Model Driven Engineering for Resilience of Systems with Black Box and AI-based Components

Modern complex cyber-physical systems heavily rely on humans and AI for mission-critical operations and decision making. Unfortunately, these components are often 'black boxes' to the operator, either because the decision models are too complex for human comprehension (e.g. deep neural networks) or are intentionally hidden (e.g. proprietary intellectual property). In these cases, the decision logic cannot be validated and therefore trust is forced.