Safety and Resiliency Challenges for Highly Autonomous Intelligent Systems

Intelligent systems, capable of taking autonomous decisions based on AI algorithms, are becoming more and more widespread in several application fields (autonomous robots, autonomous vehicles, smart factories, smart agriculture, etc.). This thanks to their possible adoption to replace and/or collaborate with humans in harsh environments (hospitals, mines, space, etc.) and/or in difficult jobs (goods delivery, surveillance, etc.). Moreover, autonomous robots (e.g., service robots) and vehicles (e.g., drones) are today’s receiving an increasing interest, due to their possible pivotal role in facing the current pandemic emergency and its aftermath. They are complex systems, requiring intelligence at the edge (for low-latency data acquisition and processing), in the network, and up to the cloud and related services. Since such autonomous intelligent systems are in a closed collaboration with human beings and/or the health of human beings may depend on their operation, the need to guarantee their functional safety and resiliency with respect to hazardous conditions emerges. Enabling to increase the autonomy level of such intelligent systems, thus moving towards a smarter world, mandates to satisfy stronger requirements in terms of their functional safety and resiliency. Safety and resiliency challenges to enable highly autonomous intelligent systems are discussed.