Insides to Trustworthy AI-based Embedded Systems

AI-based methods are experiencing a rapid surge in adoption across various applications, particularly in the context of autonomous and trustworthy embedded systems. Since AI-based systems then have the potential to affect with mission critical system properties of trustworthy embedded systems, a higher level of maturity and dependability considerations is required to be followed. This paper combines the findings from the TEACHING project, which focuses on technology bricks for humanistic AI concepts, with insights derived from a facilitation workshop involving subject matter experts for dependability engineering. The paper establishes the body of knowledge and fundamental grounds outcomes discussed in an expert workshop at international conference on computer safety, reliability, and security. The assurance of dependability continues to be an open issue with no common solution yet. Therefore, the expert discussion on multiple perspectives related to all factors of the PESTEL analysis (political, environmental, social, technological, economic, and legal) and an updated common view of the diverse fields of expertise. The workshop serves as a platform for domain experts to share their perspectives and collectively refine their understanding of diverse fields of expertise. This work is synthesizing insights from the TEACHING project and expert workshops related, aiming to contribute to the ongoing discourse surrounding the assurance of dependability in AI-driven systems, offering a comprehensive view informed by a multitude of perspectives and factors.