TEACHING -- Trustworthy autonomous cyber-physical applications through human-centred intelligence
It addresses the problem of enhancing trust and performance in autonomous applications for users in heterogeneous environments, but it is incremental as it builds on existing concepts without introducing a new paradigm.
The paper presents the TEACHING project's vision for developing trustworthy autonomous cyber-physical applications by using human physiological, emotional, and cognitive states to adapt and optimize systems in distributed edge-cloud environments, but it does not report specific results or concrete numbers.
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges