Towards Dependable Integration Concepts for AI-Based Systems

AI-based methods are currently on the rise for multiple applications, therefore also their application for autonomous or trustworthy embedded systems is discussed more frequently. There are various ways that can leverage AI-based technologies, but since AI has the potential to affect the key system properties of trustworthy embedded systems, a far higher level of maturity and dependability is required for the implementation of emerging AI-based technologies in safety-critical domains (such as an autonomous vehicle). The TEACHING project focuses on mission-critical, energy-sensitive autonomous systems and the development of technology bricks for humanistic AI concepts. To enhance the development of the technology bricks, the building of a dependable engineering environment to support the development of a self-adaptive artificial humanistic intelligence in a dependable manner is intended. The paper establishes the body of knowledge and fundamental ground for a workshop discussion on engineering methods and design patterns that can be used to develop dependable and AI-based autonomous system development. 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) should provide an updated common view of the diverse fields of expertise and exchange between domain experts during the workshop.