Introducing SAFEXPLAIN: Safe and Explainable Critical Embedded Systems based on AI
Channel: BSC CNS
Date: 2023-11-10

💻Deep Learning (DL) techniques are key for most future advanced software functions in Critical Autonomous AI-based Systems (CAIS) in cars, trains and satellites. Hence, those CAIS industries depend on their ability to design, implement, qualify, and certify DL-based software products under bounded effort/cost. There is a fundamental gap between Functional Safety (FUSA) requirements of CAIS and the nature of DL solutions needed to satisfy those requirements. The lack of transparency (mainly explainability and traceability), and the data-dependent and stochastic nature of DL software clash against the need for deterministic, verifiable and pass/fail test based software solutions for CAIS. 

➡The long-term viability of the SAFEXPLAIN approach will be demonstrated by integrating its solutions in a commercial toolset for system testing, and applying its principles to several mixed-criticality case studies relevant for European society. SAFEXPLAIN will focus on state-of-the-art and representative mixed-criticality case studies from the automotive, railway and space domains.