresolved challenge, lacking a one-size-fits-all solution. On the other hand, the positive outcome of this dialogue about the dependability of AI in embedded systems is that experts foster a shared understanding across diverse domains of expertise. We enhance the outcomes by considering the entirety of the PESTEL analysis framework encompassing political, environmental, social, technological, economic and legal dimensions. Therefore, this work synthesizes insights aiming to provide a comprehensive view informed by a multitude of perspectives and factors.